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A Clustering Routing Protocol for Energy Balance of Wireless Sensor Network based on Simulated Annealing and Genetic Algorithm
Abstract
The LEACH is a popular protocol used in wireless sensor network analysis and simulation. This paper analyses the advantages and disadvantages of LEACH protocol and then puts forward a clustering routing protocol for energy balance of wireless sensor network based on simulated annealing and genetic algorithm. When the sensor nodes are deployed randomly in the area, Firstly, we cluster the sensor nodes by simulated annealing and genetic algorithm and then calculate the cluster center of each cluster. If the energy of the node in the cluster is higher than the average energy of the cluster, it will become the candidate cluster head; at last the candidate cluster head becomes the cluster head according to the distance from the cluster center of the cluster. Simulations show that the new program could improve Energy Hotspot caused by the uneven distribution of cluster head in LEACH protocol, thus it can balance the wireless sensor network load balance and extend the lifecycle of wireless sensor network.
... Currently, there is still no widely recognized optimization algorithm that can efficiently and stably achieve the global optimal solution, while local optimization is usually infeasible. To address this issue, researchers have proposed theoretical analysis [4][5][6][7][8][9], as well as various optimization algorithms, including the genetic algorithm [10][11][12][13][14][15], simulated annealing algorithm [16,17], and particle swarm optimization algorithm [18,19], to optimize the station arrangement. The studies discussed in [4,8,9] investigated the optimization of distance-measuring devices, using the Cramer-Rao bound and the geometric dilution of precision (GDOP) as objective functions. ...
... As a result, these methods have poor practical applicability. The studies discussed in [10,11,17] used the genetic algorithm to optimize node arrangement in WSNs (Wireless Sensor Networks) based on the distance range of the sensors, though paper [17] combined this approach with the simulated annealing algorithm. The papers in [12,14,15] established different mathematical models for optimal arrangement of radar netting, among which distance is one of the main factors. ...
... As a result, these methods have poor practical applicability. The studies discussed in [10,11,17] used the genetic algorithm to optimize node arrangement in WSNs (Wireless Sensor Networks) based on the distance range of the sensors, though paper [17] combined this approach with the simulated annealing algorithm. The papers in [12,14,15] established different mathematical models for optimal arrangement of radar netting, among which distance is one of the main factors. ...
Station arrangement optimization of photoelectric theodolites in shooting ranges presents a non-convex and non-linear problem, and the method required to seek the global optimal solution remains an open question. This paper proposes an efficient traversal algorithm that could solve this problem by utilizing discretization of regions with a finite length of mesh, in which both the terrain of the station arrangement region and the observation airspace region are discretized through triangulation. To enhance the computational efficiency of the traversal algorithm, two strategies are employed to speed up the calculation: reducing the dimension of the observation airspace and using the Euclidean distance matrix to compute the intersection angle. After the global optimal solution with discrete finite precision was obtained through the traversal algorithm, it was then used as the initial points for local mesh refinement and to implement gradient-based optimization in order to further improve the precision of the solution. The proposed approach is demonstrated to be practical through application to numerical examples used for the optimization of station arrangements that involve two to four stations.
... In PEGASIS protocol (Vhatkar and Atique, 2013;Lindsey and Raghavendram, 2002), each node fuses its own sensed data with those received from other nodes before transmitting. Thanks to the proportionality between the energy dissipation of the amplifier in the sensor node and the energy attenuation caused by the transmission distance in the range of less than 87.7 metres (Zhang et al., 2014), the topology optimisation of WSN by minimising the quadratic sum of distance becomes the key to conserving energy (in this case, the distance exponent is considered to be 2). ...
... There have been large number of distributed and centralised algorithms directing at clustering proposed in WSNs and they can obtain maximum energy efficiency (Zhou et al., 2016). Based on the PEGASIS, some conventional ad hoc networks replace its chain construction algorithm, such as the ant colony optimisation algorithm (Su et al., 2016), genetic algorithm (Zhang et al., 2014;Lin et al., 2015;Bai et al., 2013) and simulated annealing algorithm (Zhang et al., 2014;Bai et al., 2013). ...
... There have been large number of distributed and centralised algorithms directing at clustering proposed in WSNs and they can obtain maximum energy efficiency (Zhou et al., 2016). Based on the PEGASIS, some conventional ad hoc networks replace its chain construction algorithm, such as the ant colony optimisation algorithm (Su et al., 2016), genetic algorithm (Zhang et al., 2014;Lin et al., 2015;Bai et al., 2013) and simulated annealing algorithm (Zhang et al., 2014;Bai et al., 2013). ...
In order to solve the deficiencies with the PEGASIS in the inevitability of long link, the overhead of the ineligible cluster head (CH), and the overhead and time cost of chain rebuilding, an improved protocol, the BranChain, is proposed. The proposed algorithm can avoid long links, re-adjust network topology and adopt CH re-election mechanism. Whenever a long link is formed, the node originally connected is supposed to form a new independent branched chain with the greedy algorithm. When all nodes get connected in the chain, the system will connect all the independent branched chains together by searching for the optimal paths between each two of the branched chains. When the sensor nodes die, the two broken branched chains will be connected with the same algorithm as that of the optimal paths searching. Simulation results show that the BranChain, compared with the PEGASIS, can significantly prolong the network lifetime.
... In PEGASIS protocol (Vhatkar and Atique, 2013;Lindsey and Raghavendram, 2002), each node fuses its own sensed data with those received from other nodes before transmitting. Thanks to the proportionality between the energy dissipation of the amplifier in the sensor node and the energy attenuation caused by the transmission distance in the range of less than 87.7 metres (Zhang et al., 2014), the topology optimisation of WSN by minimising the quadratic sum of distance becomes the key to conserving energy (in this case, the distance exponent is considered to be 2). ...
... There have been large number of distributed and centralised algorithms directing at clustering proposed in WSNs and they can obtain maximum energy efficiency (Zhou et al., 2016). Based on the PEGASIS, some conventional ad hoc networks replace its chain construction algorithm, such as the ant colony optimisation algorithm (Su et al., 2016), genetic algorithm (Zhang et al., 2014;Lin et al., 2015;Bai et al., 2013) and simulated annealing algorithm (Zhang et al., 2014;Bai et al., 2013). ...
