ABC algorithm‐based trustworthy energy‐efficient MIMO routing protocol

This paper introduces artificial bee algorithm (ABC)‐based energy‐efficient protocol with security for the enhancement of lifetime of wireless sensor network. A trustworthy energy‐efficient routing MIMO (TEEM) technique is used by implementing MIMO technique in TEER protocol to isolate malicious nodes and to reduce the fading effects and interference in the network. The performance of ABC‐based trustworthy energy‐efficient MIMO routing (ABC‐TEEM) protocol is analysed. Alive node performance, residual energy, throughput analysis, and pocket loss rate of ABC‐TEEM protocol for WSN are computed and compared with the performance of existing TEEM protocol for various diversity orders.     

Performance modeling and optimization of multiple‐objective cross‐layer design in multi‐flow ad‐hoc networks

In ad‐hoc wireless networks, to achieve good performance, multiple parameters need to be optimized jointly. However, existing literature lacks a design framework that investigates the synchronic impact of several parameters on overall system performance. Among several design parameters, energy conservation, end‐to‐end delay minimization, and improved throughput are considered most important for efficient operation of these networks. In this paper, we propose a novel scheme for multiple‐objective cross‐layer optimization capable of optimizing all these performance objectives simultaneously for reliable, energy‐efficient, and timely transmission of continuous media information across the network. The three global criteria considered for optimization are incorporated in a single programming problem via linear scalarization. Besides, we employ standard convex optimization method and Lagrangian technique to solve the proposed problem to seek optimality. Extensive simulation results are generated accounting for several topologies with multiple concurrent flows in the network. These results are used to validate the analytical results and demonstrate the efficiency of the proposed optimization model. Efficiency of the model is verified by finding the set of Pareto‐optimal solutions plotted in three‐dimensional objective space. These solution points constituting the Pareto front are used as the best possible balance points among maximum throughput, maximum residual energy, and least network delay. Finally, to emphasize the effectiveness and supremacy of our proposed multiple‐objective cross‐layer design scheme, we compare it with the conventional multiple‐objective genetic algorithm. Simulation results demonstrate that our method provides significant performance gain over the genetic algorithm approach in terms of the above specified three objectives.     

Bio‐inspired Load Balancing Routing for Delay‐Guaranteed Services in Ever‐Changing Networks

We consider a new load balancing routing for delay‐guaranteed services in the network in which the traffic is dynamic and network topologies frequently change. For such an ever‐changing network, we propose a new online load balancing routing called AntLBR, which exploits the ant colony optimization method. Generally, to achieve load balancing, researchers have tried to calculate the traffic split ratio by solving a complicated linear programming (LP) problem under the static network environment. In contrast, the proposed AntLBR does not make any attempt to solve this complicated LP problem. So as to achieve load balancing, AntLBR simply forwards incoming flows by referring to the amount of pheromone trails. Simulation results indicate that the AntLBR algorithm achieves a more load‐balanced network under the changing network environment than techniques used in previous research while guaranteeing the requirements of delay‐guaranteed services.     

Cluster based wireless sensor network routing using artificial bee colony algorithm

Due to recent advances in wireless communication technologies, there has been a rapid growth in wireless sensor networks research during the past few decades. Many novel architectures, protocols, algorithms, and applications have been proposed and implemented. The efficiency of these networks is highly dependent on routing protocols directly affecting the network life-time. Clustering is one of the most popular techniques preferred in routing operations. In this paper, a novel energy efficient clustering mechanism, based on artificial bee colony algorithm, is presented to prolong the network life-time. Artificial bee colony algorithm, simulating the intelligent foraging behavior of honey bee swarms, has been successfully used in clustering techniques. The performance of the proposed approach is compared with protocols based on LEACH and particle swarm optimization, which are studied in several routing applications. The results of the experiments show that the artificial bee colony algorithm based clustering can successfully be applied to WSN routing protocols.     

A survey and analysis of multipath routing protocols in wireless multimedia sensor networks

The main objective of this research is to conduct a performance analysis of various multipath routing protocols in wireless multimedia sensor networks for the efficient transmission of the image, audio and video data. To provide efficient routing for the large sized multimedia content, various multipath routing protocols such as energy-aware routing, QoS based routing and geographical routing methods are analyzed. In this analysis, the efficient routing techniques including geographical routing techniques such as GPSR, DGR, PW-DGR presented for wireless multimedia sensor networks are studied and the performance of each technique is evaluated to determine the efficient multipath routing technique. Comparisons are made for evaluated protocols and it is proved that the PW-DGR provides better routing performance for the multimedia data. The findings of the research also show that the PW-DGR method efficiently overcomes the routing problems such as energy bottleneck problem, energy-hole, reduced network lifetime and high delay in packet transmission.     

