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The provision for addressing multiple destinations in group multimedia application delivery over Wireless Mesh Networks (WMN) can be achieved efficiently via multicasting while considering the mobility of Mesh Clients (MC). One of the prominent components of WMN is the Internet Gateway (IGW) which provides wired bridge connection between the backbo...
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... growing demand for Wireless Mesh Networks (WMN) is majorly motivated by its provision of low cost broadband access. This is achievable with the multihop and the Internet Gateway (IGW) concepts. Fig. 1 shows its three types of nodes: Mesh Clients (MC), Mesh Routers (MR) and Internet Gateways (IGW). The case of no planning may be considered for such networks as ease of deployment is obtained. However, network planning translates to cost and performance savings since the number and placement of mesh nodes, routing and node interface ...
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Citations
... All the secondary users can access the spectrum without any priority [9]. The physical location of radio frequency transmission sources has been a hot topic for many years in wireless applications [10], [11]. These specific features of CR predispose the network to new kinds of threats, one of which is called a primary user emulation attack [12]. ...
Cognitive Radio Networks (CRNs) have been conceived to improve the efficiency of accessing the spectrum. However, these networks are prone to various kinds of attacks and failures that can compromise the security and performance of their users. One of the notable malicious attacks in cognitive radio networks is the Primary User Emulation (PUE) attack, which results in underutilization and unavailability of the spectrum and low operational efficiency of the network. This study developed an improved technique for detecting PUE attacks in cognitive radio networks and further addressed the characteristics of sparsely populated cognitive radio networks and the mobility of the primary users. A hybrid signal processing-based model was developed using the free space path loss and additive Gaussian noise models. The free space path loss model was used to detect the position of the transmitter, while the additive Gaussian noise model was used to analyze the signal transmitted, i.e., energy detection in the spectrum at the detected location. The proposed model was benchmarked with an existing model using the number of secondary users and the velocity of the transmitter as performance parameters. The simulation results show that the proposed model has improved accuracy in detecting primary user emulation attacks. It was concluded that the proposed hybrid model with respect to the number of secondary users and the velocity of the transmitter can be used for primary user emulation attack detection in cognitive radio networks.
... In the work of Benyamina et al. [11], the authors surveyed different aspects of WMNs design and examined various methods that have been proposed categorized into fixed topology and unfixed topology-based approaches. Sanni et al. [12] introduced the modeling and formulation of the MG placement problem and surveyed some heuristics and meta-heuristics applied to optimize the MG placement in WMNs. Ahmed and Hachim [13] reviewed the WMNs gateway placement optimization based on meta-heuristic approaches. ...
... Sanni et al. [12] 2012 MG -Modeling and formulation of MG placement problem. ...
Wireless mesh networks (WMNs) have grown substantially and instigated numerous deployments during the previous decade thanks to their simple implementation, easy network maintenance, and reliable service coverage. Despite these proprieties, the nodes placement of such networks presents many challenges for network operators. In this paper, we present a survey of optimization approaches implemented to address the WMNs nodes placement problem. These approaches are classified into four main categories: exact approaches, heuristic approaches, meta-heuristic approaches, and hybrid approaches. For each category, a critical analysis is drawn according to targeted objectives, considered constraints, type of positioned nodes (Mesh Router and Mesh Gateway), location (discrete or continuous), and environment (static or dynamic). In the end, several new key search areas for WMNs nodes placement are suggested.
... To improve accuracy of position estimation, it requires dyanamically gateway (and known position node) reallocation. Recent research of gateway allocation focuses on improving load balancing and efficiency of data transmission only [8,9,14]. Our previous study [15] proposed position estimation method using the map of received signal strength, and we extend the previous study and allow the reconfiguration of the gateway allocation to assure the accuracy of node position estimation. ...
