No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
A*Prune: An Algorithm for Finding K Shortest Paths Subject to Multiple Constraints
Abstract
We present a new algorithm, A*Prune, to list (in order of increasing length) the first K Multiple-Constrained-Shortest-Path (KMCSP) between a given pair of nodes in a digraph in which each arc is associated with multiple Quality-of-Service (QoS) metrics. The algorithm constructs paths starting at the source and going towards the destination. But, at each iteration, the algorithm gets rid of all paths that are guaranteed to violate the constraints, thereby keeping only those partial paths that have the potential to be turned into feasible paths, from which the optimal paths are drawn. The choice of which path to be extended first and which path can be pruned depend upon a projected path cost function, which is obtained by adding the cost already incurred to get to an intermediate node to an admissible cost to go the remaining distance to the destination. The Dijkstra's shortest path algorithm is a good choice to give a good admissible cost. Experimental results show that A*Prune is comparable to the current best known ffl-approximate algorithms for most of randomly generated graphs. BA*Prune, which combines the A*Prune with any known polynomial time ffl-approximate algorithms to give either optimal or ffl-approximate solutions to the KMCSP problem, is also presented. Keywords---shortest paths, constraint based routing, QoS routing, multiple constrained path selection, Dijkstra algorithm, NP complete. I.
... Using these traces we compared the scalability and optimality of the QROUTE algorithm to the current state-of-theart multi-constrained shortest path (MCSP) algorithms, like A* Prune [21], H_MCOP [22], and MH_MCOP [23]. ...
... There are several works [12], [13], [21]- [24] which solve the multi-constrained shortest path problem using Lagrange relaxation but they generate routes for every source-destination pair and QoS policy instead of generating a routing directedacyclic graph. Thus, their approaches lead to an exponential increase in route computation time and the proliferation of routing entries. ...
... Thus, their approaches lead to an exponential increase in route computation time and the proliferation of routing entries. A*Prune [21] is an optimal approach to solve the MCSP problem by assuming that there is a guess function available for the constraints and costs and the algorithm is made faster by pruning certain paths based on their projected constrained values. However, its run-time increases much faster with network size compared to heuristics based algorithms [21]- [23]. ...
Many computer network applications impose constraints for multiple quality of service (QoS) metrics, e.g., delay, packet loss, bandwidth, and jitter. These QoS constraints cannot be guaranteed by the Internet due to its best-effort service model. Overlay networks have been an effective technique at the application layer to support multiple QoS constraints of networking applications. In software-defined overlay networks, software-defined networking (SDN) paradigm is introduced in the overlay networks to enable centralized and efficient routing of traffic in the overlay networks, thus, enabling better QoS. One of the main challenges in software-defined overlay networks is the fast-changing overlay link QoS characteristics. However, the existing routing algorithms for satisfying multiple QoS constraints in software-defined overlay networks involve high route computation time and thus these routing algorithms cannot adapt to the fast-changing overlay link QoS characteristics. Moreover, as we scale the size of overlay networks, the size of forwarding tables increases exponentially. This is because the existing routing schemes for ensuring multiple QoS constraints use both the source and the destination address for data-plane forwarding. This leads to pushing a huge amount of forwarding table entries by the controller through the network and thus limiting the size of the overlay network. We propose an efficient routing scheme, QROUTE, for satisfying multiple QoS constraints in software-defined overlay networks. QROUTE consists of a control plane routing algorithm which has significantly low route computation time because of employing a novel directed-acyclic-graph (DAG) based approach. QROUTE also reduces the forwarding entries in the data plane by using a QoS-metric-based forwarding scheme. We extensively evaluate QROUTE using traces from a global overlay service provider. We also examine QROUTE on a testbed of P4-BMv2 switches controlled by the ONOS controller using P4Runtime protocol. We find that QROUTE outperforms other state-of-the-art QoS routing schemes in route computation time, size of the forwarding tables and meeting the QoS requirements of various applications.
... IV, we present three solutions: A*Prune, edgebased Dijkstra (EBD) and a graph transformation algorithm (GTA). On the one hand, A*Prune [5], a state-of-the-art algorithm, and EBD, a newly proposed extension of the Dijkstra algorithm [4], are algorithms for the specific, respectively, multi-constrained shortest path (MCSP) and shortest path (SP) problems, which keep their optimality and completeness properties for the new defined classes of metrics. On the other hand, GTA can be used for any routing problem. ...
... A*Prune [5] is a complete and optimal state-of-the-art algorithm able to solve the shortest path (SP) and multiconstrained shortest path (MCSP) problems. Although similar to Dijkstra, A*Prune does not rely on the OSP but is only faster when it is satisfied. ...
... Based on this taxonomy, we presented solutions guaranteeing optimality and completeness. First, we presented A*Prune [5], a state-of-the-art algorithm that can deal with any type of Mn and M∞ metric for solving the shortest path (SP) and multi-constrained shortest path (MCSP) problems. Second, we proposed edge-based Dijkstra (EBD), a newly proposed modification of Dijkstra for solving SP problems with M1 metrics. ...
The routing algorithms used by current operators aim at coping with the demanded QoS requirements while optimizing the use of their network resources. These algorithms rely on the optimal substructure property (OSP), which states that an optimal path contains other optimal paths within it. However, we show that QoS metrics such as queuing delay and buffer consumption do not satisfy this property, which implies that the used algorithms lose their optimality and/or completeness. This negatively impacts the operator economy by causing a waste of network resources and/or violating Service Level Agreements (SLAs). In this paper, we propose a new so-called Mn taxonomy defining new metric classes. An Mn metric corresponds to a metric which requires the knowledge of the n previously traversed edges to compute its value at a given edge. Based on this taxonomy, we present three solutions for solving routing problems with the newly defined classes of metrics. We show that state-of-the-art algorithms based on the OSP indeed lose their original optimality and/or completeness properties while our proposed solutions do not, at the price of an increased computation time.
... IV, we present three solutions: A*Prune, edgebased Dijkstra (EBD) and a graph transformation algorithm (GTA). On the one hand, A*Prune [5], a state-of-the-art algorithm, and EBD, a newly proposed extension of the Dijkstra algorithm [4], are algorithms for the specific, respectively, multi-constrained shortest path (MCSP) and shortest path (SP) problems, which keep their optimality and completeness properties for the new defined classes of metrics. On the other hand, GTA can be used for any routing problem. ...
... A*Prune [5] is a complete and optimal state-of-the-art algorithm able to solve the shortest path (SP) and multiconstrained shortest path (MCSP) problems. Although similar to Dijkstra, A*Prune does not rely on the OSP but is only faster when it is satisfied. ...
... Based on this taxonomy, we presented solutions guaranteeing optimality and completeness. First, we presented A*Prune [5], a state-of-the-art algorithm that can deal with any type of Mn and M∞ metric for solving the shortest path (SP) and multi-constrained shortest path (MCSP) problems. Second, we proposed edge-based Dijkstra (EBD), a newly proposed modification of Dijkstra for solving SP problems with M1 metrics. ...
The routing algorithms used by current operators aim at coping with the demanded QoS requirements while optimizing the use of their network resources. These algorithms rely on the optimal substructure property (OSP), which states that an optimal path contains other optimal paths within it. However, we show that QoS metrics such as queuing delay and buffer consumption do not satisfy this property, which implies that the used algorithms lose their optimality and/or completeness. This negatively impacts the operator economy by causing a waste of network resources and/or violating Service Level Agreements (SLAs). In this paper, we propose a new so-called Mn taxonomy defining new metric classes. An Mn metric corresponds to a metric which requires the knowledge of the n previously traversed edges to compute its value at a given edge. Based on this taxonomy, we present three solutions for solving routing problems with the newly defined classes of metrics. We show that state-of-the-art algorithms based on the OSP indeed lose their original optimality and/or completeness properties while our proposed solutions do not, at the price of an increased computation time.
... 3-In the database center, based on available online maps, realtime traffic data and historical driving data, a set of routes with shortest travel time from node O to node D are located and introduced as candidates for the routing algorithm. Current navigation systems use common K shortest-time routes algorithms for this purpose [25], [26]. Note that, as discussed before, the travel time has the priority to energy efficiency; hence, the shortest-time routing algorithms are employed for finding the candidate routes. ...
... Then, GPS coordinates along with the vehicle code and initial SoC are sent to the database center through communication network. In the database center, the candidate routes are determined based on common shortesttime routing algorithms [25], [26]. Here, it is assumed that the four routes that lead to the shortest travel time are selected. ...
... Note that the cost function can be selected as either the consumed energy for traveling a segment, or travel time or a combination of both. After extracting the speed profile, it must be verified whether it meets the SoC constraints as expressed in (26). The minimum cost function for each route can be then calculated by summing up the obtained minimum cost functions for each segment. ...