... There have been large number of distributed and centralised algorithms directing at clustering proposed in WSNs and they can obtain maximum energy efficiency (Zhou et al., 2016). Based on the PEGASIS, some conventional ad hoc networks replace its chain construction algorithm, such as the ant colony optimisation algorithm (Su et al., 2016), genetic algorithm (Zhang et al., 2014;Lin et al., 2015;Bai et al., 2013) and simulated annealing algorithm (Zhang et al., 2014;Bai et al., 2013). ...
... The protocol uses parameters such as maximum dump energy, minimum mobility, and the minimum distance from the base station, and selects new clusters by periodically running algorithms proposed so as to prolong the life of sensor network through balancing node energy consumption. Based on the analysis of low energy adaptive clustering hierarchy (LEACH) protocol characteristics, Zhang et al. 14 propose WSN based on simulated annealing (SA) and genetic algorithm (GA) to balance clustering routing protocol; meanwhile, they prolong lifetime of WSN by switching cluster head balance load. Han et al. 15 propose a general self-organizing energy balance routing protocol based on tree, which constructs a routing tree, reports the information about root node by broadcasting, and allows each node and its neighbors' information to select node relation, thus transmitting information. ...
... Local routing finds the optimal routing for nodes between adjacent clusters. Therefore, the local routing function can be described as formula (14), where n a is the starting point and n b is the end of adjacent cluster ...
The target tracking issue has always been the hotspot in wireless sensor network, and with the emergence of new application in multimedia and real-time transmission, new requirements are proposed for transmission performance of target tracking routing; therefore, a software-defined network–based hierarchical adaptive routing algorithm of wireless sensor network is proposed in this article. The algorithm takes into account both network energy and throughput, uses Hopfield neural network algorithm to calculate the optimal path among adjacent clusters as a local routing (LR), and builds the Multi-choice Knapsack Problem model based on local paths to realize end-to-end global routing, in order to realize the routing of tracking target information under multi-objective conditions. The test bed includes physical and simulation tests. Experimental results show that the proposed algorithm is superior to low energy adaptive clustering hierarchy (LEACH) and Sequential Assignment Routing under different test scenarios.
... A new routing protocol based on annealing and genetic algorithms called LEACH simulated annealing and genetic algorithm (LEACH-SAGA) was proposed in [91] to enhance energy distribution among nodes in the net-work. In LEACH-SAGA, clusters are formed by using genetic and annealing algorithms. ...
... Features of routing protocols in WSNs based on the LEACH protocol. Distance between node and BS Two factors are considered in selecting a cluster head which increase the number of alive nodes LEACH-SAGA[91] Optimization Residual energy and distance from centroid of a cluster Simulated annealing and genetic algorithms are used to find the optimal number of cluster heads Forming a chain of cluster heads in the network from the source cluster head to the BS C-LEACH[97] Network division Residual energy and shortest path Dividing the network into cells and forming a cluster from seven nearby cells Select an intermediate cluster head based on the distance to the BS and the energy of the current cluster head ...
A wireless sensor network (WSN) is a modern technology in radio communication. A WSN comprises a number of sensors that are randomly spread in a specific area for sensing and monitoring physical attributes that are difficult to monitor by humans, such as temperature, humidity, and pressure. Many problems, including data routing, power consumption, clustering, and selecting cluster heads (CHs), may occur due to the nature of WSNs. Various protocols have been conducted to resolve these issues. One of the important hierarchical protocols that are used to reduce power consumption in WSNs is low-energy adaptive clustering hierarchy (LEACH). This paper presents a comprehensive study of clustering protocols for WSNs that are relevant to LEACH. This paper is the first to emphasis on cluster formation and CHs selection methods and their strengths and weaknesses. A new taxonomy is presented to discuss LEACH variants on the basis of different classes, and the current survey is compared with other existing surveys. A complete comparison of the location, energy, complexity, reliability, multi–hop path, and load balancing characteristics of LEACH variants is conducted. Future research guidelines for CHs selection and cluster formation in WSNs are also discussed.
... In a simulation study [38], associated parameters of Eq. 3 have following assumed values: E elec = 50/nJ bit, ε f s = 10 pJ/bit/m 2 , ε mp = 0.0013 pJ/bit/m 4 , E da = 5 nJ/bit/signal and d 0 = 87 m. The present research, analyses energy model described in Eqs. 2 and 3. Since Eqs. 2, and 3 define energy consumption in both micro and standard operation of WSN. ...
... For the energy model 2 (Eq. 4) with distance d < 87 m, the minimum energy obtained in the present study is equal to 0.0002 J which is 0.04% of the total energy in a sensor node (0.5 J) [38]. The minimum energy achieved in the present analysis, for energy model 3 (Eq. ...
Wireless sensor networks (WSNs) are used for several commercial and military applications, by collecting, processing and distributing a wide range of data. Maximizing the battery life of WSNs is crucial in improving the performance of WSN. In the present study, different variations of genetic algorithm (GA) method have been implemented independently on energy models for data communication of WSNs with the objective to find out the optimal energy \(\hbox {(E)}\) consumption conditions. Each of the GA methods results in an optimal set of parameters for minimum energy consumption in WSN related to the type of selected energy model for data communication, while the best performance of the GA method [energy consumption \((\hbox {E}=3.49\times 10^{-4}\,\hbox {J})\)] is obtained in WSN for communication distance (d) \({\ge }87\,\hbox {m}\) in between the sensor cluster head and a base station.
... This enhances the reliability of the clustering process. Zhang et al. (14) analyzed the pros and cons of the LEACH protocol and proposed a clustering routing protocol aiming for energy balance in WSNs. The protocol, clusters randomly organized sensor nodes using a combination of Simulated Annealing (SA) and GA. ...
... The author compared the performance of LEACH-GA versus LEACH by placing the BS at two different locations. In both the cases the LEACH-GA outperformed the LEACH but it suffers from message overhead and energy consumption issues because of location information requirement of the BS before the start of a round [16,17]. ...
