Joint load balanced stable routing and communication segment assignment in mobile cognitive radio ad‐hoc networks

The fundamental issues in mobile cognitive radio ad‐hoc networks are the selection of the optimal stable paths between nodes and proper assignment of the frequency channels/time slots (communication segments) to the links. In this paper, a joint load balanced stable routing and communication segment assignment algorithm is proposed that considers jointly the mobility prediction, mitigating the co‐channel interference and energy consumption. The novelty of the proposed algorithm lies in the increasing of the path stability, which benefits from the maximum link lifetime parameter and introduced weighting function to keep routes away from the PU's region. This avoids the negative impacts on the PUs' operations and decreases the conflict of the cognitive nodes. In the proposed algorithm, the concept of load balancing is considered that yields in the balancing energy consumption in the network, improving the network performance and distributing traffic loads on all available channels. The effectiveness of the proposed algorithm is verified by evaluating the aggregate interference energy, average end‐to‐end delay, goodput, and the energy usage per packet under 6 scenarios. The results show that the performance of the proposed algorithm is significantly better than the recently proposed joint stable routing and channel assignment protocol.     

Energy efficiency of virtual multi‐input,multi‐output based on sensor selection in wireless sensor networks

In this paper, a weighted node selection technique in wireless sensor networks is proposed. It is an energy‐efficient cooperative technique where a selected number of sensors at the transmitting end are connected with a selected number of sensors at the receiving end to form a virtual multi‐input multi‐output. The proposed technique is based on a weighted selection function that combines geographical location, inter‐sensor distance in a cluster, channel estimate energy, power circuit, channel loss, mobility factor, and residual energy of each sensor. The weight of each of these parameters in the selection function depends on the degree that this parameter affects the energy consumption. Then, the cluster head selects the sensors with better selection parameters that reduce the overall energy consumption. The numerical results show that the proposed weighted node selection technique achieves a significant improvement in the energy consumption, delay, and network lifetime than the conventional techniques with and without the selected number of sensors. Its improvement reaches 15% in the energy consumption that leads to an increase in the network lifetime by four times the network lifetime of other techniques. Copyright © 2012 John Wiley & Sons, Ltd.     

Distributed simultaneous wireless information and power transfer in multiuser amplify‐and‐forward ad hoc wireless networks

This paper studies the problem of stable node matching for distributed simultaneous wireless information and power transfer in multiuser amplify‐and‐forward ad hoc wireless networks. Particularly, each source node aims to be paired with another node that takes the role of an amplify‐and‐forward relay to forward its signal to the destination, such that the achievable rate is improved, in return of some payment made to the relaying node. Each relaying node splits its received signal from its respective source into two parts: one for information processing and the other for energy harvesting. In turn, a matching‐theoretic solution based on the one‐to‐one stable marriage matching game is studied, and a distributed polynomial‐time complexity algorithm is proposed to pair each source node with its best potential relaying node based on the power‐splitting ratios, such that their utilities or payments are maximized while achieving network stability. For comparison purposes, an algorithm to enumerate all possible stable matchings is also devised to study the impact of different matchings on the source and relay utilities. Simulation results are presented to validate the proposed matching algorithm and illustrate that it yields sum‐utility and sum‐payment that are closely comparable to those of centralized power allocation and node pairing, with the added merits of low complexity, truth telling, and network stability.     

PFARS: Enhancing throughput and lifetime of heterogeneous WSNs through power‐aware fusion,aggregation, and routing scheme

Heterogeneous wireless sensor networks (WSNs) consist of resource‐starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy‐efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application‐specific or too complex that make their implementation unrealistic, specifically, in a resource‐constrained environment. In this paper, we propose a novel node‐level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in‐network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real‐time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay.     

A novel energy‐aware routing mechanism for SDN‐enabled WSAN

Energy consumption is one of the most important design constraints when building a wireless sensor and actuator network since each device in the network has a limited battery capacity, and prolonging the lifetime of the network depends on saving energy. Overcoming this challenge requires a smart and reconfigurable network energy management strategy. The Software‐Defined Networking (SDN) paradigm aims at building a flexible and dynamic network structure, especially in wireless sensor networks. In this study, we propose an SDN‐enabled wireless sensor and actuator network architecture that has a new routing discovery mechanism. To build a flexible and energy‐efficient network structure, a new routing decision approach that uses a fuzzy‐based Dijkstra's algorithm is developed in the study. The proposed architecture can change the existing path during data transmission, which is the key property of our model and is achieved through the adoption of the SDN approach. All the components and algorithms of the proposed system are modeled and simulated using the Riverbed Modeler software for more realistic performance evaluation. The results indicate that the proposed SDN‐enabled structure with fuzzy‐based Dijkstra's algorithm outperforms the one using the regular Dijkstra's and the ZigBee‐based counterpart, in terms of the energy consumption ratio, and the proposed architecture can provide an effective cluster routing while prolonging the network lifetime.     