A routing algorithm which leads to extended driving range and battery longevity of electric vehicles (EV) is proposed. In addition to locating the time and energy efficient routes, the proposed algorithm provides a desired speed profile to be tracked by the driver. Data mining techniques are employed for extracting the desired speed profile for the goal driver from a set of historical driving data. In order to select data with strong analogy to those of the goal driver's vehicle and driving conditions, driving and vehicle attributes are defined. The historical driving data are clustered and the class of the goal driver among clustered data is determined through classification. Eventually, the required travel time and energy consumption corresponding to historical speed profiles are evaluated and the time and/or energy efficient route along with the desired speed profile are determined. The proposed method is tested on a set of data gathered in the Warrigal project, which provides real vehicle state information. Since the consumed energy data are not available in this dataset, a detailed EV model is adopted to estimate the energy consumption. The obtained results verify the effectiveness of the proposed routing algorithm in locating the time and/or energy efficient routes.
... Stances with free legs or hands are also allowed. At any time, an A* Prune search [Liu and Ramakrishnan 2001] of the stance graph gives us a path to try, and a sampling-based low-level controller is then utilized to optimize and simulate the transitions between stances. Even for a small bouldering route, the stance graph can have thousands of vertices and edges. ...
... A good review on methods for the shortest paths problem can be found in [Eppstein 1998;Eppstein et al. 2016]. In this paper we utilize A* prune [Liu and Ramakrishnan 2001], a general algorithm for returning k shortest paths between two terminal graph nodes. The method is based on the original A*; however, instead of keeping two lists, it only keeps one list of all possible paths to a graph node which is sorted based on heuristics costs (see Section 5.2). ...
... The costs for stance vertices and transitions among them are defined such that the most a-priori preferred path on the stance graph has the lowest cost. To grow the tree, we use A* prune [Liu and Ramakrishnan 2001] in line 7 to find yet not simulated paths from the stance graph. We then use either C-PBP and CMA-ES, two different physically based sampling/optimization methods to optimize and simulate the moves corresponding to each not yet simulated stance path edge. ...
This paper addresses the problem of offline path and movement planning
for wall climbing humanoid agents. We focus on simulating bouldering, i.e.
climbing short routes with diverse moves, although we also demonstrate
our system on a longer wall. Our approach combines a graph-based highlevel path planner with low-level sampling-based optimization of climbing
moves. Although the planning problem is complex, our system produces
plausible solutions to bouldering problems (short climbing routes) in less
than a minute. We further utilize a k-shortest paths approach, which enables
the system to discover alternative paths – in climbing, alternative strategies
often exist, and what might be optimal for one climber could be impossible
for others due to individual differences in strength, flexibility, and reach. We
envision our system could be used, e.g. in learning a climbing strategy, or as
a test and evaluation tool for climbing route designers. To the best of our
knowledge, this is the first paper to solve and simulate rich humanoid wall
climbing, where more than one limb can move at the same time, and limbs
can also hang free for balance or use wall friction in addition to predefined
holds.
... The allocation of optimal bit among DFD and DVF is a multi constraint shortest path (MCSP) problem. R-D problem is not feasible to solve using graph search since it is shown as N-P hard (Gang and Ramakrishnan 2001). The lagrangian optimization technique is the most admired and extensively accepted technique for optimal bit allocation at a few distortion levels. ...
... A* search algorithm (Gang and Ramakrishnan 2001;Choudhury et al. 2020) can be used to obtain the solution to Eq. (1) for the optimization problem. To solve Eq. (1), only two constraints (R = 2), i.e., bit rate and distortion, are considered for optimization problems related to video compression. ...
Today, everyone is demanding high-quality video services along with large bandwidth. Due to this demand, a ruthless burden is felt across the network architecture. Thus, a recently developed video codec H.265, also called high-efficiency video coding (HEVC), offers high coding efficiency than its predecessor H.264 Advanced Video Coding. Although H.265 or HEVC offers a greatly improved compression ratio, it is done at the expense of a high increase in computational complexity and time complexity to process the video compression. This disadvantage of HEVC makes it less suitable for real-time video sequences that may contain varying motion activities. Therefore, it is insufficient to use conventional motion estimation techniques that consume 80–90% of the total computational power. The research work presented in this paper deals with these two-short coming of H.265 HEVC. In this paper, first, an improved motion estimation technique is presented, which yields higher compression efficiency, computational complexities and better video quality, especially for low and medium video resolution applications such as handheld devices based videotelephony. Experimental results using improved motion estimation technique based on Quadtree decomposition and A* prune algorithm optimization reveals that total bits for different multi constraints shortest path get reduced while retaining the quality of video in reconstruction part. Besides, it can also be used in various multimedia applications with restricted computational resources.
... The allocation of optimal bit among DFD and DVF is a multi constraint shortest path (MCSP) problem. R-D problem is not feasible to solve using graph search since it is shown as N-P hard (Gang and Ramakrishnan 2001). The lagrangian optimization technique is the most admired and extensively accepted technique for optimal bit allocation at a few distortion levels. ...
... A* search algorithm (Gang and Ramakrishnan 2001;Choudhury et al. 2020) can be used to obtain the solution to Eq. (1) for the optimization problem. To solve Eq. (1), only two constraints (R = 2), i.e., bit rate and distortion, are considered for optimization problems related to video compression. ...
Today, everyone is demanding high-quality video services along with large bandwidth. Due to this demand, a ruthless burden is felt across the network architecture. Thus, a recently developed video codec H.265, also called high-efficiency video coding (HEVC), offers high coding efficiency than its predecessor H.264 Advanced Video Coding. Although H.265 or HEVC offers a greatly improved compression ratio, it is done at the expense of a high increase in computational complexity and time complexity to process the video compression. This disadvantage of HEVC makes it less suitable for real-time video sequences that may contain varying motion activities. Therefore, it is insufficient to use conventional motion estimation techniques that consume 80–90% of the total computational power. The research work presented in this paper deals with these two-short coming of H.265 HEVC. In this paper, first, an improved motion estimation technique is presented, which yields higher compression efficiency, computational complexities and better video quality, especially for low and medium video resolution applications such as handheld devices based videotelephony. Experimental results using improved motion estimation technique based on Quadtree decomposition and A* prune algorithm optimization reveals that total bits for different multi constraints shortest path get reduced while retaining the quality of video in reconstruction part. Besides, it can also be used in various multimedia applications with restricted computational resources.
... The problem of finding the k shortest paths (kSP) between two nodes (or the kSPT from one node to several destinations) A*Prune [43] kSPMC [2] E MCOP [44] SMS-PBO [45] kLARAC [46] Algorithms that Can Use BD for SP Only (Sec. IV-B) LDP also arises often as a subroutine of more complex algorithms (e.g., kDCBF, see Sec. ...
... First, CBF [42], A*Prune [43] and SMS-PBO [45] have a specific structure making use of no underlying (k)SP/SPT algorithm and can hence not make use of BD. Second, kSPMC [2], E MCOP [44] and kLARAC [46] exclusively make use of kSP and SP algorithms to which no bound can be provided. ...
The shortest path (SP) and shortest paths tree (SPT) problems arise both as direct applications and as subroutines of overlay algorithms solving more complex problems such as the constrained shortest path (CSP) or the constrained minimum Steiner tree (CMST) problems. Often, such algorithms do not use the result of an SP subroutine if its total cost is greater than a given bound. For example, for delay-constrained problems, paths resulting from a least-delay SP run and whose delay is greater than the delay constraint of the original problem are not used by the overlay algorithm to construct its solution. As a result of the existence of these bounds, and because the Dijkstra SP algorithm discovers paths in increasing order of cost, we can terminate the SP search earlier, i.e., once it is known that paths with a greater total cost will not be considered by the overlay algorithm. This early termination allows to reduce the runtime of the SP subroutine, thereby reducing the runtime of the overlay algorithm without impacting its final result. We refer to this adaptation of Dijkstra for centralized implementations as bounded Dijkstra (BD). On the example of CSP algorithms, we confirm the usefulness of BD by showing that it can reduce the runtime of some algorithms by 75% on average.
... For each climbing route, we build a stance graph and use it for planning one or multiple stance paths, denoted by p(σ 0 , σg), which are sequences of stance-to-stance transitions or paths in the stance graph Gσ starting from the initial stance σ 0 and ending at the goal stance σg. Stance paths are planned with A* prune [LR01] such that they pass through a user specified stance σstart where the hands are on predefined starting hand holds. In real-life bouldering, one should first commence climbing by grabbing the predefined starting hold(s). ...
... We use A* Prune algorithm [LR01] to find one or more minimum cost paths from the initial stance to a goal stance. Typically, we only use the first found path to the goal hold, but it can be interesting to compare various alternative solutions to a climbing problem. ...
... Input: Weighted DAG G = (V, E), a BDD representing the logical constraints on path s, t ∈ V Output: The shortest path from s to t that satisfies the logical con- 2: for Select every e i j ∈ E in topological order do 3: (v, u) ← source and target vertices of e i j 4: for all BDD node α which is key to Cost [v][α] do 5: β ← followBDD(e i j , α) 6: if β = ⊥ then continue 7: if label(β) = e i j then 8: β ← hi(β) 9: if 13: while Source vertex of e is not s do 14: u ← source vertex of e 15: Output e; 16: Back [v][α] stores the state just before reaching state (v, α). Subroutine followBDD(e, α) visits BDD nodes by following lo-edges from node α until the label of the visited node is not less than e and returns the last visited node β. ...