To capture sensed data from different locations, Wireless sensor network (WSN) requires large number of sensors in the monitoring area. A sensor helps in sensing and forwarding data to an application data store but due to inadequate energy, preserving the network lifetime and its operation remains a major challenge in WSN. To overcome this challenge different clustering techniques are proposed in literature. LEACH is a primitive clustering technique from which most of the latest clustering techniques stem in. Many recent studies have focused on the optimization of cluster based WSNs through fine tuning of LEACH parameters and other related parameters. Motivated by this, it has been reviewed that the latest optimized variants of LEACH. This survey will provide a roadmap for future researchers to scrutinize LEACH and its variants in terms of optimization technique used and parameters used for clustering.
... In case of a probability resulting from the algorithm does not elect a cluster-head, the selection of one clusterhead will be executed at random. Every member node sends a request message as a membership to the cluster head [25]. ...
Wireless sensor networks (WSNs) are characterized by huge sensors that are having a limited amount of energy and specifying their behavior. Sensor networks combine distributed sensing, processing, and communication capabilities to create a powerful system. There are issues with the length of sensors connected to the network since features inside the sensors frequently require energy, which is likely to limit WSN performance. In creating WSN application architectures, extending network longevity, scalability, and load balancing are important factors. Using clustering techniques, the challenge of prolonging overall network lifetime and increasing the first dead node duration in the network may be tackled. Clustering is a valuable approach for breaking a network into parts known as clusters and giving solutions for energy consumption concerns including data collection, aggregating, and routing to sink nodes by cluster heads (CHs). In this paper, we suggest optimum clustering in multi-path and multi-hop protocols as a feasible option for reducing energy consumption and extending the lifetime of wireless sensor networks. In compared to the low energy adaptive clustering hierarchy (LEACH) clustering method, simulation results show that the new technique, optimal real time clustering (ORTC), is promising in terms of extending network lifetime.
... Moreover, PEAR adapts to the nodes residual energy level and is not limited to single hop communication. Thus, larger areas can be covered, and the transmission power is lower due to shorter transmission distances [21,22]. These disadvantages were addressed by LEACH-based protocols such as [23][24][25]. ...
In industrial wireless sensors networks (IWSNs), the sensor lifetime predictability is critical for ensuring continuous system availability, cost efficiency and suitability for safety applications. When deployed in a real-world dynamic and centralised network, the sensor lifetime is highly dependent on the network topology, deployment configuration and application requirements. (In the absence of an energy-aware mechanism, there is no guarantee for the sensor lifetime). This research defines a conceptual model for enhancing the energy predictability and efficiency of IWSNs. A particularization of this model is the predictive energy-aware routing (PEAR) solution that assures network lifetime predictability through energy-aware routing, energy balancing and profiling. The PEAR solution considers the requirements and constraints of the industrial ISA100.11a communication standard and the VR950 IIoT Gateway hardware platform. The results demonstrate the PEAR ability to ensure predictable energy consumption for one or multiple network clusters. The PEAR solution is capable of intracluster energy balancing, reducing the overconsumption 10.4 times after 210 routing changes as well as intercluster energy balancing, increasing the cluster lifetime 2.3 times on average and up to 3.2 times, while reducing the average consumption by 23.6%. The PEAR solution validates the feasibility and effectiveness of the energy-aware conceptual indicating its suitability within IWSNs having real world applications and requirements.
... However, it runs into the problems of a large overhead and network complexity. In [11], LEACH simulated annealing was proposed in which the BS is at the center. The method searches for the energy of each node and the distance between sensor nodes according to the center, and the node with the highest remaining energy is nominated as the cluster head. ...
... Sensor nodes with energy greater than the average energy of the cluster become the set of possible CHs in each cluster. The LEACH-SAGA routing protocol claims even distribution of the CH in the network with less energy consumption [63]. ...
The networking system refers to the technique which allows users to share the information and requires lifetime efficient wireless networking protocols that are energy efficient and provides low latency. The applications of wireless sensor network cover a wide range and provide remote monitoring using networked microsensors. During efficient scrutiny of the network, they suffer for inadequacy information, but it is rarely seen in orthodoxly circuited computing systems. An application-specific algorithmic architecture is comparatively more preferable than the traditional layer formed approach. Low-energy adaptive clustering hierarchy (LEACH) is one the modern protocols for remote sensor networks which can unite the notion of both media access and energy-efficient cluster-based routing protocols to gain the best performance in accordance with system lifetime. For reducing information loss for the data aggregation property of LEACH-B, a simulation that has modified the “LEACH-B” has been proposed to ensure optimization and more robustness.
... This is scale-independent and converges in time proportional to the deployment density of the nodes regardless of the overall number of nodes in the network. ACE requires no understanding of geographic location and requires only petite amount of communication overhead [4][5][6]. ...
Wireless sensor network (WSN) is a low-powered prestigious network fashioned by sensor nodes that treasures application in civilian, military, visual sense models and many others. Reduced energy utilization is an exigent task for these sensor networks. By the data aggregation procedure, needless communication between sensor nodes, cluster head and the base station is eluded. An evaluation of energy efficient optical low energy adaptive clustering hierarchy has been performed and the enactments have been compared with the prevailing low energy adaptive clustering hierarchy algorithm, between two detached wireless sensor network fields. The proposed clustering procedure has been primarily implemented to join two distinct wireless sensor fields. An optical fiber is used to join two reserved wireless sensor fields. This distributed clustering methodology chiefly targets in exploiting the parameters like network lifetime, throughput and energy efficiency of the whole wireless sensor system.
... In some works, [28][29][30] researchers used an optimization algorithm to find optimal cluster size and cluster heads in wireless sensor networks and sensor-based CRNs. The optimization algorithms like fuzzy, genetic, simulated annealing, and PSO are used for cluster optimization. ...
Wireless ad hoc networks with additional features of dynamic spectrum access (DSA) are called cognitive radio networks (CRNs) which have the ability to overcome spectrum shortage problem. It is capable to construct collaborative clusters in a dynamic environment to achieve an interference resilience and minimum communication overhead. In this work, a clustering algorithm based on the golden ratio optimization method (GROM) and fuzzy clustering are proposed. The GROM, formulated by the well-known mathematician Fibonacci, is used to select eligible cluster heads in the network. The objective of the optimization fitness function is to choose cluster head by considering the parameters of a higher number of free channels, node degree, remaining energy, speed, and distance to the fusion center. In clustering, fuzzy logic is applied to increase the number of common channels, and it also reduces the number of overlap channels among clusters which increase the cluster stability. The numerical evaluation shows considerable improvement of clustering performance achieved by the proposed clustering when compared with other related works.