Topological design,routing and capacity dimensioning for ISL networks in broadband LEO satellite systems

This paper considers the network design of intersatellite link (ISL) networks in broadband LEO satellite systems, where the major challenge is the topology dynamics. First, a general method to design convenient ISL topologies for connection‐oriented operation is presented, and a reference topology for numerical studies is derived. A permanent virtual topology is then defined on top of the orbiting physical one, thus forming a framework for discrete‐time dynamic traffic routing. On this basis, heuristic and optimization approaches for the combined routing and dimensioning task, operating on discrete time steps, are presented and their performance is numerically compared. It is shown that minimizing the worst‐case link capacity is an appropriate target function, which can be formulated as linear optimization problem with linear constraints. Using linear programming (LP) techniques, the dimensioning results are clearly better than with simple heuristic approaches. Copyright © 2001 John Wiley & Sons, Ltd.     

Multi-objective fractional artificial bee colony algorithm to energy aware routing protocol in wireless sensor network

Due to the promising application of collecting information from remote or inaccessible location, wireless sensor networks pose big challenge for data routing to maximize the communication with more energy efficient. Literature presents different cluster-based energy aware routing protocol for maximizing the life time of sensor nodes. Accordingly, an energy efficient clustering mechanism, based on artificial bee colony algorithm and factional calculus is proposed in this paper to maximize the network energy and life time of nodes by optimally selecting cluster-head. The hybrid optimization algorithm called, multi-objective fractional artificial bee colony is developed to control the convergence rate of ABC with the newly designed fitness function which considered three objectives like, energy consumption, distance travelled and delays to minimize the overall objective. The performance of the proposed FABC-based cluster head selection is compared with LEACH, PSO and ABC-based routing using life time, and energy. The results proved that the proposed FABC maximizes the energy as well as life time of nodes as compared with existing protocols.     

Cross‐Layer Resource Allocation in Multi‐interface Multi‐channel Wireless Multi‐hop Networks

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi‐channel wireless multi‐hop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems — flow control; next‐hop routing; rate allocation and scheduling; power control; and channel allocation — and finally solved by a low‐complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.     

Betweenness centrality based connectivity aware routing algorithm for prolonging network lifetime in wireless sensor networks

Network lifetime is the key design parameter for wireless sensor network protocols. In recent years, based on energy efficient routing techniques numerous methods have been proposed for enhancing network lifetime. These methods have mainly considered residual energy, number of hops and communication cost as route selection metrics. This paper introduces a method for further improvement in the network lifetime by considering network connectivity along with energy efficiency for the selection of data transmission routes. The network lifetime is enhanced by preserving highly connected nodes at initial rounds of data communication to ensure network connectivity during later rounds. Bassed on the above mentioned concept, a connectivity aware routing algorithm: CARA has been proposed. In the proposed algorithm, connectivity factor of a node is calculated on the basis of Betweenness centrality of a node and energy efficient routes are found by using fuzzy logic and ant colony optimization. The simulation results show that the proposed algorithm CARA performs better than other related state-of-the-art energy efficient routing algorithms viz. FML, EEABR and FACOR in terms of network lifetime, connectivity, energy dissipation, load balancing and packet delivery ratio.     

Performance Analysis of Adaptive Routing Structure for Wireless Sensor Network Based on Load Balancing

Wireless sensor network consists of sensor nodes with battery operated device. The key challenges in the wireless sensor network are energy consumption and routing optimization. This work presents the cluster based load balancing (CBLB) routing protocol. The proposed routing protocol is used to minimize the energy consumption and increase the routing performance. It avoids the routing robustness, delay and increases the delivery rate and network performance. In existing techniques, different routing protocols such as LEACH, HEED and MESTER were used to increase the network performance and to decrease the energy consumption. But these existing techniques did not satisfy the performance requirements of wireless sensor networks. Hence, there is a requirement to develop a technique that meets the QoS requirements and needs of wireless sensor network. The proposed CBLB routing protocol creates a cluster head in the decentralized network and the cluster head will be used to distribute the workload evenly to the cluster members for reducing the energy consumption in wireless sensor network. Experimental results analyze the performance of the proposed protocol with the different existing protocols. The proposed protocol achieves high throughput, delivery rate and reduces the energy consumption, delay and routing overhead.     