... However, since existing studies treat very few constraints, we suspect that this approach would impractical with dozens or more disjunctive pairs. The A * approach has also been studied for MRCSP [13]. It has some common points with our method in the sense that unconstrained DAG shortest paths are used by a heuristic function. ...
This paper deals with the constrained DAG shortest path problem (CDSP), which finds the shortest path on a given directed acyclic graph (DAG) under any logical constraints posed on taken edges. There exists a previous work that uses binary decision diagrams (BDDs) to represent the logical constraints, and traverses the input DAG and the BDD simultaneously. The time and space complexity of this BDD-based method is derived from BDD size, and tends to be fast only when BDDs are small. However, since it does not prioritize the search order, there is considerable room for improvement, particularly for large BDDs. We combine the well-known A* search with the BDD-based method synergistically, and implement several novel heuristic functions. The key insight here is that the ‘shortest path’ in the BDD is a solution of a relaxed problem, just as the shortest path in the DAG is. Experiments, particularly practical machine learning applications, show that the proposed method decreases search time by up to 2 orders of magnitude, with the specific result that it is 2,000 times faster than a commercial solver. Moreover, the proposed method can reduce the peak memory usage up to 40 times less than the conventional method.
... According to [22], it has been proved that the CSP problem is NP-complete and some approximation and heuristic algorithms have been proposed in many literatures [16,22]. The Lagrangian Relaxation Based Aggregated Cost (LARAC) algorithm is one of the most promising and polynomial-time algorithms in which the lower bound for optimal value of the CSP problem is provided. ...
... According to [22], it has been proved that the CSP problem is NP-complete and some approximation and heuristic algorithms have been proposed in many literatures [16,22]. The Lagrangian Relaxation Based Aggregated Cost (LARAC) algorithm is one of the most promising and polynomial-time algorithms in which the lower bound for optimal value of the CSP problem is provided. ...
Software Defined Network (SDN) is a new network technology which allows network providers to afford predefined Quality of Service (QoS) for video streaming applications. Network administrators can develop desired traffic engineering techniques over SDN and support Quality of Experience (QoE) and QoS for their customers. One of the most important issues in traffic engineering is to find favorable links for routing between source and destination. The fitness of each link in the network depends on the end users QoE and the applications they are used. In this paper to achieve optimal routes, the fitness of each link is determined by type-2 fuzzy sets. Then, an adaptive traffic engineering method is proposed to find the best routes between source cameras and monitoring center in a video surveillance system. The proposed method is based on Constraint Shortest Path (CSP) problem and calculates minimum cost path which satisfies delay constraint. Due to NP-completeness of the CSP problems, LARAC algorithm is used to solve it. To the best of our knowledge, this is the first proposed traffic engineering technique which is based on type-2 fuzzy set for video streaming applications over SDN. The contribution of the proposed method regarding to the related works, is to apply type-2 and type-1 fuzzy logic for calculating the costs of network links based on QoE for providing QoS in a video surveillance system. In addition, this paper models the provisioning of QoS in a real scenario and emulates them in a network emulator. Many comparisons carried out between the proposed method and other well-known methods to show the effectiveness of the proposed method in terms of packet loss, delay and PSNR.
... But those links do not provide the required reliability for specific applications like Standard Definition (SD) and High Definition (HD). The network reliability problem is solved using the A* prune algorithm [63]. The results show that RVSDN processed more requests with high reliability when compared to VSDN. ...
Software Defined Network (SDN) is a new emerging technology that has attracted enormous interest over the last few years as a result of existing networking designs’ constraints. It allows a centralized programmable controller to interface with forwarding devices and is utilized in a variety of communication networking scenarios, including Service Provider networks, Campus networks, Hospitality networks, Video communication, etc. One of the promising applications is multimedia services to provide strict delay guarantees for the transferred flows. The video traffic demands a guaranteed Quality of Service (QoS) to provide a smooth consumer experience. Several QoS models have been proposed in the literature and individual studies are presented to measure the QoS metric. An overview of interesting research on QoS models for video streaming over SDN, issues in video streaming models, existing QoS models, QoS metrics used for emulation, and limitations of QoS models are presented in this paper.
... A*-search is a well-known searching strategy in Artificial Intelligence. This present study used the A* prune as presented by Liu and Ramakrishnan [40], with some changes to the definitions and steps. A* prune combines A* search algorithm and proper pruning techniques to better prune algorithms. ...
Organisations and governments constantly face potential security attacks. However, the need for next-generation cyber defence has become even more urgent in a day and age when attack surfaces that hackers can exploit have grown at an alarming rate with an increase in the number of devices that are connected to the Internet. As such, next-generation cyber defence that relies on predictive analysis is more proactive than existing technologies that rely on intrusion detection. Many approaches with which to detect and predict attacks have been proposed in recent times. One such approach is attack graphs. The primary purpose of an attack graph is to not only predict an attack but its next steps within a network as well as. More specifically, an attack graph depicts the paths that an attacker may employ to circumvent network policies by exploiting interdependencies between the vulnerabilities. However, extant attack graphs are plagued with a few issues. Scalability is just one of the main issues that attack graph generation faces. This is because an increase in the number of devices used increases the number of vulnerabilities within a network. This, in turn, increases the complexity as well as the amount of time required to generate an attack graph. At present, existing studies that have used attack graphs to predict the subsequent steps during an attack have had to manually assigned the attack location for attack graph analysis. In order to overcome this limitation, this present study recommends the use of intelligent agents to reduce reachability time by calculating between the nodes as well as using the A* prune algorithm to remove useless edges and reduce attack graph complexity. For the attack graph analysis, the random forest (RF) algorithm was used to detect, predict, and dynamically ascertain the attack location in the network. The results of the attack graph generation experiment revealed that the A* prune attack graph produced better results than existing attack graphs. Abstract Organizations and governments constantly face potential security attacks. However, the need for next-generation cyber defense has become even more urgent in a day and age when attack surfaces that hackers can exploit have grown at an alarming rate with an increase in the number of connected devices to the Internet. The next-generation cyber defense that relies on predictive analysis is more proactive than existing technologies that rely on intrusion detection. Many approaches with which to detect and predict attacks have been proposed in recent times. One such approach is attack graphs. The primary purpose of an attack graph is to not only predict an attack but its next steps within a network as well. More specifically, an attack graph depicts the paths that an attacker may employ to circumvent network policies by exploiting interdependencies between the vulnerabilities. However, extant attack graphs are plagued with a few issues. Scalability is just one of the main issues that attack graph generation faces. This is because an increase in the number of devices used increases the number of vulnerabilities within a network. This, in turn, increases the complexity as well as the amount of time required to generate an attack graph. At present, existing studies that have used attack graphs to predict the subsequent steps during an attack have manually assigned the attack location for attack graph analysis. In order to overcome this limitation, this present study recommends the use of intelligent agents to reduce reachability time by calculating between the nodes, as well as using the A* prune algorithm to remove useless edges and reduce attack graph complexity. For the attack graph analysis, the random forest algorithm was used to detect, predict, and dynamically ascertain the attack location in the network. The results of the attack graph generation experiment revealed that the A* prune attack graph produced better results than existing attack graphs.
... The validation of the proposed algorithm is done for both type of coders and found K multiconstraint shortest paths (K-MCSP) [16,29]. Recently it is found that a large portion of multimedia data transmitted in the mobile domain. ...
Advance Video Coder (H.264/AVC) and High-Efficiency Video (H.265/HEVC) coders are fast developing video compression standards, provides high compression and quality of service as compared to previously established standards. The present work focuses on the technical features of both the coder and finds the research gap between them. In this paper an A*prune algorithm and optimization technique is integrated into a multi-constraint environment and generates K-multiple constraints based shortest paths (K-MCSP). These K-MCSPs are provides high compression and quality of service for an input video stream. In this paper proposed algorithm is implemented for both H.264/AVC and H.265/HEVC encoders and discusses the simulation results for different test video sequences. Proposed algorithm is validated with the simulation results for both type of encoders. It is found that, in case of H.264/AVC for slow motion video sequence a good quality of reconstructed video sequence is achieved with 5615 total bit budget, 97.71 s time complexity and 30.14 dB PSNR at 5fps and 3731bits total bit budget, 85.44 s time complexity 32.75 dB PSNR at 10fps. Similarly, 805 total bits, 45.10 s time complexity Multimedia Tools and Applications https://doi. and 34.77 dB PSNR achieved at 30fps. Fast motion video sequence reconstructed with 10778bits total bit budget, 76.10 s time complexity and 30.15 dB PSNR at 5fps and 10,666 total bit budget, 67.34 s time complexity and 30.17 dB PSNR at10fps. Similarly, 8898bits total bit budget, 69.55 s time complexity and 30.94 PSNR achieved at 30fps. In H.265/HEVC, frame has been reconstructed with PSNR 29.72 dB and a bit budget of 12,139 bits with time complexity of 106.33 s at 5fps. Similarly, frame has been reconstructed with PSNR 31.18 dB and a bit budget of 11,167 bits with time complexity of 100.53 s and PSNR 33.37 dB and a bit budget of 8896 bits with time complexity of 96.77 Seconds at frame rate 10fps and 30fps respectively.