... The utility function of existing models may lacks in network adaption and ignores the need of fault tolerance over network function while dealing with energy efficiency. Henceforth, in this investigation, energy efficiency and fault tolerance based clustering procedure are anticipated to endure above mentioned confronts by Zhang et al. (2014). In clustering, flower pollination was utilized for clustering nodes and choosing those nodes for transmission. ...
The significance of wireless sensor network (WSN) applications is to examine dangerous and remote fields that are not reachable or complex or expensive to reach human insights. This feature leads to self-managed networking that may face enormous confronts in energy consumption, fault tolerance and network lifetime based restraints owing certain non-renewable energy resources. From this research, an effectual managing strategy has been provided and methodology to tolerate faults in a network has been anticipated. To model these kinds of framework, fault recognition and revitalization approaches for handling diverse faulty levels have to be considered, i.e. communication and network nodes among them are used. The anticipated management strategy and protocol model may improve network-based fault tolerance ability in network nodes and corresponding transmission among them. As well as, network lifetime is increased for about five times higher than existing methods. Subsequently, it is validated that network fault tolerance proficiency is decreased with 2% and improved network lifetime with 10%. It improves data transmission and reduces energy consumption and increases network lifetime. Simulation is carried out in MATLAB 2018a environment. This model provides the finest results in terms of fault tolerance, network lifetime and energy consumption.
... In recent years, heuristic and metaheuristic algorithms have been applied to WSNs for theoretical research [37][38][39]. However, many of the above algorithms have also been applied to clustering routing protocols to optimize the selection process of cluster heads, thus improving the network's life cycle [40][41][42][43][44][45]. Wang et al. proposed a special clustering method called energy centers searching using particle swarm optimization (EC-PSO) [46]. ...
Wireless sensor network (WSN) nodes are devices with limited power, and rational utilization of node energy and prolonging the network lifetime are the main objectives of the WSN’s routing protocol. However, irrational considerations of heterogeneity of node energy will lead to an energy imbalance between nodes in heterogeneous WSNs (HWSNs). Therefore, in this paper, a routing protocol for HWSNs based on the modified grey wolf optimizer (HMGWO) is proposed. First, the protocol selects the appropriate initial clusters by defining different fitness functions for heterogeneous energy nodes; the nodes’ fitness values are then calculated and treated as initial weights in the GWO. At the same time, the weights are dynamically updated according to the distance between the wolves and their prey and coefficient vectors to improve the GWO’s optimization ability and ensure the selection of the optimal cluster heads (CHs). The experimental results indicate that the network lifecycle of the HMGWO protocol improves by 55.7%, 31.9%, 46.3%, and 27.0%, respectively, compared with the stable election protocol (SEP), distributed energy-efficient clustering algorithm (DEEC), modified SEP (M-SEP), and fitness-value-based improved GWO (FIGWO) protocols. In terms of the power consumption and network throughput, the HMGWO is also superior to other protocols.
... Base station layout intelligent algorithm based on heuristic search is more adaptable and easily to model [20]. Zhang et al. [21] proposed a solution based on Simulated Annealing (SA) algorithm, but the initial value of "temperature" and the rate of decline in the simulated annealing algorithm need to be repeated several times to determine. Pereira et al. [22] used the particle swarm optimization algorithm based on the idea of group intelligent optimization to apply to the base station optimization problem, which is easy to modify the objective function, and can be implemented in parallel with good scalability. ...
Abstract The indoor scene has the characteristics of complexity and Non-Line of Sight (NLOS). Therefore, in the application of cellular network positioning, the layout of the base station has a significant influence on the positioning accuracy. In three-dimensional indoor positioning, the layout of the base station only focuses on the network capacity and the quality of positioning signal. At present, the influence of the coverage and positioning accuracy has not been considered. Therefore, a network element layout optimization algorithm based on improved Adaptive Simulated Annealing and Genetic Algorithm (ASA-GA) is proposed in this paper. Firstly, a three-dimensional positioning signal coverage model and a base station layout model are established. Then, the ASA-GA algorithm is proposed for optimizing the base station layout scheme. Experimental results show that the proposed ASA-GA algorithm has a faster convergence speed, which is 16.7% higher than the AG-AC (Adaptive Genetic Combining Ant Colony) algorithm. It takes about 25 generations to achieve full coverage. At the same time, the proposed algorithm has better coverage capability. After optimization of the layout of the network element, the effective coverage rate is increased from 89.77 to 100% and the average location error decreased from 2.874 to 0.983 m, which is about 16% lower than the AG-AC algorithm and 22% lower than the AGA (Adaptive Genetic Algorithm) algorithm.
... In addition there should be electronic "check -in " and "checkout " stations at the entry and exit points of the automated lane, somewhat analogous to the toll booths on close where you a ticket at the entrance and then pay a toll at the exit ,based on how far you travel on the road at checking station ,wireless communication between vehicles and road side would verify that the vehicle is in proper operating condition prior to its entry to the automated line .similarly, the check out system would seek assurance of the drivers readiness to resume control at the exit the traffic management system for an automated highway would also have broader scope than today's traffic systems, because it would select an optimal route for every vehicle in the system ,continuously balancing travel demand the system capacity ,and directing vehicles to follow those routes precisely [25][26][27][28][29]. Most of the functions have already been implemented and tested in experimental vehicles. ...
... Hybrid Energy Efficient Distributed Clustering (HEED): This particular approach is mainly formulated so as to attain effective clusters in a wireless sensor network [15]. HEED algorithm mainly depends upon residual energy and communication cost for forming effective clusters. ...
... Além de Redes de Petri, ferramentas computacionais podem ser desenvolvidas para estimar o consumo de energia em redes de sensores, desde que implementem um modelo matemático consistente para embasar os cálculos realizados, como visto em [8,9,28]. Ferramentas computacionais para estimativas de desempenho são muitoúteis pois facilitam sobremaneira diversos tipos de análises, uma vez que as ferramentas são geralmente desenvolvidas sobre um modelo matemático já definido. ...