Energy‐Connectivity Tradeoff through Topology Control in Wireless Ad Hoc Networks

In this study, we investigate topology control as a means of obtaining the best possible compromise between the conflicting requirements of reducing energy consumption and improving network connectivity. A topology design algorithm capable of producing network topologies that minimize energy consumption under a minimum‐connectivity constraint is presented. To this end, we define a new topology metric, called connectivity efficiency, which is a function of both algebraic connectivity and the transmit power level. Based on this metric, links that require a high transmit power but only contribute to a small fraction of the network connectivity are chosen to be removed. A connectivity‐efficiency‐based topology control (CETC) algorithm then assigns a transmit power level to each node. The network topology derived by the proposed CETC heuristic algorithm is shown to attain a better tradeoff between energy consumption and network connectivity than existing algorithms. Simulation results demonstrate the efficiency of the CECT algorithm.     

Multi‐cost routing for energy and capacity constrained wireless mesh networks

We propose a class of novel energy‐efficient multi‐cost routing algorithms for wireless mesh networks, and evaluate their performance. In multi‐cost routing, a vector of cost parameters is assigned to each network link, from which the cost vectors of candidate paths are calculated using appropriate operators. In the end these parameters are combined in various optimization functions, corresponding to different routing algorithms, for selecting the optimal path. We evaluate the performance of the proposed energy‐aware multi‐cost routing algorithms under two models. In the network evacuation model, the network starts with a number of packets that have to be transmitted and an amount of energy per node, and the objective is to serve the packets in the smallest number of steps, or serve as many packets as possible before the energy is depleted. In the dynamic one‐to‐one communication model, new data packets are generated continuously and nodes are capable of recharging their energy periodically, over an infinite time horizon, and we are interested in the maximum achievable steady‐state throughput, the packet delay, and the energy consumption. Our results show that energy‐aware multi‐cost routing increases the lifetime of the network and achieves better overall network performance than other approaches. Copyright © 2011 John Wiley & Sons, Ltd.     

Flower pollination algorithm‐based energy‐efficient stable clustering approach for WSNs

The advances in the size, cost of deployment, and user‐friendly interface of wireless sensor devices have given rise to many wireless sensor network (WSN) applications. WSNs need to use protocols for transmitting data samples from event regions to sink through minimum cost links. Clustering is a commonly used method of data aggregation in which nodes are organized into groups to reduce energy consumption. Nonetheless, cluster head (CH) has to bear an additional load in clustering protocols to organize different activities within the cluster. Proper CH selection and load balancing using efficient routing protocol is therefore a critical aspect for WSN's long‐term operation. In this paper, a threshold‐sensitive energy‐efficient cluster‐based routing protocol based on flower pollination algorithm (FPA) is proposed to extend the network's stability period. Using FPA, multihop communication between CHs and base station is used to achieve optimal link costs for load balancing distant CHs and energy minimization. Analysis and simulation results show that the proposed algorithm significantly outperforms competitive clustering algorithms in terms of energy consumption, stability period, and system lifetime.     

Cluster‐based coordination scheme for cooperative cognitive radio networks

In this paper, a cluster‐based two‐phase coordination scheme for cooperative cognitive radio networks is proposed considering both spectrum efficiency and network fairness. Specifically, candidate secondary users (SUs) are first selected by a partner selection algorithm to enter the two‐phase cooperation with primary users (PUs). In phase I, the selected SUs cooperate with PUs to acquire a fraction of time slot as a reward. In phase II, all SUs including the unselected ones share the available spectrum resources in local clusters; each of which is managed by a cluster head who participated in the cooperation in phase I. To improve the total network utility of both PUs and SUs, the maximum weighted bipartite matching is adopted in partner selection. To further improve the network performance and communication reliability, network coding is exploited during the spectrum sharing within the cluster. Simulation results demonstrate that, with the proposed cluster‐based coordination scheme, not only the PUs' transmission performance is improved, but also SUs achieve spectrum access opportunities. Copyright © 2015 John Wiley & Sons, Ltd.     