... Both K-MCSP and MCSP problem are NP-complete problem meaning it is not possible for any efficient algorithms (polynomial or pseudo polynomial time) to find a realistic path satisfying multiple constraints simultaneously. A*prune algorithm which list the first k-multiple constraint shortest paths satisfies multiple quality-of-service (QoS) constraints as proposed in [13]. ...
Motion Estimation (ME) is one of the vital components in video coding standards. Many motion estimation techniques are developed by researchers but out of these, motion estimation using block matching algorithm (BMA) is most broadly used for estimating the motion vectors in most efficient manner. Therefore, an efficient representation of motion vectors (MVs) and its transmission is the most crucial step of video coding standards to achieve better coding efficiency with minimum degradation in video quality. Since motion estimation consumed about 70%–90% of total computational power, hence reducing the redundancy and computational complexity is need of hour and one of most widely used area of research in the last few decades. In this paper, first a review of various block matching algorithms along with their limitations is done and then a modified block matching algorithm using quadtree decomposition is proposed for finding the optimal solution for rate distortion trade-off which is termed as rate distortion optimization (RDO) problem in video coding. Moreover, K-Multiple Constrained Shortest Path (K-MCSP) algorithm which uses non-linear function in place of linear function is used for finding the shortest paths & best feasible path instead of Multiple Constrained Shortest Path (MCSP). It is experimentally tested for the first six frames of three benchmarking test video namely News, Mother Daughter and Foreman. In all the cases, distribution of bits among DVF and DFD are calculated and it is found that they satisfy the given constraints. The experimental testing demonstrate that the proposed technique is able to decrease the computational complexity by 8–20% with minimum variation in PSNR for all K-MCSP paths to compromise between DVF and DFD which is not achievable in fixed block size matching algorithms (FSBMA).
... Several algorithms use the same principle but order the paths differently within the queue, relying either on a lexicographical ordering, ordered aggregated sums, or a simple FIFO/LIFO ordering [51,52,12]. Most notably, A* Prune [45] is a multi-metric adaptation 3 of A* relying on a PQ where paths known to be unfeasible are pruned. Twophase methods [61] first find paths lying on the convex hull of the Pareto front through multiple Dijkstra runs, before finding the remaining non-dominated path through implicit enumerations. ...
With a growing demand for quasi-instantaneous communication services such as real-time video streaming, cloud gaming, and industry 4.0 applications, multi-constraint Traffic Engineering (TE) becomes increasingly important. While legacy TE management planes have proven laborious to deploy, Segment Routing (SR) drastically eases the deployment of TE paths and is thus increasingly adopted by Internet Service Providers (ISP). There is a clear need in computing and deploying Delay-Constrained Least-Cost paths (DCLC) with SR for real-time interactive services. However, most current DCLC solutions are not tailored for SR. They also often lack efficiency or guarantees. Similarly to approximation schemes, we argue that the challenge is to design an algorithm providing both performances and guarantees. However, conversely to most of these schemes, we also consider operational constraints to provide a practical, high-performance implementation. We leverage the inherent limitations of delay measurements and account for the operational constraint added by SR to design a new algorithm, best2cop, providing guarantees and performance in all cases. Best2cop outperforms a state-of-the-art algorithm on both random and real networks of up to 1000 nodes. Relying on commodity hardware with a single thread, our algorithm retrieves all non-superfluous 3-dimensional routes in only 250ms and 100ms respectively. This execution time is further reduced using multiple threads, as the design of best2cop enables a speedup almost linear in the number of cores. Finally, we extend best2cop to deal with massive scale ISP by leveraging the multi-area partitioning of these deployments. Thanks to our new topology generator specifically designed to model the realistic patterns of such massive IP networks, we show that best2cop solves DCLC-SR in approximately 1 second even for ISP having more than 100000 routers.
... Comparison of singletree segmentation results of the TG, CSP, and PCS algorithms the interested reader might consultLiu and Ramakrishnan (2001) orZhang et al. (2020). ...
Forest resource management and ecological assessment have been recently supported by emerging technologies. Terrestrial laser scanning (TLS) is one that can be quickly and accurately used to obtain three-dimensional forest information, and create good representations of forest vertical structure. TLS data can be exploited for highly significant tasks, particularly the segmentation and information extraction for individual trees. However, the existing single-tree segmentation methods suffer from low segmentation accuracy and poor robustness, and hence do not lead to satisfactory results for natural forests in complex environments. In this paper, we propose a trunk-growth (TG) method for single-tree point-cloud segmentation, and apply this method to the natural forest scenes of Shangri-La City in Northwest Yunnan, China. First, the point normal vector and its Z-axis component are used as trunk-growth constraints. Then, the points surrounding the trunk are searched to account for regrowth. Finally, the nearest distributed branch and leaf points are used to complete the individual tree segmentation. The results show that the TG method can effectively segment individual trees with an average F -score of 0.96. The proposed method applies to many types of trees with various growth shapes, and can effectively identify shrubs and herbs in complex scenes of natural forests. The promising outcomes of the TG method demonstrate the key advantages of combining plant morphology theory and LiDAR technology for advancing and optimizing forestry systems.
... The idea is to optimize one metric (e.g., delay) and then to prune the tree locally by discarding links that violate the bound assigned to another metric (e.g., reliability). The shortest path algorithm with pruning is fast and has relatively small computational complexity [34]. ...
Ad hoc wireless networks have aroused much interest of the scientific community in the last two decades. The provision of Quality of Service (QoS) is a prominent challenge in this research field, since these networks are prone to suffer from instabilities related to wireless medium and mobility. Depending on application, the protocol needs to consider two or more QoS criteria when solving the routing problem. In this context, this work proposes a multicriteria and adaptive framework for proactive routing in order to generate promising compromise solutions by considering critical network quality indicators. Two new methods are proposed—one based on weighted sum method and another based on compromise method (\(\varepsilon\)-constraint)—and compared with the standard weighted sum method. Aiming to map a single final solution, a utility function is proposed to support the definition of the parameters (weights and constraints) of each method. The results show the framework, jointly with the proposed methods, were efficient in promoting significant improvements in the quality indicators investigated in static and mobile scenarios.
... Constrained shortest path algorithms: Liu and Ramakrishnan [47] proposed a heuristic algorithm that solved the K Multiple-Constrained-Shortest-Path problem (KMCSP) in the networks. They applied the A*-search strategy and a proper pruning technique to solve the KMCSP problem. ...
In traditional networks, routing table is essential for packet transmission due to the lack of the direction information abut destination in the head of packet. However, it is feasible to make the address of device encode the routing information with the application of data technology. In this paper, we propose new identities for networking routers-vectors, and a new routing principle based on these vectors is designed accordingly. These vectors encode the device distance information and serve as a pattern of the network topology. Then, routing decisions could be made by these vector calculations and only requirement of table query on the destination vector following the proposed routing principle. The proposed method is not limited in calculating the shortest path routing, but extend to solve the constrain routing problem. Besides, multi-paths routing is also available as long as multi-paths exist between the origin-destination pairs. The simulation results show that our proposed method works reliable and stable in routing tasks, and can achieve a remarkable performance when compared with the state-of-the-art work on the delay constrained least cost path (DCLC) problem.
... Constraints are often introduced into flight travel planning problems so that they can be modeled as QoS-aware network problems. Heuristic algorithms have been designed to find paths with the minimum cost in a QoS-aware network with constraints [2,3,10]. Many researchers have also studied bio-inspired algorithms to solve QoSaware network problems [11,12]. ...
The rapid growth of the airline industry has resulted in the availability of a large number of flights, however this can also create a paralyzing problem. Flight information on all airlines across the world can be obtained via the Internet. Today, passengers trend to be interested in user personalized service. How to effectively find a passenger’s most preferred air travel plan, which might include multiple transfers from millions of possible choices with certain constraints, such as time and price, is a critical challenge. This paper presents an efficient air travel planning approach, which can find a number of air travel plans by invoking the APIs offered by airline companies. At the same time, these plans also best match the customer’s preference based on an analysis of historical orders. An algorithm to extract user preference features is introduced and heuristic rules to speed up the K path search process under constraints are presented. The experiment results show that the proposed model finds optimal air travel plans efficiently on a real-world dataset.
... Then branch and cut or other gap closing method [5] is used to solve similar problems. Because what we can get from (3.2.5)is not a directly feasible solution for the original problem, the time consuming gap closing process can't be avoid. ...
Given an undirected graph and nonnegative numbers as weights for each edge, we consider the problem of finding a spanning tree that has lowest total cost with respect to cost weight and has constrained budget with respect to constrains weight [1]. Different from the traditional Lagrangean relaxation method, we proposed a new randomized method for solving the constrained spanning tree problem in this paper. For this newly proposed method every solution found is in the original problem’s feasible region, there is no need to do the hard work to close the gap between the Lagrangean relaxation and the original problem. And the proposed algorithm is very easy to parallelize, can take full advantage of multi-core processors to improve problem solving efficiency. For most optimization algorithms, properly selecting the super parameters have big impact on the algorithm’s practical performance. Through computer numerical simulation, we can see that our algorithm is robust to super parameters.