A routing protocol for mobile ad‐hoc networks using the profit optimization model

Recently, wireless networks have become one of the major development trends in computer network technology. Because there is no more need of the wired transmission medium, applications have thus diversified. One such growing field of wireless networks is the mobile ad‐hoc network (MANET). A MANET consists of mobile hosts (such as portable laptops, vehicles, etc.), and no fixed infrastructure is required. MANETs provide ease of self‐configuration and can extend coverage at a low cost. Numerous applications have therefore been proposed under this network environment for daily life use. Because MANETs nodes are capable of moving, MANET network topology changes frequently. Thus, the traditional routing protocols fail to fit such an environment. In this paper, we propose an efficient routing protocol for MANETs, which integrates the mathematical model of profit optimization (the Kelly formula) from the field of economics to cope with the routing problem caused by node mobility. Some numerical simulations have been conducted to evaluate the performance of the proposed method using the network simulator NS‐2. The results show that our proposed method outperforms conventional routing protocols in packet delivery ratio comparisons; and the average end‐to‐end delays are within a tolerable range. Copyright © 2013 John Wiley & Sons, Ltd.     

Network Lifetime Maximization for Estimation in Multihop Wireless Sensor Networks

We consider the distributed estimation by a network consisting of a fusion center and a set of sensor nodes, where the goal is to maximize the network lifetime, defined as the estimation task cycles accomplished before the network becomes nonfunctional. In energy-limited wireless sensor networks, both local quantization and multihop transmission are essential to save transmission energy and thus prolong the network lifetime. The network lifetime optimization problem includes three components: i) optimizing source coding at each sensor node, ii) optimizing source throughput of each sensor node, and iii) optimizing multihop routing path. Fortunately, source coding optimization can be decoupled from source throughput and multihop routing path optimization, and is solved by introducing a concept of equivalent 1-bit MSE function. Based on the optimal source coding, the source throughput and multihop routing path optimization is formulated as a linear programming (LP) problem, which suggests a new notion of character-based routing. The proposed algorithm is optimal and the simulation results show that a significant gain is achieved by the proposed algorithm compared with heuristic methods.     

Phased arrays in communication system based on Taguchi‐neural networks

Phased antenna array design is one of the most important electromagnetic optimization problems. This research combined the Taguchi method and artificial intelligence methods, used them as the prediction tool in designing parameters for the communication system, and then constructed a set of the optimal parameter analysis flow and steps. In this paper, we present an application of artificial neural networks in the electromagnetic domain. We particularly look at the multilayer perceptron network, which has been the most used of artificial neural networks architectures both in the electromagnetic domain and in the Taguchi optimization technique and describes the Taguchi method to optimize the excitations elements of the linear array to produce a radiation pattern with minimum side lobe level and null placement control. This paper investigates how the implementation of the signal processing in hardware affects the performance of the adaptive array antenna. The investigation is confined to uplink or receive antenna array only. Results of a prototype of antenna array with feeding values designed using the proposed techniques are also presented. Copyright © 2013 John Wiley & Sons, Ltd.     

Optimistic Selection of Cluster Heads Based on Facility Location Problem in Cluster-Based Routing Protocols

Cluster-based routing protocols are one of the most favorable approaches for energy management in wireless sensor networks. The selection of the best cluster heads (CHs), as well as the formation of optimal clusters, is an NP-hard problem. The present study proposes an optimal solution for CHs selection to generate a network topology with optimized network performance. The problem is formulated as facility location problem and a linear programming model is used to solve the optimization problem. Results of analysis o the network simulator (NS2) indicate that applying this method in cluster-based routing protocols prolongs 16 % of the network lifetime, increases 15.5 % of data transmission and improves 5.5 % of throughput, as compared to the results of current heuristic methods such as LEACH, DEEC and EDFCM protocols.     

A gradient‐based multiple‐path routing protocol for low duty‐cycled wireless sensor networks

Routing in a low duty‐cycled wireless sensor network (WSN) has attracted much attention recently because of the challenge that low duty‐cycled sleep scheduling brings to the design of efficient distributed routing protocols for such networks. In a low duty‐cycled WSN, a big problem is how to design an efficient distributed routing protocol, which uses only local network state information while achieving low end‐to‐end (E2E) packet delivery delay and also high packet delivery efficiency. In this paper, we study low duty‐cycled WSNs wherein sensor nodes adopt pseudorandom sleep scheduling for energy saving. The objective of this paper is to design an efficient distributed routing protocol with low overhead. For this purpose, we design a simple but efficient hop‐by‐hop routing protocol, which integrates the ideas of multipath routing and gradient‐based routing for improved routing performance. We conduct extensive simulations, and the results demonstrate the high performance of the proposed protocol in terms of E2E packet delivery latency and packet delivery efficiency as compared with existing protocols. Copyright © 2014 John Wiley & Sons, Ltd.     