The Internet of Things (IoT) technology has been rapidly deployed for real-time information collection and physical system management. These IoT-based smart services require robust mobile ad-hoc network to assure communications between heterogeneous nodes/sensors and the service management systems. Gateway allocation therefore is essential for an IoT network to collect and process captured data with limited gateway capability (bandwidth) and energy resources (battery). In this study, we propose a recursive approach using the combination of self-localization and model checking methods to (1) enable mobile device position estimation and (2) repeatedly validate convergence and reconfiguration of gateway allocation according to constraints obtained from requirements of the target network system. Concrete examples are provided in experimental studies to present the essential foundation of the proposed approach. Future work of the extension and application of this recursive gateway allocation technique is also discussed.
... The IGW placement problem is usually considered NP hard, thus near optimal heuristics are generally employed [4,[18][19][20][21][22][23][24][25][26][27]. The problem of formulations for promoting IGW placement is usually placed in one of the following categories: ...
Due to the high demand of Internet access by users, and the tremendous success of wireless technologies, Wireless Mesh Networks (WMNs) have become a promising solution. IGW Placement and Selection (GPS) are significantly investigated problems to achieve QoS requirements, network performance, and reduce deployment cost in WMNs. Best effort is made to classify different works in the literature based on network characteristics. At first, one of the most principal capabilities of WMNs, which is taking advantage of using multi-radio routers in a multi-channel network, is studied. In this article, GPS protocols considering a definition of three types of WMN are investigated based on channel-radio association including Single Radio Single Channel (SRSC), Single Radio Multi- Channel (SRMC), and Multi-Radio Multi-Channel (MRMC) WMNs. Furthermore, a classification regarding static and dynamic channel allocation policies is derived. In addition, the reported works from the viewpoint of network solutions are classified. The first perspective is: centralized, distributed or hybrid architectures. Following this classification, the studies are categorized regarding optimization techniques, which are operation research-based solutions, heuristic algorithms, and meta-heuristic-based algorithms.
... Considering the router placement problem as facility location problem with the assumption that the mesh routers are the facilities, which gives services such as Internet to the client nodes, Xhafa et al. (2015) have experimentally implemented and evaluated the Tabu search algorithm for optimizing various instances of the giant component to maximize the connectivity of the network. Sanni et al. (2012) has sketched out an Internet gateway (IGW) optimization problem for optimizing the placement of gateways. The authors have not experimentally evaluated the problem with any of the conventional methods or evolutionary computations. ...
Wireless Mesh Networks (WMNs) have received a greater attention in wireless communication field. The conventional node deployment allows random distribution of mesh routers, which increases the number of mesh routers, and hence the design cost also increases. In order to have an optimal placement of mesh nodes, the node placement problem is considered as an optimization problem. Here, the problem is formulated as a facility location problem. A Fuzzy Differential Evolution (FDE) approach is proposed along with a traffic weight (TW) assignment method for optimal placement of mesh nodes and allotting gateways. Design Cost (DC) and Transmission Cost (TC) are the two minimization objectives, which are solved using the proposed method. The simulation results show that, on average, the DC using FDE approach is minimized 10% compared to TW algorithm, 2.8% less than SA, and 1.2% less than DE methods. A network performance metric called failure rate (FR) and the TC objective are considerably reduced using the FDE based placement. The performance of the network is evaluated with multiple CBR flows, and the simulation results show 10% to 5% increase in the throughput and packet delivery rate compared to the existing approaches.
... The ITAP placement problem is formulated as a linear program and solved via several greedy-based approximation algorithms. In [4] an ITAP deployment problem was described with multicasting strategies, based on the general assignment and traveling salesman problems. Maintaining fairness in WMNs is important since nodes far from the ITAPs, due to forwarding, significantly reduce the overall throughput. ...
... The ITAP placement problem is formulated as a linear program and solved via several greedy-based approximation algorithms. In [4] an ITAP deployment problem was described with multicasting strategies, based on the general assignment and traveling salesman problems. Maintaining fairness in WMNs is important since nodes far from the ITAPs, due to forwarding, significantly reduce the overall throughput. ...