Energy‐efficient multiple‐domain bidirectional scheme for G.hn applications

This paper presents an energy‐efficient relaying scheme for G.hn standard. We propose a multi‐domain bidirectional communication network with network coding at the physical layer in order to increase network coverage. The logical link control stack was also modified and supplemented with additional functionality. This reduces the power consumption in the network and enhances the performance while reducing collisions for inter‐domain network access. We consider domain selection to minimize the total energy consumption of the network and present optimal power allocation for the given QoS of each end node. Energy efficiency is evaluated in terms of transmit energy per bit for relay networks with bidirectional symmetric and asymmetric traffic flows. Simulation results show that the proposed multi‐domain bidirectional communication provides improved performance and higher energy savings than the single‐domain unidirectional network, especially in powerline communication channel, which is the worst medium of the three G.hn media. Finally, it was demonstrated that improved energy efficiency can be achieved with appropriate domain selection. Copyright © 2015 John Wiley & Sons, Ltd.     

DUCR: Distributed unequal cluster‐based routing algorithm for heterogeneous wireless sensor networks

Designing energy efficient communication protocols for wireless sensor networks (WSNs) to conserve the sensors' energy is one of the prime concerns. Clustering in WSNs significantly reduces the energy consumption in which the nodes are organized in clusters, each having a cluster head (CH). The CHs collect data from their cluster members and transmit it to the base station via a single or multihop communication. The main issue in such mechanism is how to associate the nodes to CHs and how to route the data of CHs so that the overall load on CHs are balanced. Since the sensor nodes operate autonomously, the methods designed for WSNs should be of distributed nature, i.e., each node should run it using its local information only. Considering these issues, we propose a distributed multiobjective‐based clustering method to assign a sensor node to appropriate CH so that the load is balanced. We also propose an energy‐efficient routing algorithm to balance the relay load among the CHs. In case any CH dies, we propose a recovery strategy for its cluster members. All our proposed methods are completely distributed in nature. Simulation results demonstrate the efficiency of the proposed algorithm in terms of energy consumption and hence prolonging the network lifetime. We compare the performance of the proposed algorithm with some existing algorithms in terms of number of alive nodes, network lifetime, energy efficiency, and energy population.     

Design of logical topology with K‐connected constraints and channel assignment for multi‐radio wireless mesh networks

In multi‐radio multi‐channel wireless mesh networks, the design of logical topology is different from that in single channel wireless mesh networks. The same channel assignment algorithm used for various logical topologies will lead to diverse network performance. In this paper, we study the relationship between k ‐connected logical topology and the maximum number of assigned channels. Meanwhile, we analyze the issues affecting channel assignment performance, and present the lower and upper bounds of the maximum allowable number of assigned channels for k ‐connected logical topology. We then develop a k ‐connected logical topology design algorithm based on shortest disjoint paths and minimum interference disjoint paths for each node‐pair. In addition, we propose a static channel assignment algorithm according to minimum spanning tree search. Extensive simulations show that our proposed algorithm achieves higher throughput and lower end‐to‐end delay than fault tolerant topology control algorithms, which validates the involved trade‐off between path length and nodal interference. Moreover, numerical results demonstrate that our proposed channel assignment further improves network performance under the context of limited radio interfaces. Copyright © 2014 John Wiley & Sons, Ltd.     

Load‐balanced data gathering in Internet of Things using an energy‐aware cuckoo‐search algorithm

This paper deals with the lifetime problem in the Internet of Things. We first propose an efficient cluster‐based scheme named “Cuckoo‐search Clustering with Two‐hop Routing Tree (CC‐TRT)” to develop a two‐hop load‐balanced data aggregation routing tree in the network. CC‐TRT uses a modified energy‐aware cuckoo‐search algorithm to fairly select the best cluster head (CH) for each cluster. The applied cuckoo‐search algorithm makes the CH role to rotate between different sensors round by round. Subsequently, we extend the CC‐TRT scheme to present two methods for constructing multi‐hop data aggregation routing trees, named “Cuckoo‐search Clustering with Multi‐Hop Routing Tree (CC‐MRT)” and “Cuckoo‐search Clustering with Weighted Multi‐hop Routing Tree (CC‐WMRT).” Both CC‐MRT and CC‐WMRT rely on a two‐level structure; they not only use an energy‐aware cuckoo‐search algorithm to fairly select the best CHs but also adopt a load‐balanced high‐level routing tree to route the aggregated data of CHs to the sink node. However, CC‐WMRT slightly has a better performance thanks to its low‐level routing strategy. As an advantage, the proposed schemes balance the energy consumption among different sensors. Numerical results show the efficiency of the CC‐TRT, CC‐MRT, and CC‐WMRT algorithms in terms of the number of transmissions, remaining energy, energy consumption variance, and network lifetime.     