... Furthermore, we have conducted a heuristics, i.e. A*Prune Algorithm [16], to find a feasible path through the network. In all scenarios, in the first part of the experiments, we have provided enough bandwidth (100 Gbps) in links so that there is no service request rejection due to network resource limitations, while, in the second part of the experiments, we have reduced the link bandwidth to 1 Gbps to see their performances under network resource limitations. ...
... Therefore, links are labeled with these four metrics and reliability has high priority in path selection. They argue that they modeled the problem as Multiple Constrained Shortest Path (MCSP) and used A*Prune [226] algorithm for solving it. They showed that VSDN could support a low number of satisfied requests when a high-reliability value is requested compared to RVSDN. ...
In today’s Internet, killer network services and applications such as video and audio streaming, network storage, and online video games are pushing the network infrastructure resources to the edge. By design and for the most part, the Internet is best offer delivery ecosystem with little or no end-to-end Quality of Service (QoS) guarantees. Even, frameworks such as IntServ and DiffServ that were designed and implemented to provide QoS guarantees still fail to solve this problem at a wide scale. Software Defined Networking (SDN) is a fast emerging networking paradigm that promises to provide end-to-end QoS guaranteeing by offering greater network flexibility, abstraction, control and programmability to network resources. In this article, we review, survey, and discuss the current state-of-the-art on QoS provisioning in the area of SDN, with respect of applying the concept of Autonomic Computing (AC) to automatically support, provision, monitor and maintain QoS requirements. The article includes in-depth classification, taxonomy, and comparative analysis for autonomic-based QoS provisioning in accordance with the famous influential and widely adopted Monitor-Analyze-Plan-Execute-Knowledge (MAPE-K) IBM architectural model for autonomic computing.
... Also, we have used a modified version of Waxman (1988) random topology generator defined by Erdos-Renyi random graph model to randomly create the networks while preserving connectivity degrees of nodes (i.e., switches) as three in all switch cases and models. Furthermore, we have used a heuristics, i.e., A * Prune Algorithm (Liu and Ramakrishnan, 2001), to find a feasible path through the network because constraint-based routing with two or more constraints has been shown to be an NP-hard (Younis and Fahmy, 2003). A * Prune algorithm combines A * -search with a correct pruning technique. ...
As new networking architectures such as 5G start materializing in the next era of communication revolution, economic and operational facets of these future networks drive researchers to rethink about their capabilities of flexibility, agility, programmability, and cost-effectiveness. These are the main features to make networks like 5G (fifth-generation) possible and available for societies shortly because they are the fundamental catalysts to achieve economic success in a network. It is vital for network owners to analyze and understand economic aspects of a network architecture before deciding to invest in it. In this article, we introduce a framework utilizing an activity-based approach for the techno-economic analysis of network architectures. In particular, we perform an economic analysis of SDN (Software Defined Networking) technology and MPLS (Multiprotocol Label Switching) technology in order to understand how programmable networking, i.e., SDN technology, affects the network economics compared to traditional networking, i.e., MPLS technology. To this end, we firstly conduct a quantitative analysis exploiting an activity-based approach for CAPEX (Capital Expenditure) and OPEX (Operational Expenditure) calculations of a network. Secondly, we evaluate the architectures above concerning their economic performances using two metrics: Unit Service Cost Scalability metric and Cost-to-Service metric. Also, we present mathematical models to calculate certain cost parts of a network. Also, we compare different popular SDN control plane models, Centralized Control Plane (CCP), Distributed Control Plane (DCP), and Hierarchical Control Plane (HCP), to understand their economic impact with regards to the defined metrics. We use video as the service with different traffic patterns for the comparison. This work aims at being a useful primer to providing insights regarding which technology and control plane model(s) are appropriate for a specific service, i.e., video, for network owners to plan their investments.
... But, owing to VANETs high link instability, the exact QoSaware routing algorithms proposed in the literatures are not suitable for solving the MCOP problem. Different approaches such as: nonlinear definition of the path length [144], look-ahead feature [145], non-dominal paths [146], Dijkstra-like path search [147], and k shortest path [148], ...
Vehicular ad hoc networks (VANETs) present an intriguing platform for several applications on e.g., intelligent transportation system (ITS) and infotainment applications aspire to be the main pattern of communication among vehicles while travelling. This can significantly impact on the amount of data exchanged by vehicles, increasing the contention on communication links and thus, degrading the quality of service of these applications. So, discrimination of data becomes imperative and forwarding critical information on suitable routes becomes decisive. Hence, a quality of service (QoS)-driven mechanism is needed to handle and assign network resources according to the stringent application data traffic demands. But, VANETs high node mobility and frequent link failure, stuck a big challenge in implementing an effective policy to meet and enforce these QoS requirements. A promising way to tackle this issue is to enforce QoS at the network layer, since it is the crucial point in VANETs’ communication. So, over the years, many QoS-aware routing protocols were specifically conceived for VANETs. In this paper, we present a comprehensive survey of QoS-aware routing protocols in VANETs’ literature. We examined the protocols based on their ability to support ITS infotainment services, their multi-constraint path problem (MCP), protocol’s functionality and weakness, objectives and design challenges. This way, we outline future directions for VANETs QoS-aware protocol research.
... El algoritmo A*Prune [31] considera el hecho de encontrar no sólo uno, sino múltiples caminos más cortos que están dentro de las restricciones. La función de longitud lineal usada en este algoritmo es la misma utilizada en el algoritmo Jaffe's. ...
El enrutamiento en Internet está basado en la dirección destino y en un algoritmo del camino más corto, esto conlleva a que se congestionen ciertos enlaces debido a que se seleccionan los mismos caminos para muchas comunicaciones. Por otro lado, los algoritmos basados en restricciones toman las decisiones de selección del camino con base en un conjunto de requerimientos que permite escoger el camino más óptimo para un conjunto de restricciones específi co, resolviendo el problema del enrutamiento del camino más corto y proporcionando ventajas adicionales como el soporte de calidad de servicio e ingeniería de tráfi co . En la literatura se ha demostrado que los procesos de los objetivos de ingeniería de tráfi co son NP-díficil, y los de calidad de servicio son NP-completo, esto conduce a que sea un tema abierto para hacer propuestas de algoritmos heurísticos. Por tanto, en este artículo se presenta una revisión general de los algoritmos basados en restricciones propuestos como solución al problema de enrutamiento convencional de Internet en los últimos 15 años, los cuales se han organizado en tres categorías según los objetivos trazados en cada uno de ellos. Estas categorías están enfocadas a las problemáticas actuales en Internet que son la provisión de ingeniería de tráfi co y calidad de servicio. Se presenta una breve descripción de cada uno, resaltando las restricciones utilizadas y los objetivos trazados. Un conocimiento de la taxonomía de estos algoritmos y sus objetivos permite plantear nuevas alternativas al enrutamiento para redes de nueva generación, con nuevas exigencias en sus servicios.
... Due to NP-completeness of the CSP problem, some heuristic and approximation algorithms have been proposed in literatures (Liu and Ramakrishnan 2001;Mohammadi and Javidan 2016). In this paper, TLBO (Rao et al. 2011) is used to solve ...
Telesurgery is a form of surgery in which a remote surgeon can perform surgical operation on a patient over a distance using robots. Due to human life is at stake, telesurgery is a high risk operation. Therefore, safety is one of the most important issues in telesurgery. Implementing appropriate mechanisms and protocols over communication network in order to transmit telesurgical traffics effectively, can improve the safety of telesurgery. The limitations of traditional IP-based protocols make it difficult to provide quality of service (QoS) for telesurgery. Fortunately, the advent of software defined network (SDN) facilitates to provide and guarantee QoS for most applications such as telesurgery. This paper investigates the feasibility of telesurgery over SDN, and proposes an SDN-based network architecture for the implementation of telesurgery. The proposed architecture considers all communication aspects of telesurgery and manages telesurgical traffics by using an efficient traffic engineering (TE) technique. To prove the effectiveness of our proposed architecture and TE method, we conducted extensive simulations for telesurgery application. Experimental results confirm that the proposed solution can be practically used for telesurgery and improve the performance of telesurgery in terms of QoS parameters.
... El algoritmo A*Prune [31] considera el hecho de encontrar no sólo uno, sino múltiples caminos más cortos que están dentro de las restricciones. La función de longitud lineal usada en este algoritmo es la misma utilizada en el algoritmo Jaffe's. ...
Internet routing is based on the destination address and a shortest path algorithm, this leads to some links are congested because the same paths are selected for many communications. On the other hand, constraint based algorithms select the path based on a set of requirements that allows choosing the most optimal path for a specific set of constraints, solving the problem of the shortest path routing and providing additional benefits such as support QoS and traffic engineering. In the literature, it has been shown that the processes with traffic engineering objectives are NP-hard, and for quality of service are NP-complete, it allows making heuristic algorithms proposals because this is an open issue. Therefore, this article provides an overview of the constraint based algorithms proposed as a solution to the problem of conventional Internet routing in the last 15 years. This study has been organized into three categories according to the goals for each proposal. These categories were targeted in Internet current issues that are Traffic Engineering and Quality of Service support. A brief description of each algorithm is presented, highlighting their objectives and constraints. It is very important to highlight that to propose solutions to these issues remains a challenge and is an open issue, for this reason to have a knowledge of the taxonomy of these algorithms and objectives allows us to propose new alternatives to routing for next generation networks, with new demands on their services.