Wireless sensor networks have an important role in the current scenario of new communication technologies, focused on Internet of Things and Smart Cities applications. In those networks, energy issues are central, since many wireless sensor networks are developed to operate with battery-operated sensors. In such way, the proper planning of wireless sensor networks is required for good performance and there are some techniques to assess the performance of those networks without requiring deployment of real sensors. This article proposes a new mathematical model to assess energy consumption in camera-enabled sensors, allowing relevant measurements before deployment of physical networks. Besides this innovate mathematical model, a new tool was developed, referred as EnergyWVSN, aimed at the support of practical usage of the proposed model.
... Além de Redes de Petri, ferramentas computacionais podem ser desenvolvidas para estimar o consumo de energia em redes de sensores, desde que implementem um modelo matemático consistente para embasar os cálculos realizados, como visto em [8,9,28]. Ferramentas computacionais para estimativas de desempenho são muitoúteis pois facilitam sobremaneira diversos tipos de análises, uma vez que as ferramentas são geralmente desenvolvidas sobre um modelo matemático já definido. ...
... The weakness of LEACH-MAC is overhead problem and complexity in the network. In [22] a genetic algorithm-based routing protocol called LEACH simulated annealing and genetic algorithm was proposed. In this protocol, the BS places itself at the centre point and calculates the distance and energy of all SN with respect to the centre point. ...
The fault is inevitable in case of the wireless sensor network (WSN) because of its remote deployment and constrained architecture. In literature, many algorithms have been proposed to address several types of fault in the WSN life-cycle. In the context of fault tolerance, the clustering method has been adopted as a proven technique. Heintzelman et al. first considered the clustering technique and proposed the seminal low energy adaptive clustering hierarchy (LEACH) algorithm for fault handling in WSN. In this study, the authors propose a LEACH variant clustering convention called partitioned-based energy-efficient – LEACH (PE-LEACH) protocol which tends to the energy-based fault-tolerant technique. They also study and present a taxonomy on LEACH variants. The execution of PE-LEACH is analysed against its predecessors; hard-computing based LEACH, energy-efficient LEACH (E-LEACH) convention and soft-computing-based energy-swarm-optimisation LEACH (ESO-LEACH). They have found through their recreation that PE-LEACH outperforms than LEACH and E-LEACH separately whereas, for ESO-LEACH the PE-LEACH is a tough competitor.
... Similarly, in [25] the same mechanism, in two rounds, is used for selection of a secondary cluster head, which becomes the cluster head when the energy level of the cluster head falls below a certain threshold. LEACH-SAGA [26] is another enhancement of the LEACH algorithm, which is based on a simulated annealing and genetic algorithm. In LEACH-SAGA the clusters are formed by genetic algorithms and simulated annealing. ...
Smart ocean is a term broadly used for monitoring the ocean surface, sea habitat monitoring, and mineral exploration to name a few. Development of an efficient routing protocol for smart oceans is a non-trivial task because of various challenges, such as presence of tidal waves, multiple sources of noise, high propagation delay, and low bandwidth. In this paper, we have proposed a routing protocol named adaptive node clustering technique for smart ocean underwater sensor network (SOSNET). SOSNET employs a moth flame optimizer (MFO) based technique for selecting a near optimal number of clusters required for routing. MFO is a bio inspired optimization technique, which takes into account the movement of moths towards light. The SOSNET algorithm is compared with other bio inspired algorithms such as comprehensive learning particle swarm optimization (CLPSO), ant colony optimization (ACO), and gray wolf optimization (GWO). All these algorithms are used for routing optimization. The performance metrics used for this comparison are transmission range of nodes, node density, and grid size. These parameters are varied during the simulation, and the results indicate that SOSNET performed better than other algorithms.
... Because there are many limitations in Wireless Sensor Networks, it is necessary to design the routing protocol. In Sensor networks, there are many network resource limitations such as energy, bandwidth, central processing unit, memory [15]. Due to the efficient use of radio and energy resources and the need for effective operational capability, a routing protocol in sensor networks is expected to provide the following requirements [16][17][18][19]:Energy Efficiency: The Routing Protocol should extend the life of the network by allowing good connectivity and communication between the nodes. ...
Wireless sensor networks consist of low cost sensor nodes which have limited power supplies, memory capacity, processing capability and transmission rate. Sensor nodes gather information from the environment and send the collected information to base station with help of a routing cooperation. Because of limited resources in Wireless Sensor Networks, fulfilling these routing operations is a major problem. Routing protocols are used to perform these operations. The most important thing by considering while these protocols are designed is energy efficiency. Because wireless sensor networks are widely used in intelligent systems, the energy efficiency of these networks is very important in IoT. Researchers have proposed several hierarchical routing protocols such as LEACH, PEGASIS, TEEN and APTEEN. In this study, an energy efficient routing protocol is developed which is more efficient than currently avaliable routing protocols. The developed protocol involves mapping of the network, sleep–wake/load balancing, data merge processes. The proposed protocol gives better results than other protocols in number of surviving nodes and amount of energy consumed criterias.
... Zhang et al. [48] proposed a clustering routing protocol for balancing energy in WSNs based on simulated annealing (SA) and genetic algorithm (GA). Firstly, sensor nodes are clustered by SA and GA, and then the cluster center of each cluster is calculated. ...
In recent years, wireless sensor networks (WSNs) have attracted many researchers due to their widely usage in a wide range of applications. One of the most important problems in these networks is energy consumption that has a direct effect on network lifetime. Clustering is one of the most important solutions in order to overcome the problem. Energy resource limitation is a fundamental problem in WSNs and clustering protocols provide suitable procedures in order to enhance network lifetime. However, they impose high energy consumption on cluster heads (CH), and therefore, in each round, the protocol should reform clusters and change CH in order to enhance network lifetime. Although these protocols are proper for clustering, do not guarantee suitable CH selection. In this paper, a novel energy-efficient method is proposed using fuzzy logic and three parameters including the amount of energy in CH, distance from CH to base station, and the number of connections in CH. In fact, we focus on the cluster formation process. The proposed model is compared to the well-known low-energy adaptive clustering hierarchy protocol. Simulation results demonstrate that the proposed protocol improves network lifetime.