A Cognitive Energy Efficient and Trusted Routing Model for the Security of Wireless Sensor Networks: CEMT

There are many smart applications evolved in the area of the wireless sensor networks. The applications of WSNs are exponentially increasing every year which creates a lot of security challenges that need to be addressed to safeguard the devices in WSN. Due to the dynamic characteristics of these resource constrained devices in WSN, there must be high level security requirements to be considered to create a high secure environments. This paper presents an efficient multi attribute based routing algorithm to provide secure routing of information for WSNs. The work proposed in this paper can decrease the energy and enhances the performance of the network than the currently available routing algorithm such as multi-attribute pheromone ant secure routing algorithm based on reputation value and ant-colony optimization algorithm. The proposed work secures the network environment with the improved detection techniques based on nodes’ higher coincidence rates to find the malicious behavior using trust calculation algorithm. This algorithm uses some QoS parameters such as reliability rate, elapsed time to detect impersonation attacks, and stability rate for trust related attacks, to perform an efficient trust calculation of the nodes in communication. The outcome of the simulation show that the proposed method enhances the performance of the network with the improved detection rate and secure routing service.

     

An Adaptive Fuzzy C Means with Seagull Optimization Algorithm for Analysis of WSNs in Agricultural Field with IoT

In recent years, the environmental monitoring in agriculture field is an essential required application. To achieve the environmental monitoring of agriculture fields, the wireless sense networks (WSN) and internet of things is utilized. In the WSN, the energy consumption is a main issue to access the medium and transfer the networks. Hence, in this paper, adaptive fuzzy C means clustering and seagull optimization algorithm is developed for monitoring environmental conditions in agriculture field. Two main objective functions are utilized to empower the presentation of the WSN such as load balancing and energy efficient operation. The proposed method is a combination of fuzzy C means clustering and seagull optimization algorithm (SOA). The energy efficient and load balancing is achieved by optimal routing scheme by proposed method. The fuzzy C-means clustering is utilized to empower the energy efficient operation and load balancing. In the fuzzy C-means clustering, the SOA is utilized to select the optimal path selection. The proposed method is executed by NS2 simulator and performances are compared with existing methods such as atom search optimization and emperor penguin optimization respectively. The performance metrics are delay, drop, throughput, energy consumption, network lifetime, overhead and delivery ratio.

     

基于动态人工鱼群优化的WSN分簇算法

将群智能优化算法引入无线传感器网络分簇路由协议的设计能有效地节约节点能量和提高分簇效率.针对基本人工鱼群算法在运算速度方面的不足,提出了一种基于动态人工鱼群优化的无线传感器网络分簇算法,算法为了同时具有较好的全局搜索和局部寻优能力,更快地得到最优分簇结果,在一次迭代进化中除了考虑人工鱼的觅食行为、聚群行为和追尾行为的寻...     

Energy efficient watchman based flooding algorithm for IoT-enabled underwater wireless sensor and actor networks

In the task of data routing in Internet of Things enabled volatile underwater environments, providing better transmission and maximizing network communication performance are always challenging. Many network issues such as void holes and network isolation occur because of long routing distances between nodes. Void holes usually occur around the sink because nodes die early due to the high energy consumed to forward packets sent and received from other nodes. These void holes are a major challenge for I-UWSANs and cause high end-to-end delay, data packet loss, and energy consumption. They also affect the data delivery ratio. Hence, this paper presents an energy efficient watchman based flooding algorithm to address void holes. First, the proposed technique is formally verified by the Z-Eves toolbox to ensure its validity and correctness. Second, simulation is used to evaluate the energy consumption, packet loss, packet delivery ratio, and throughput of the network. The results are compared with well-known algorithms like energy-aware scalable reliable and void-hole mitigation routing and angle based flooding. The extensive results show that the proposed algorithm performs better than the benchmark techniques.     

Fuzzy chessboard clustering and artificial bee colony routing method for energy‐efficient heterogeneous wireless sensor networks

Energy is an extremely critical resource for battery‐powered wireless sensor networks (WSNs), thus making energy‐efficient protocol design a key challenging problem. However, uneven energy consumption is an inherent problem in WSNs caused by multi‐hop routing and many‐to‐one traffic pattern among sensors. In this paper, we therefore propose a new clustering method called fuzzy chessboard clustering (FFC), which is capable to overcome the bottleneck problem and addressing the uneven energy consumption problem in heterogeneous WSNs. We also propose an energy‐efficient routing method called artificial bee colony routing method (ABCRM) to find the optimal routing path for the heterogeneous WSNs. ABCRM seeks to investigate the problems of balancing energy consumption and maximization of network lifetime. To demonstrate the effectiveness of FCC‐ABCRM in terms of lessening end‐to‐end delay, balancing energy consumption, and maximization of heterogeneous network lifetime, we compare our method with three approaches namely, chessboard clustering approach, PEGASIS, and LEACH. Simulation results show that the network lifetime achieved by FCC‐ABCRM could be increased by nearly 25%, 45%, and 60% more than that obtained by chessboard clustering, PEGASIS, and LEACH, respectively. Copyright © 2013 John Wiley & Sons, Ltd.