... Carlyle and Wood [19] proposed a new algorithm for solving the problem of enumerating all near-shortest simple (loopless) paths in a graph with nonnegative edge lengths. Liu and Ramakrishnan [20] presented a new algorithm, * Prune, to list the first Multi-Constrained-Shortest Path (KMCSP) between a given pair of nodes in a digraph. Although there exist a lot of -shortest algorithms, few of them have been used for solving the reliability-based path finding problem. ...
There is a growing interest in finding a global optimal path in transportation networks particularly when the network suffers from unexpected disturbance. This paper studies the problem of finding a global optimal path to guarantee a given probability of arriving on time in a network with uncertainty, in which the travel time is stochastic instead of deterministic. Traditional path finding methods based on least expected travel time cannot capture the network user’s risk-taking behaviors in path finding. To overcome such limitation, the reliable path finding algorithms have been proposed but the convergence of global optimum is seldom addressed in the literature. This paper integrates the K -shortest path algorithm into Backtracking method to propose a new path finding algorithm under uncertainty. The global optimum of the proposed method can be guaranteed. Numerical examples are conducted to demonstrate the correctness and efficiency of the proposed algorithm.
... Liu and Ramakrishnan [195] proposed the A*Prune algorithm for solving the MCSP problem. As its name suggests, the A*Prune algorithm is in principle similar to the A* algorithm (see Section II-D). ...
A variety of communication networks, such as industrial communication systems, have to provide strict delay guarantees to the carried flows. Fast and close to optimal quality of service (QoS) routing algorithms, e.g., delay-constrained least-cost (DCLC) routing algorithms, are required for routing flows in such networks with strict delay requirements. The emerging software-defined networking (SDN) paradigm centralizes the network control in SDN controllers that can centrally execute QoS routing algorithms. A wide range of QoS routing algorithms have been proposed in the literature and examined in individual studies. However, a comprehensive evaluation framework and quantitative comparison of QoS routing algorithms that can serve as a basis for selecting and further advancing QoS routing in SDN networks is missing in the literature. This makes it difficult to select the most appropriate QoS routing algorithm for a particular use case, e.g., for SDN controlled industrial communications. We close this gap in the literature by conducting a comprehensive up-to-date survey of centralized QoS routing algorithms. We introduce a novel four-dimensional (4D) evaluation framework for QoS routing algorithms, whereby the four dimensions correspond to the type of topology, two forms of scalability of a topology, and the tightness of the delay constraint. We implemented 26 selected DCLC algorithms and compared their runtime and cost inefficiency within the 4D evaluation framework. While the main conclusion of this evaluation is that the best algorithm depends on the specific sub-space of the 4D space that is targeted, we identify two algorithms, namely Lagrange relaxation based aggregated cost (LARAC) and search space reduction delay-cost-constrained routing (SSR+DCCR), that perform very well in most of the 4D evaluation space.
... We perform path computation on a five node topology mesh and compare Pathfinder's performance with the Freeflow [20] and Prune-Dijk [21] techniques using following cases. ...
Path computation in a network is dependent on the network’s processes and resource usage pattern. While distributed traffic control methods improve the scalability of a system, their topology and link state conditions may influence the sub-optimal path computation. Herein, we present Pathfinder, an application-aware distributed path computation model. The proposed model framework can improve path computation functions through software-defined network controls. In the paper, we first analyse the key issues in distributed path computation functions and then present Pathfinder’s system architecture, followed by its design principles and orchestration environment. Furthermore, we evaluate our system’s performance by comparing it with FreeFlow and Prune-Dijk techniques. Our results demonstrate that Pathfinder outperforms these two techniques and delivers significant improvement in the system’s resource utilisation behaviour.
This paper considers a novel quality-of-service (QoS) routing problem from a source to a destination, named the Cheapest Deadline Path Problem (CDPP), which arises from the real-world scenario. Let D=(V,A,c,d,s,t) be a double-weighted strongly connected digraph, where each arc a∈A is associated with a cost, c(a)∈Z+, and a delay, d(a)∈Z+, and s and t are the indices of the designated source and destination, respectively, and let B={B1,B2,…,Bn} be a set of positive constants, where Bi,1≤i≤n represents the upper bound on delay at vi∈V. The objective of CDPP is to find a vs-to-vt path of the minimum cost in D such that the vs-to-vk delay along the path is at most Bk, for each vertex, vk, appearing in the path. This paper presents a fully polynomial time approximation scheme (FPTAS) for CDPP in D=(V,A,c,d,s,t) using a graph traverse based dynamic programming algorithm as a sub-procedure.
With a growing demand for quasi-instantaneous communication services such as real-time video streaming, cloud gaming, and industry 4.0 applications, multi-constraint Traffic Engineering (TE) becomes increasingly important. While legacy TE management planes like MPLS have proven laborious to deploy, Segment Routing (SR) drastically eases the deployment of TE paths and is thus increasingly adopted by Internet Service Providers (ISP). There is now a clear need in computing and deploying Delay-Constrained Least-Cost paths (DCLC) with SR for real-time interactive services requiring both low delay and high bandwidth routes. However, most current DCLC solutions are not tailored for SR. They also often lack efficiency (particularly exact schemes) or guarantees (by relying on unbounded heuristics). Similarly to approximation schemes, we argue that the actual challenge is to design an algorithm providing both performances and strong guarantees. However, conversely to most of these schemes, we also consider operational constraints to provide a practical, high-performance implementation.
In this work, we extend and further evaluate our previous contribution, BEST2COP. BEST2COP leverages inherent limitations in the accuracy of delay measurements, accounts for the operational constraint added by SR, and provides guarantees and bounded computation time in all cases thanks to simple but efficient data structures and amortized procedures. We show that BEST2COP is faster than a state-of-the-art algorithm on both random and real networks of up to 1000 nodes. Relying on commodity hardware with a single thread, our algorithm retrieves all non-superfluous 3-dimensional routes in under 100ms in both cases. This execution time is further reduced using multiple threads, as the design of BEST2COP enables a significant speed-up thanks to a highly parallelizable core which also enables a balanced computing load between threads. Finally, we extend BEST2COP to deal with massive-scale ISP by leveraging the multi-area partitioning of these deployments. Thanks to our new topology generator specifically designed to model realistic patterns in such massive IP networks, we show that BEST2COP can solve DCLC-SR in approximately 1 s even for ISP having more than 100 000 routers.
Software-Defined Networking (SDN) has become a popular paradigm for modern day optimal performance of the network system as a result of the separation of the control component from other network elements. This enables the maintenance of the flow table structure on these devices while optimal forwarding of packets is enhanced via the central controller. Being a growing network architecture which is supposed to be able to meet up with increasing traffic demands in the future, it becomes apparently important that the mechanism that takes care of the QoS of the network demands is put in place. Such demands include the smooth running of big data transmission, D2D video exchange, Voice over IP and real-time multimedia applications which needed certain QoS requirements for optimal service delivery. However, fewer research articles have reported on the improvement on the QoS routing especially in connection with the SDN paradigm. We propose a multi-criteria routing algorithm that is based on deterministic Adaptive rendering technique called DART_MCP. Our DART_MCP QoS routing algorithm deployed Dijkstra’s algorithm to simplify the topology of the network before using multiple-criteria energy function to address the QoS requirements. We recorded a relatively stable bandwidth and user experience maximization under a low rate of network convergence in comparison with other approaches.
Optimal coding of video data depends upon the content of the frame. In a video frame, static and motion area exist. It is necessary to handle the static and motion parts separately for the optimal video coding. Doing that task firstly it is necessary to separate out the motion activity and the static portion of the frame separately with the help of some frame partitioning technique. In this paper quadtree (QT) based frame partitioning strategy is used. In the case of quad partitioning strategy on the basis of the edge threshold value motion part is represented by the small size of the block and a static portion of the frame represented by the large size of the block. In this paper on the basis of this block-based information level, an information-based variable quantization method (IV-QM) is developed. In this method, the value of the quantization parameter is fixed on the basis of information level in the block. In our suggested method, the rate-distortion algorithm was determined and tested for a variety of video sequences both fast and slow motion. Therefore the output is the testing of these various sequences for the newly proposed technique was done because of the variable R–D behavior for a variety of test sequence. The purposed technique is represented in a way that during the improvement of the rate and distortion, the estimate does not violate the multi-constraints parameters. Results are validated with the two video sequences, Mother-daughter and Foreman having different motion activity and varying frame rate 10 and 5 fps. In case of slow motion Mother-daughter video frame at frame rate 5 fps total bit budget reduced 5615–3185 bits and complexity reduced 102.57–99.23 s with acceptable degradation in PSNR 30.14 dB to 29.25 and at frame rate 10 fps bit budget reduced 4071–1949 bits and complexity reduced 56.58–55.65 s with acceptable degradation in PSNR 30.48 dB to 29.58 using proposed algorithm. Same algorithm is verified at fast motion foreman video sequence at 5 fps and found that total bit budget reduced 10,778–9152 bits and complexity reduced 76.10–75.15 s with acceptable degradation in PSNR 30.15 dB to 29.19 and at frame rate 10 fps bit budget reduced 10,666 bits to 8741 bits and complexity reduced 67.34–54.65 s with acceptable degradation in PSNR 30.17 dB to 29.02 using proposed algorithm. When the performance parameters are compared, it is concluded that bits requirement and complexity is reduced while moving from the fixed quantization parameters to variable quantization parameter and some acceptable degradation in PSNR is comes into the picture.