... Ye, Li, Chen and Wu proposed EECS [22][23][24][25][26], which is based on a supposition that all CHs can communicate directly with the BS. The clusters have variable size, those closer to the CH are larger in size and those farther from CH are smaller in size. ...
... By analyzing the cluster formation process of LEACH [9] protocol, it is found that it just considers the communication cost between the cluster head and normal node; it fails to consider the remaining energy of cluster head and its location information which results in rapid depletion of network lifetime. On the other hand, random cluster head selection mechanism of LEACH protocol lead to uneven distribution of cluster head node which is main cause behind increase in energy consumption because of increase in transmission distance, thereby affecting the life cycle of the network [7]. ...
Prolonging lifetime of wireless sensor network is a most significant problem due to energy constraint nature of sensor nodes. It is difficult to recharge nodes during network lifetime, to increase application area of WSN there is a need to design energy efficient clustering protocol for WSN. In this article there is a discussion about problems in Leach protocol and propose an improvement on the Leach routing protocol to reduce energy consumption and to extend network lifetime. Proposed self organized cluster based energy balanced routing protocol (SCERP) selects a cluster head node by considering probability based on ratio of residual energy of the node and the average energy level of nodes in network, and the geometric distance between the candidate node to the BS as key parameters. The outcome of simulation shows that proposed protocol is better than Leach in terms of balancing energy consumption of nodes and extending WSN lifetime.
... In addition there should be electronic "check -in " and "check-out " stations at the entry and exit points of the automated lane, somewhat analogous to the toll booths on close where you a ticket at the entrance and then pay a toll at the exit ,based on how far you travel on the road at checking station ,wireless communication between vehicles and road side would verify that the vehicle is in proper operating condition prior to its entry to the automated line .similarly, the check out system would seek assurance of the drivers readiness to resume control at the exit the traffic management system for an automated highway would also have broader scope than today's traffic systems, because it would select an optimal route for every vehicle in the system ,continuously balancing travel demand the system capacity ,and directing vehicles to follow those routes precisely [25][26][27][28][29]. ...
Intelligent transportation systems (ITS) are advanced applications which, without embodying intelligence as such, aim to provide innovative services relating to different modes of transport and traffic management and enable various users to be better informed and make safer, more coordinated, and 'smarter' use of transport networks. Highway travel is the lifeblood of modern industrial nations. The larger roads are sorely over burdened: around the major cities, heavy usage slows most peak-hour travel on freeways to less than 60 kilometers per hour. In all excessive traffic causes more than five billion hours delay every year; it wastes countless gallons of fuel and needless multiplies exhaust emission. The main goal of this paper is to make the experience of driving less burdensome and accident less, especially on long trips. This can be achieved by making the highway itself part of the driving experience and integrating roadside technologies that would allow the overburdened highway system to be used more efficiently. The automobile will have automatic throttle, braking and steering control.
... Hence, quite a group of measurement points are also enviable. This smart environment is necessarily demanding both for the wireless sensor node electronics and for the short-range wireless network in which communication range is to a vast extent longer in wide areas [22][23][24][25][26][27]. ...
... During the early stages of the concept of WSN technology particularly during the period of first generation sensor network one way communication is much more enough [27][28][29]. But advancement of technology lead us into a new phase of second generation sensor network where in some scenarios the commander has to take control of the sensor node where we need duplexed communication techniques say to steer electro optical sensors like CC TV [20][21][22][23][24][25][26]. ...
Due to the radio range of the network; suspicious transmission; unattended nature; and easier access; Wireless Sensor Networks are vulnerable to malicious users and physical attacks. Hence security is a must in these cases. The development of a WSN for a secured temperature measurement system could be a feasible answer to these issues. The temperature signals are collected by sensors and transmitted to an Advanced RISC Microprocessor (ARM) via Wireless Fidelity (Wi-Fi) technology, which has been proven to transfer data accurately and reliably. The data is then stored in memory that is controlled by the microprocessor. The functionality is created using an ARM 9-based Samsung S3C2440 Controller with the Linux operating system. The security system is incorporated using the host MCUs and the temperature values are converted to digital form using the ARM processor's ADC (S3C2440). The processor is connected to the console terminal through UART, which sends data to the system on a regular basis with security data being monitored and transferred to other Wi-Fi-equipped devices through a USB-based Wi-Fi module, and the temperature readings are continuously monitored via this wireless sensor network. We perform the validation of our study through MATLAB simulations. Through MATLAB simulations we measure the total energy dissipated, throughput, and the lifetime of the sensor nodes. Overall, in this research, we develop an improved security in WSN system with application in ARM controller based secured temperature monitoring system. This paper paves a direction towards further research in physical security in Wireless Sensor Networks.
Network lifetime and energy consumption are the important requirement of wireless sensor networks. The sensor network is mainly used for the military and civil applications, habitat monitoring. These tasks consume more energy for the data processing and directly affect the network lifetime. Clustering methodology provides a better solution for prolonging the network lifetime and reducing the energy consumption. In this paper, moth flame optimization algorithm is proposed in LEACH-C algorithm for identifying the suitable cluster head in wireless sensor networks. The proposed methodology uses the navigation method of moths for balancing the exploration and exploitation phases in the optimization process. The residual energy of the node and distance between the cluster head and sensor node are utilized to calculate the fitness function. The proposed methodology is evaluated with the help of performance metrics of network lifetime, energy consumption and number of alive nodes. The proposed methodology prolongs the network lifetime and reduces the energy consumption.
Background
Indeed, even following 20 years of presence, LEACH protocol is as yet picking up the consideration of the examination network working in the territory of wireless sensor networks (WSNs). This demonstrates the significance of LEACH protocol. Professionals have thought of different and various adjustments of the LEACH convention. Beneficiaries of LEACH convention are presently accessible from single hop to multi-hop positions.