A multi-objective approach to optimize wireless mesh network design with three conflicting objectives is presented: it minimizes the number of Internet Transit Access Points (ITAPs), maximizing the fairness of bandwidth allocation and maximizing coverage to mesh clients. We discuss how such an approach can allow more effective use of an existing ITAP deployment, enabling a greater number of consumers to obtain Internet services. Previous contributions have formulated and solved this problem by using single-objective integer programming formulations. We instead apply the weighted-sum method and propose a heuristic algorithm with an efficient combination of move operators. This algorithm produces a set of effective optimization solutions under the ideal link network model.
... In addition to different approaches for GP, a variety of problem settings for GP were considered, e.g., GP with cross-layer throughput optimization [22], GP with optimal mobile multicast design [23], and GP with QoS requirements. Among them, most previous works focused on finding the GP with QoS requirements. ...
Conventionally, router node placement is concerned with placing only routers to serve clients; and gateway placement is concerned with placing only gateways to achieve some requirements for routers. More generally, this work considers the placement with routers and gateways simultaneously, while clients can move based on their own willingness. That is, this work investigates the adaptive placement problem of a dynamic wireless mesh network (dynWMN) consisting of mesh clients, mesh routers, and Internet gateways. Given fixed positions of Internet gateways, this problem is to adjust positions of mesh routers dynamically to make each mesh client connected with some gateway via multi-hop communication at different times, when each mesh client may switch on or off network access, so that both network connectivity and client coverage are maximized, subject to the Quality of Service (QoS) constraints of delay hops, relay load, and gateway capacity. To avoid almost-overlapping routers and few-clients-covered routers in router node placement, this work further proposes a novel particle swarm optimization approach with three local search operators. In simulation of dynWMNs, dynamics of mesh clients can be characterized by a Markov chain, and hence, their stable states can be derived theoretically and are used as criteria of evaluating performance, by which the proposed approach shows promising performance and adaptability to topology changes at different times.
... Mistura L. Sanni et.al. [8]have described the basis of internet gateway deployment optimization problems with multicasting strategies. The gateway placement problem is formulated based on the general assignment problem and travelling sales man problem. ...
Mesh node placement problem is one of the major design issues in Wireless Mesh Network (WMN). Mesh networking is one of the cost effective solution for broadband internet connectivity. Gateway is one of the active devices in the backbone network to supply internet service to the users. Multiple gateways will be needed for high density networks. The budget and the time to setup these networks are important parameters to be considered. Given the number of gateways and routers with the number of clients in the service area, an optimization problem is formulated such that the installation cost is minimized satisfying the QOS constraints. In this paper a traffic weight algorithm is used for the placement of gateways based on the traffic demand. A cost minimization model is proposed and evaluated using three global optimization search algorithms such as Simulated Annealing (SA), Differential Evolution (DE) and Fuzzy DE (FDE). The simulation result shows that FDE method achieves best minimum compared with other two algorithms.
... Many node placement approaches are formulated by the researchers as it is one of the active research areas [5][6][7][8].A ILP for cost effective node placement problem was proposed and formulated by Wenjia Wu et.al [5].The authors have evaluated using CeNp LSA algorithm with gateway deployment constraint. To determine the positions of mesh nodes the algorithm is categorized as (a) MSC-based coverage algorithm (b) weighted clustering algorithm (c) GW-rooted tree pruning algorithm. ...
... A WMN-GA system is developed and the network performance is evaluated by Admir Barollia et.al. [7].The performance of the proposed system for different client distributions such as Normal, Uniform, Exponential and Weibull is observed. ...
Wireless Mesh network is one of the cost effective solution for broadband internet connectivity. The gateways play the major role by supplying internet service to the users. Hence multiple gateways will be needed for large campus networks. The budget cost and the time to setup these networks are important parameters to be considered. Given the number of gateways and routers with the no of clients in the service area, an optimization problem is formulated such that the installation cost is minimized satisfying the QOS constraints. The routers are replaced with gateways according to the high traffic demand. In this paper a cost minimization problem is formulated to solve the gateway placement issue in WMN. Using a local search method Simulated Annealing (SA) and a population based method Differential Evolution (DE) the network model is evaluated in NS2 simulator to achieve cost optimization. The later outperforms the SA algorithm around 20% to 30%. © 2015, International Journal of Pharmacy and Technology. All rights reserved.