A Genetic‐Algorithm‐Based Optimized Clustering for Energy‐Efficient Routing in MWSN

With the increasing demands for mobile wireless sensor networks in recent years, designing an energy‐efficient clustering and routing protocol has become very important. This paper provides an analytical model to evaluate the power consumption of a mobile sensor node. Based on this, a clustering algorithm is designed to optimize the energy efficiency during cluster head formation. A genetic algorithm technique is employed to find the near‐optimal threshold for residual energy below which a node has to give up its role of being the cluster head. This clustering algorithm along with a hybrid routing concept is applied as the near‐optimal energy‐efficient routing technique to increase the overall efficiency of the network. Compared to the mobile low energy adaptive clustering hierarchy protocol, the simulation studies reveal that the energy‐efficient routing technique produces a longer network lifetime and achieves better energy efficiency.     

Distance and clustering‐based energy‐efficient pseudonyms changing strategy over road network

To improve the fairness, the energy consumption changing pseudonyms needs to be taken into account. Existing works focus on changing velocity‐based pseudonyms changing strategy and short changes interval with limited coverage, but due to similar velocity and short changes, internal attacker guesses easily known communication and location information due to location information of vehicle on tracking, which may expose adversary private information, and frequently, pseudonyms changing occurs due to movement of vehicles' similar velocity and short coverage, which may cause serious attack of vehicle. To overcome this problem, distance and cluster can be performed. In this work, we proposed distance and cluster‐based energy pseudonyms changing method for road network. We proposed distance and energy‐based clustering routing service over road network, the cluster head elected to depend on random number of distance and energy to change pseudonyms of vehicles. An each interval to be establish cluster head vehicle deployed while selects the operation mode and informs the cluster members of the selected mode through beacon signal. The cluster head vehicle node performs the pseudonyms changing based on the predicted distance and energy of the cluster member to use clustering optimization. The data of whole network send to report server through these nodes while near the RSU, and the vehicles in this area will use less energy to change the pseudonyms. The simulation results show that the proposed method enhances pseudonyms changing strategy less consumption and delays sufficient privacy level each vehicle also our method has outperform compare with existing methods than we use Sumo simulation and Matlab tools to verify our proposed method. Our proposed method outperformed in terms of pseudonym changing energy efficiency to careful attention during the cluster formation process, stable and balanced clusters that prolong the network lifetime, increases distances to more CH vehicles connectivity to makes clustering group and changing their pseudonyms in terms of high level privacy and finally, CH nodes use Dijkstra's algorithm use MST among the vehicles nodes depend on existing road networks to follow shortest path selection roads in terms of high connectivity probability of CH and stable structure of the network decreases the topology changes and thus,the clustering overhead is reduced.     

Achieving energy‐neutral data transmission by adjusting transmission power for energy‐harvesting wireless sensor networks

Recently, benefiting from rapid development of energy harvesting technologies, the research trend of wireless sensor networks has shifted from the battery‐powered network to the one that can harvest energy from ambient environments. In such networks, a proper use of harvested energy poses plenty of challenges caused by numerous influence factors and complex application environments. Although numerous works have been based on the energy status of sensor nodes, no work refers to the issue of minimizing the overall data transmission cost by adjusting transmission power of nodes in energy‐harvesting wireless sensor networks. In this paper, we consider the optimization problem of deriving the energy‐neutral minimum cost paths between the source nodes and the sink node. By introducing the concept of energy‐neutral operation, we first propose a polynomial‐time optimal algorithm for finding the optimal path from a single source to the sink by adjusting the transmission powers. Based on the work earlier, another polynomial‐time algorithm is further proposed for finding the approximated optimal paths from multiple sources to the sink node. Also, we analyze the network capacity and present a near‐optimal algorithm based on the Ford–Fulkerson algorithm for approaching the maximum flow in the given network. We have validated our algorithms by various numerical results in terms of path capacity, least energy of nodes, energy ratio, and path cost. Simulation results show that the proposed algorithms achieve significant performance enhancements over existing schemes. Copyright © 2016 John Wiley & Sons, Ltd.     