Methods
The present paper reviews different variations of LEACH steering conventions introduced up until this point and examines the upgrade and working of them. We have examined 65 unique variations of LEACH and inspected how they improve imperativeness usage in WSNs and augmentation framework's lifetime. This study classifies every one of the conventions in two areas, to be specific, single-hop correspondence and multi-hop correspondence dependent on information communication from the cluster head to the base station
Results
A complete investigation utilizing eight unique criteria’s, for example, energy efficiency, scalability, delay, overhead, etc, has been given in an ordered manner.
Conclusion
The article additionally talks about the solid and feeble purposes of each also every variation of LEACH. At last, the paper finishes up with proposals on future research spaces in the zone of WSN.
In the past two decades, network clustering has been proven as efficient approach for data collection and routing in wireless sensor networks (WSNs). It provides several advantages over other methods in terms of energy efficiency, scalability, even energy distribution, etc. Given the limited capabilities of sensor nodes energy resources, processing power, and communication range, cluster-based protocols accommodate the network’s operation with these constraints. Several survey papers present and compare many clustering algorithms from various perspectives. However, most of these surveys either are outdated or have limited scope. This paper provides a comprehensive review of clustering algorithms where the new ideas and concepts proposed in each phase of the clustering process are extensively studied. Three topics are discussed in this review. First, we present the objectives, characteristics and challenges of clustering algorithms. Second, the cluster-head selection methods for different types of WSNs are extensively studied. Third, this review presents a detailed description of newly proposed methods to handle energy heterogeneity, energy harvesting, fault-tolerance, scalability, mobility and data correlation in WSNs. Furthermore, the protocols taxonomy in each phase is discussed to provide a deeper understanding of current clustering approaches. Finally, a set of criteria is presented to simplify the comparison and identify each protocol’s pros and cons. This review presents a comprehensive introduction and can be a useful guidance for new researchers in this field. Also, it will help system designers to identify alternative solutions for selecting an appropriate method in each phase of the clustering process.
We introduce two novel evolutionary algorithms for the problem of optimising electricity distribution networks in remote areas. Traditionally, electricity networks have been built using a centralised network infrastructure. In remote areas these typically include long distances between sparsely distributed consumers that lead to high costs and several risks that accompany these long connection lines. Therefore, alternative distributed infrastructures including potential microgrids or stand-alone power systems can be beneficial. Given a set of electricity consumers, their loads and locations, the aim is to find an optimal electricity network topology that might not be interconnected. Previously, this problem has been addressed using different standard clustering approaches comparing the total network costs of each solution. We propose a problem-specific evolutionary algorithm that alters the network structure directly as well as a novel quadtree-based evolutionary algorithm. The algorithms minimise a non-linear objective function representing the cost of the network while approximating real-world constraints. They are tested on a large set of various problem instances and compared to the standard clustering algorithms that have been used previously and an intuitive baseline method. The problem-specific evolutionary algorithm outperforms most standard clustering methods on a range of different test cases while the quadtree-based algorithm is shown to be effective in certain settings.
Energy-efficient resource-optimization for multiple application scenarios requires appropriate clustering-based network-fractioning that skillfully removes unbalanced network connectivity, which is a stimulating bottleneck in WSN-performance. This paper proposes a new Uniform Connectivity-based clustering Protocol, called Lines-of-Uniformity based Enhanced-Threshold (LUET) to provide energy-efficient coverage in three-tier heterogeneous WSN. This protocol considers the node’s remnant-energy and its proximity from either of the lines of uniformity for lowering down average isolated node count in WSN. This paper also proposes a rotation epoch-based LUET variant, (LUET|R) that incorporates static epoch for initial clustering rounds until First-Node-Death to overcome the rapid fall after the death of the first node. The simulation model demonstrates the superiority of LUET and its variants over other established clustering protocols in terms of network-lifetime, power-efficiency, net death-rate, average isolated-nodes, throughput.
Index Terms Clustering, Energy-efficiency, Heterogeneous-networks, Lifetime-estimation, WSN
Wireless sensor network (WSN) consists of a large number of sensor nodes distributed over a certain target area. The WSN plays a vital role in surveillance, advanced healthcare, and commercialized industrial automation. Enhancing energy-efficiency of the WSN is a prime concern because higher energy consumption restricts the lifetime (LT) of the network. Clustering is a powerful technique widely adopted to increase LT of the network and reduce the transmission energy consumption. In this article (LT) we develop a novel ARSH-FATI-based Cluster Head Selection (ARSH-FATI-CHS) algorithm integrated with a heuristic called novel ranked-based clustering (NRC) to reduce the communication energy consumption of the sensor nodes while efficiently enhancing LT of the network. Unlike other population-based algorithms ARSH-FATI-CHS dynamically switches between exploration and exploitation of the search process during run-time to achieve higher performance trade-off and significantly increase LT of the network. ARSH-FATI-CHS considers the residual energy, communication distance parameters, and workload during cluster heads (CHs) selection. We simulate our proposed ARSH-FATI-CHS and generate various results to determine the performance of the WSN in terms of LT. We compare our results with state-of-the-art particle swarm optimization (PSO) and prove that ARSH-FATI-CHS approach improves the LT of the network by
$\sim \text{25}\%$
.
The real-time properties and operational constraints of Wireless Sensor Networks (WSNs) have emerged the need for designing
energy efficient routing protocols. Recently, software defined network based WSN (SDN-WSN) emerging technology has offered
a significant development by untying control logic plane from the low power sensor nodes. This centralized programmable control
still suffers from several configuration challenges in distributed sensors environment. Meta-heuristic based SDN approaches had
been proposed for the efficient path selection in WSN but they still suffer from both, exploration and exploitation problems.
Therefore, this paper addresses these shortcomings by proposing a meta-heuristic based dolphin echolocation algorithm (DEA) for
optimizing route selection in WSNs. Objective function of the DEA algorithm is to consider the residual energy of the nodes for
selecting energy efficient routes. The proposed algorithm performance is compared with several meta-heuristic algorithms in terms of energy-consumption, and network throughput parameters.
Water cycle algorithm (WCA) is a relatively new bio-inspired algorithm in the field of wireless sensor networks (WSN). In this work WCA has been applied independently to three energy models of WSN, with a view to optimize the energy spent on data communication in the nodes. By taking different sets of node population sizes, the energy performance is analyzed from the point of view of the percentage reduction of energy depleted, and the number of iterations needed to achieve the optimum value. Based on the simulation results, some salient trends are commented upon. The implementation renders an energy reduction of up to 46.24% in the sensor nodes, which is a promising outcome, and must be investigated further.