Heterogeneous information networks (HINs), which are typed graphs with labeled nodes and edges, have attracted tremendous interest from academia and industry. Given two HIN nodes
${s}$
and
${t}$
, and a natural number
${k}$
, we study the discovery of the
${k}$
most important meta paths in real time, which can be used to support friend search, product recommendation, anomaly detection, and graph clustering. In this work, we argue that the shortest path between
${s}$
and
${t}$
may not necessarily be the most important path. As such, we combine several ranking functions, which are based on frequency and rarity, to redefine the unified importance function of the meta paths between
${s}$
and
${t}$
. Although this importance function can capture more information, it is very time-consuming to find top-
${k}$
meta paths using this importance function. Therefore, we integrate this importance function into a multi-step framework, which can efficiently filter some impossible meta paths between
${s}$
and
${t}$
. In addition, we combine bidirectional searching algorithm with this framework to further boost the efficiency performance. The experiment on different datasets shows that our proposed method outperforms state-of-the-art algorithms in terms of effectiveness with reasonable response time.
Telemedicine is a new area based on the information and communication technology for collecting, storing, organizing, retrieving and exchanging medical information. One of the most important applications of telemedicine is indeed telesurgery in which an efficient telecommunication infrastructure between the surgery room and remote surgeons need to be established. One of the most important issues to be tackled in telesurgery is to find favorable links for routing as well as providing high Quality of Service (QoS). In this paper, an efficient model based on the hybridization of Type‐2 Fuzzy System (T2FS) and Cuckoo Optimization Algorithm (COA) over the Software Defined Networks (SDN) is proposed in order to achieve optimal and reliable routes for telesurgery application. Using T2FS, the fitness of the links is determined; then, a COA is conducted over the Constraint Shortest Path (CSP) problem to find the best routes. Delay is considered as a CSP problem which is satisfied by trying to find the paths with minimum cost. Due to the NP‐completeness of the CSP problem, an Enhanced COA (so‐called E‐COA) is proposed and utilized as a metaheuristic solver. To the best of our knowledge, this paper is the first SDN‐based communication model that applies both T2FS and E‐COA for assigning proper costs to the network's links, and solves the consequence CSP problem according to the QoS requirement for telesurgery. The model also recognizes and preserves the second‐best routes in order to keep the reliability for such a critical application. In addition to the simulations, the performance evaluation is also conducted on a real experimental scenario. Many comparisons are carried out between the proposed model and other conventional methods, and the evaluation study shows the superiority of the proposed model on all the three QoS‐related metrics, i.e. average end‐to‐end delay, packet loss ratio and PSNR.
In applications such as video surveillance systems, cameras transmit video data streams through network in which quality of received video should be assured. Traditional IP based networks cannot guarantee the required Quality of Service (QoS) for such applications. Nowadays, Software Defined Network (SDN) is a popular technology, which assists network management using computer programs. In this paper, a new SDN-based video surveillance system infrastructure is proposed to apply desire traffic engineering for practical video surveillance applications. To keep the quality of received videos adaptively, usually Constraint Shortest Path (CSP) problem is used which is a NP-complete problem. Hence, heuristic algorithms are suitable candidate for solving such problem. This paper models streaming video data on a surveillance system as a CSP problem, and proposes an artificial bee colony (ABC) algorithm to find optimal solution to manage the network adaptively and guarantee the required QoS. The simulation results show the effectiveness of the proposed method in terms of QoS metrics.
Traditional Internet routing is simple, scalable and
robust, but cannot provide perfect QoS support due to the
current completely distributed hop-by-hop routing architecture.
Software defined networking (SDN) opens up the door to traffic
engineering innovation and makes possible QoS routing with a
broader picture of overall network resources. We further argue
that SDN can provide more opportunity for the network users to
make their own routing selections with network programmability.
In this paper, we propose OpenMCR, a general framework for
network users to make their own choice of routing given various
requirements. OpenMCR provides routing subject to several
additive QoS constraints, which is NP-hard when the number
of constraints is two or more. By composing various necessary
conditions with different path extension schemes, our platform
can customize routing solutions for each network user based
on their own requirements. Through experiments in an SDN
emulated environment, we evaluate multiple aspects of OpenMCR,
demonstrate its effectiveness compared with several baselines and
validate our theoretical analysis.
Self-optimizing robotized assembly systems are able to compensate the restricted operation purpose of traditional robotized automation, in order to adapt dynamically to changed production conditions. As the human operator is directly involved in the assembly process, the interaction between the human and the robot has to be designed carefully to avoid exposing the human to excessive physical and cognitive strain. For controlling a robotized assembly cell, a Cognitive Control Unit (CCU) was developed that uses the cognitive software Soar and human-like assembly strategies to achieve a transparent and understandable assembly process. To minimize the cognitive and ergonomic risks during assembly, the CCU was extended by a graph-based assembly sequence planner (GASP). The GASP is able to find the optimal assembly sequence by using a complete assembly graph of the final product as well as generic production rules for assessing the ergonomic conditions of the individual assembly steps. The presented simulation study validates the functionality of the GASP with respect to the number of workflow switches between the human and the robot, the number of switches between the robotic tools, as well as the number of assembly group switches required to collaboratively assemble a model of a Stromberg carburetor. The results show a significant reduction of all three measures. The number of parts and the type of assessment of the assembly steps have a significant impact here.
Also named as the path-finding algorithm, the routing algorithm aims at finding a good way between the source point and destination point under some constraint conditions (the path “cost” is the lowest). Specifying part of necessary nodes by the algorithm, the node constraint routing algorithm finds the “good” path and must pass the necessary nodes without the loop; otherwise, the path is invalid. The node constraint shortest path problem is regarded one HP-Hard problem, and the current research generally adopts the violent algorithm or the screening function approach (screen out some paths passing the most of the currently necessary nodes); however, these methods have the loop or own much high time complexity or space complexity, which easily causes the intermittent interruption of the path loop or the network. For the end-to-end node constraint path-finding problem of the common directed network graph, this thesis designs one heuristic search algorithm based on the reinforcement learning the breadth-first traversal; the algorithm adopts thought of combining the breadth-first search and the greedy algorithm to expand the path, adopts the reinforcement learning to predict and screen the importance degree of the path as well and finally gets the path passing all the necessary nodes. The simulation experiments result demonstrates that the algorithm proposed by the thesis can be applicable to the network graph with the larger scale, has good performance in the path weight and the computing time and is regarded as one practically applicable algorithm.
Vehicular ad hoc networks (VANETs) are intended to get better driver safety, avoid collisions, and offer traffic optimization. Recent years have behold an increasing interest in the security schemes for VANETs as well as improve multi-constrained optimal path selection for finding feasible routes. However, there are still several issues to be convey prior to such authentication mechanisms can be voluntarily and extensively used in real-life deployments. In this paper, we examine several authentication schemes and multi-constrained optimal path selection based on certain criteria like Qos constraints.
With steadily increasing customer requirements on quality of both products and processes, companies are faced with increasing organisational and technical challenges. The market is characterised by individualised customer wishes which result in individual adaptations of the products. In order to manage this rapidly growing variety of products, the production system has to become much more flexible with respect to the product structure to be manufactured and the corresponding production and assembly processes. Especially in the field of assembly systems the increasing variety of products adds new complexities to the planning process and increases the costs, because (re-)planning efforts tend to grow exponentially to the number of variants.
This research area focuses on the management systems and principles of a production system. It aims at controlling the complex interplay of heterogeneous processes in a highly dynamic environment, with special focus on individualized products in high-wage countries. The project addresses the comprehensive application of self-optimizing principles on all levels of the value chain. This implies the integration of self-optimizing control loops on cell level, with those addressing the production planning and control as well as supply chain and quality management aspects. A specific focus is on the consideration of human decisions during the production process. To establish socio-technical control loops, it is necessary to understand how human decisions are made in diffuse working processes as well as how cognitive and affective abilities form the human factor within production processes.
New emerging distributed multimedia applications provide
guaranteed end-to-end quality of service (QoS) and have stringent
constraints on delay, delay-jitter, cost, etc. The task of QoS routing
is to find a route in the network which has sufficient resources to
satisfy the constraints. The delay-cost-constrained routing problem is
NP-complete. We propose a heuristic algorithm for this problem. The idea
is to first reduce the NP-complete problem to a simpler one which can be
solved in polynomial time, and then solve the new problem by either an
extended Dijkstra's algorithm or an extended Bellman-Ford algorithm. We
prove the correctness of our algorithm by showing that a solution for
the simpler problem must also be a solution for the original problem.
The performance of the algorithm is studied by both theoretical analysis
and simulation
An algorithm and example using the algorithm are presented. Some search theorems are stated and proved. Some experimental findings are discussed.