FUCA: Fuzzy‐based unequal clustering algorithm to prolong the lifetime of wireless sensor networks

Wireless sensor network comprises billions of nodes that work collaboratively, gather data, and transmit to the sink. “Energy hole” or “hotspot” problem is a phenomenon in which nodes near to the sink die prematurely, which causes the network partition. This is because of the imbalance of the consumption of energy by the nodes in wireless sensor networks. This decreases the network's lifetime. Unequal clustering is a technique to cope up with this issue. In this paper, an algorithm, “fuzzy‐based unequal clustering algorithm,” is proposed to prolong the lifetime of the network. This protocol forms unequal clusters. This is to balance the energy consumption. Cluster head selection is done through fuzzy logic approach. Input variables are the distance to base station, residual energy, and density. Competition radius and rank are the two output fuzzy variables. Mamdani method is employed for fuzzy inference. The protocol is compared with well‐known algorithms, like low‐energy adaptive clustering hierarchy, energy‐aware unequal clustering fuzzy, multi‐objective fuzzy clustering algorithm, and fuzzy‐based unequal clustering under different network scenarios. In all the scenarios, the proposed protocol performs better. It extends the lifetime of the network as compared with its counterparts.     

Green optical backbone networks: virtual topology adaptation using a page rank‐based rating system

An energy‐aware virtual topology rating system is proposed in this work, which can be utilized as a tool during the virtual topology reconfiguration procedure in an optical backbone network in order to reduce its energy consumption. It is well known that maintaining a static virtual topology in Internet Protocol (IP)‐over‐Wavelength Division Multiplexing (WDM) networks is not energy‐efficient. To that end, virtual topology adaptation algorithms have been developed to adjust the virtual topology to the constantly fluctuating traffic load. While these algorithms achieve significant energy savings, further reduction on the total network energy consumption can be achieved through the proposed rating system. The proposed rating system is a modified version of the page rank algorithm, which ranks websites in the Internet based on their importance. The proposed rating system attributes ratings to lightpaths, which indicate the relative significance of a lightpath in the virtual topology in terms of energy consumption. The rating can be used during the routing procedure as an energy efficiency indicator, in order to increase the number of lightpaths that are deactivated from the reconfiguration mechanism and increase the utilization per lightpath. The proposed reconfiguration scheme (page rank‐based virtual topology reconfiguration) achieves up to 12% additional energy savings in comparison to an existing virtual topology reconfiguration algorithm at the cost of slightly increased average hop distance. Copyright © 2015 John Wiley & Sons, Ltd.     

Meta‐heuristic algorithms for channel scheduling problem in wireless sensor networks

The channel scheduling problem is to decide how to commit channels for transmitting data between nodes in wireless networks. This problem is one of the most important problems in wireless sensor networks. In this problem, we aim to obtain a near‐optimal solution with the minimal energy consumption within a reasonable time. As the number of nodes increases in the network, however, the amount of calculation for finding the solution would be too high. It can be difficult to obtain an optimal solution in a reasonable execution time because this problem is NP‐hard. Therefore, most of the recent studies for such problems seem to focus on heuristic algorithms. In this paper, we propose efficient channel scheduling algorithms to obtain a near‐optimal solution on the basis of three meta‐heuristic algorithms; the genetic algorithm, the Tabu search, and the simulated annealing. In order to make a search more efficient, we propose some neighborhood generating methods for the proposed algorithms. We evaluate the performance of the proposed algorithms through some experiments in terms of energy consumption and algorithm execution time. The experimental results show that the proposed algorithms are efficient for solving the channel scheduling problem in wireless sensor networks. Copyright © 2011 John Wiley & Sons, Ltd.     

基于多目标生物习性激励的WSN传感器节点部署

为确保无线传感器网络(WSN)覆盖和连通性最大化以及能量消耗最小化的有效监测,提出一种基于多目标生物习性激励(MOBHI)的传感器节点部署算法。首先,将传感器节点的区域(领地)根据诸如最大覆盖、最大连通性和最小能耗等多个目标,基于领地捕食者气味标记行为进行标记,并模仿气味匹配识别其监测的位置;其次,对多个目标的优化问题应用非受控Pareto最优,将其分解为多个单目标优化子问题并同时对它们进行优化,得到所需目标的解。仿真实验结果表明,本文提出算法在网络覆盖、连通性和能耗等性能指标方面都优于其他传感器节点部署的多目标和单目标优化算法。