Energy consumption has to be considered when developing energy-efficient routing algorithms, which has been a challenging issue in the field of WSNs. The idea of LEACH is dynamic clustering that brings extra overhead, such as head changes and advertisements, which may diminish the gain in energy consumption. Moreover, PEGASIS a near optimal chain-based protocol proposed, it was an improvement over LEACH protocol to extend the network lifetime. However, PEGASIS data transmission will create time-delay and, the probability of long chain is always high because of the limitations of greedy algorithm approach for such shortcomings, many protocols was proposed by researchers recently improved algorithms based on PEGASIS such as PEG-Ant, PDCH and PCC et al. Among them, EEPB, and IEEPB was proposed. In this paper, a survey of some routing protocols that are classified based on PEGASIS topology was conducted, and conclude with some open research problems for further research.
Wireless sensor networks continue to get tremendous popularity, as evidenced by the
increasing number of applications. Sophistication of wireless communications had enabled the
development of low-cost, low-power wireless sensor networks (WSNs) with wide applicability,
including environment and vehicle-health monitoring system. WSN reduce the energy consumption
and hence maximize the lifetime of the network which are the key requirements in the design of
optimum sensor networking protocols and algorithms. The limiting factors of the sensor nodes, such as
their finite energy supplies and their moderate processing abilities, as well as the unreliable wireless
medium restrict the performance of wireless sensor networks. Several routing protocols with different
objectives have been proposed for energy-efficient WSNs applications. This article surveys a sample
of existing energy-efficient cluster-based protocols PEGASIS, LEACH, EEHC, HEED, DWEHC,
BMA, BCDCP, THEEM and highlights their key features, including merits and limitations.
This paper describes a. multi-objective optimization method for the design of stall-regulated horizontal-axis wind turbines. Two modules are used for this purpose: an aerodynamic model implementing the blade-element theory and a multi-objective evolutionary algorithm. The former provides a sufficiently accurate solution of the flow field around the rotor disc; the latter handles the decision variables of the optimization problem, i.e., the main geometrical parameters of the rotor configuration, and promotes function optimization. The scope of the method is to achieve the best trade-off performance between two objectives: annual energy production per square meter of wind park (to be maximized) and cost of energy (to be minimized). Examples of the best solutions found by the method are described and their performance compared with those of commercial wind turbines.
There is a deep and useful connection between statistical mechanics (the behavior of systems with many degrees of freedom in thermal equilibrium at a finite temperature) and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters). A detailed analogy with annealing in solids provides a framework for optimization of the properties of very large and complex systems. This connection to statistical mechanics exposes new information and provides an unfamiliar perspective on traditional optimization problems and methods.
The advancement in wireless communications and electronics has enabled the development of low-cost sensor networks. The sensor networks can be used for various application areas (e.g., health, military, home). For different application areas, there are different technical issues that researchers are currently resolving. The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections. This article also points out the open research issues and intends to spark new interests and developments in this field.
Through the thorough study of existing clustering algorithms, with the problem of typical combinatorial optimization and the idea of simulated annealing algorithm, a best clustering scheme of the wireless sensor network was proposed based on simulated annealing algorithm. The assembled cluster head nodes were assembied and abstracted to a referenced model, objective cluster head collection was obtained through certain perturbation factors from continuous iteration. The idea of simulated annealing algorithm was used to the choosing process of the best number of clusters. This paper introduces the realization of the whole process in detail. The best number of clusters, persistent time, iterative times are studied and analyzed through established mathematics model and simulated experiments.
In recent ten years, wireless sensor network technology has a rapid development. After a brief introduction of the wireless sensor network, some main research results of energy conservation and node deployment is provided. Then the applications of WSN in the medical health, environment and agriculture, intelligent home furnishing and building, military, space and marine exploration are outlined. In addition, we analyze the advantage of WSN in these areas. Finally, we summarize the main factors that affect the applications of wireless sensor network.
Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.
A wireless sensor network (WSN) has important applications such as remote environmental monitoring and target tracking. This has been enabled by the availability, particularly in recent years, of sensors that are smaller, cheaper, and intelligent. These sensors are equipped with wireless interfaces with which they can communicate with one another to form a network. The design of a WSN depends significantly on the application, and it must consider factors such as the environment, the application’s design objectives, cost, hardware, and system constraints. The goal of our survey is to present a comprehensive review of the recent literature since the publication of [I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, A survey on sensor networks, IEEE Communications Magazine, 2002]. Following a top-down approach, we give an overview of several new applications and then review the literature on various aspects of WSNs. We classify the problems into three different categories: (1) internal platform and underlying operating system, (2) communication protocol stack, and (3) network services, provisioning, and deployment. We review the major development in these three categories and outline new challenges.
Sensor webs consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. Gathering sensed information in an energy efficient manner is critical to operate the sensor network for a long period of time. In W. Heinzelman et al. (Proc. Hawaii Conf. on System Sci., 2000), a data collection problem is defined where, in a round of communication, each sensor node has a packet to be sent to the distant base station. If each node transmits its sensed data directly to the base station then it will deplete its power quickly. The LEACH protocol presented by W. Heinzelman et al. is an elegant solution where clusters are formed to fuse data before transmitting to the base station. By randomizing the cluster heads chosen to transmit to the base station, LEACH achieves a factor of 8 improvement compared to direct transmissions, as measured in terms of when nodes die. In this paper, we propose PEGASIS (power-efficient gathering in sensor information systems), a near optimal chain-based protocol that is an improvement over LEACH. In PEGASIS, each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round. Simulation results show that PEGASIS performs better than LEACH by about 100 to 300% when 1%, 20%, 50%, and 100% of nodes die for different network sizes and topologies.
Sensor network optimization using a genetic algorithm
- S Jin
- M Zhou
- A S Wu
S. Jin, M. Zhou and A. S. Wu, "Sensor network optimization using a genetic algorithm", In: Proceedings of
the 7th world multiconference on systemics, cybernetics, and informatics, (2003).