Our paper on the use of heuristic information in graph searching defined a path-finding algorithm, A*, and proved that it had two important properties. In the notation of the paper, we proved that if the heuristic function ñ (n) is a lower bound on the true minimal cost from node n to a goal node, then A* is admissible; i.e., it would find a minimal cost path if any path to a goal node existed. Further, we proved that if the heuristic function also satisfied something called the consistency assumption, then A* was optimal; i.e., it expanded no more nodes than any other admissible algorithm A no more informed than A*. These results were summarized in a book by one of us.
We study methods for approximating the set of Pareto optimal paths in multiple-objective, shortest-path problems. Known generalizations of standard shortest-path methods will compute this set, but can suffer from rapidly increasing computational and storage demands as problem size increases. In an effort to avoid such difficulties, we develop approximation methods that can estimate the Pareto optima to any required degree of accuracy. The approximation methods are 'fully polynomial'; that is, they operate in time and space bounded by a polynomial in problem size and accuracy of approximation - the greater the accuracy, the more time required to reach a solution. We show how approximation methods may be applied to yield fully polynomial approximation schemes for a variety of NP-complete, single-objective problems.
This note contains two fully polynomial approximation schemes for the shortest path problem with an additional constraint. The main difficulty in constructing such algorithms arises since no trivial lower and upper bounds on the solution value, whose ratio is polynomially bounded, are known. In spite of this difficulty, one of the algorithms presented here is strongly polynomial. Applications to other problems are also discussed.
Let G = (V, E) be a graph with weight function w:E rightarrow Z+ and length function l:E /rightarrow Z+. The problem of determining for v1, V2 /in V whether there is a path from v1 to v2 with weight at most W and length at most L is NP-complete. This paper gives two approaches to meeting or approximating the length and weight constraints. The first approach is to use a pseudopolynomial-time algorithm which determines whether a path meets the constraints. Its running time is O (n5b log nb) where n = |V| and b is the largest length or weight. If tables with O (n3b) entries are kept then all instances of multiple constraints may be decided. Table size may be substantially decreased if one is willing to tolerate incorrect answers to rare instances. The algorithm is suitable for distributed execution. In the second approach, an objective function is defined which evaluates a path's distance from meeting the constraints. Polynomial-time algorithms attempt to find good paths in terms of the objective function. One algorithm is at most 1.62 times worst than optimal. A notion of “average worst-case behavior” is defined. The algorithm's “average” behavior is 1.51 times worse than optimal.
In this short paper we give a very simple fully polynomial approximation scheme for the restricted shortest path problem. The complexity of this ε-approximation scheme is , which improves Hassin's original result (Math. Oper. Res. 17 (1) (1992) 36) by a factor of n. Furthermore, this complexity bound is valid for any graph, regardless of the cost values. This generalizes Hassin's results which apply only to acyclic graphs.Our algorithm is based on Hassin's original result with two improvements. First we modify Hassin's result and achieve time complexity of , where UB and LB are upper and lower bounds for the problem. This modified version can be applied to general graphs with any cost values. Then we combine it with our second contribution, which shows how to find an upper and a lower bound such that UB/LB⩽n, to obtain the claimed result.
The long-anticipated revision of this best-selling book offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For those interested in artificial intelligence.
One of the basic problems in quality of service (QoS) routing is to find a path subject to multiple constraints on routing metrics. We first show that for additive and multiplicative metrics, the path finding problem is NP-complete, and then apply the results to QoS routing.
Two algorithms for solving the (symmetric distance) traveling salesman problem have been programmed for a high-speed digital computer. The first produces guaranteed optimal solution for problems involving no more than 13 cities; the time required (IBM 7094 II) varies from 60 milliseconds for a 9-city problem to 1.75 seconds for a 13-city problem. The second algorithm produces precisely characterized, locally optimal solutions for large problems (up to 145 cities) in an extremely short time and is based on a general heuristic approach believed to be of general applicability to various optimization problems. The average time required to obtain a locally optimal solution is under 30n3 microseconds where n is the number of cities involved. Repeated runs on a problem from random initial tours result in a high probability of finding the optimal solution among the locally optimal solutions obtained. For large problems where many locally optimal solutions have to be obtained in order to be reasonably assured of having the optimal solution, an efficient reduction scheme is incorporated in the program to reduce the total computation time by a substantial amount.
We present techniques, some of which are novel, for traffic
engineering in QoS-supported data networks, and also illustrate the
application of these techniques in a case study. In the interest of
scalability all these techniques use multicommodity flow (MCF) solution
techniques as primitives. The techniques address the design of topology
and size of explicit routes in MPLS-supported IP networks and VPNs. The
techniques are for network-wide optimization subject to constraints on
routing imposed by end-to-end QoS and other considerations. The notion
of admissible route sets specific to service class and
source-destination pair is used to differentiate QoS constraints on
real-time services, such as Internet telephony and video, and relatively
delay insensitive services, such as premium data. Contrasting
optimization techniques are given for services, such as best effort, for
which no restriction on routes are imposed. Another important traffic
engineering requirement addressed is priorities, for which an efficient
and accurate design technique is given
We give algorithms for finding the k shortest paths (not required to be simple) connecting a pair of vertices in a digraph. Our algorithms output an implicit representation of these paths in a digraph with n vertices and m edges, in time O(m+n log n+k). We can also find the k shortest paths from a given source s to each vertex in the graph, in total time O(m+n log n+kn). We describe applications to dynamic programming problems including the knapsack problem, sequence alignment, and maximum inscribed polygons
Although the problem of determining the minimum cost path through a graph arises naturally in a number of interesting applications, there has been no underlying theory to guide the development of efficient search procedures. Moreover, there is no adequate conceptual framework within which the various ad hoc search strategies proposed to date can be compared. This paper describes how heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching and demonstrates an optimality property of a class of search strategies.
We consider the problem of routing connections with quality of
service (QoS) requirements across networks when the information
available for making routing decisions is inaccurate. Such uncertainty
about the actual state of a network component arises naturally in a
number of different environments. The goal of the route selection
process is then to identify a path that is most likely to satisfy the
QoS requirements. For end-to-end delay guarantees, this problem is
intractable. However, we show that by decomposing the end-to-end
constraint into local delay constraints, efficient and tractable
solutions can be established. Moreover, we argue that such decomposition
better reflects the interoperability between the routing and reservation
phases. We first consider the simpler problem of decomposing the
end-to-end constraint into local constraints for a given path. We show
that, for general distributions, this problem is also intractable.
Nonetheless, by defining a certain class of probability distributions,
which includes typical distributions, and restricting ourselves to that
class, we are able to establish efficient and exact solutions. We then
consider the general problem of combined path optimization and delay
decomposition and present efficient solutions. Our findings are
applicable also to a broader problem of finding a path that meets QoS
requirements at minimal cost, where the cost of each link is some
general increasing function of the QoS requirements from the link
With increasingly diverse QOS requirements, it is impractical to
continue to rely on conventional routing paradigms that emphasize the
search for an optimal path based on a predetermined metric, or a
particular function of multiple metrics. Modern routing strategies must
not only be adaptive to network changes but also offer considerable
economy of scope. We consider the problem of routing in networks subject
to QOS constraints. After providing an overview of prior routing work,
we define various QOS constraints. We present a call architecture that
may be used for QOS matching and a connection management mechanism for
network resource allocation. We discuss fallback routing, and review
some existing routing frameworks. We also present a new rule-based,
call-by-call source routing strategy for integrated communication
networks
We give algorithms for finding the k shortest paths (not required to be simple) connecting a pair of vertices in a digraph. Our algorithms output an implicit representation of these paths in a digraph with n vertices and m edges, in time O(m + n log n + k). We can also find the k shortest paths from a given source s to each vertex in the graph, in total time O(m + n log n + kn). We describe applications to dynamic programming problems including the knapsack problem, sequence alignment, maximum inscribed polygons, and genealogical relationship discovery.
The search for generality. Information Processing
- A Newell
- G Ernst
A. Newell and G. Ernst, The search for generality. Information Processing 1965: Proceedings of IFIP Congress, volume 1, pages 17-24. Spartan.
1965.
An Efficient Algorithm for Constraint-based Routing in Data Networks
- A Goel
- D Kataria
- D Logothetis
- K G Ramakrishnan
A. Goel, D. Kataria, D. Logothetis and K. G. Ramakrishnan. An Efficient
Algorithm for Constraint-based Routing in Data Networks. Technical Report, BL0112120-990616-11TM, Bell Laboratories/Lucent Technologies,
1999.
Algorithms for WEDM Mesh Network Design: Routing and Wavelength Assignment for Dedicated Protection, Ring Auto-Recovery and Optical Cross-Connect Restoration in Core Optical Networks
- E Bouillet
- G Liu
- I Saniee
E. Bouillet, G. Liu and I. Saniee. Algorithms for WEDM Mesh Network
Design: Routing and Wavelength Assignment for Dedicated Protection,
Ring Auto-Recovery and Optical Cross-Connect Restoration in Core Optical Networks. Technical Report, 10009626-000126-01TM, Bell Laboratories/Lucent Technologies, 2000.
- A V Aho
- J D Ullman
A. V. Aho and J. D. Ullman. Foundations of Computer Science. C Edition,
pp. 280-285, W. H. Freeman and Company, New York, 1995.