SGDD: self‐managed grid‐based data dissemination protocol for mobile sink in wireless sensor network

The reduction of energy consumption in order to increase network lifetime is one of the most major challenges in the design of wireless sensor networks. During data dissemination, the sensors that are located in the sink's neighborhood are responsible to relay data to the other nodes; hence, their energy is exhausted expeditiously. Therefore, the idea of utilizing mobile sinks can be so advantageous to decrease energy consumption during data dissemination process. In this paper, we propose self‐managed grid‐based data disseminating protocol for mobile sink in wireless sensor networks by using the idea of constructing a virtual grid. In self‐managed grid‐based data disseminating protocol, sink and nodes map their geographical position to a virtual location. In order to increase the performance, we have employed a cell head for each grid cell. Cell heads are selected based on two parameters, centralization and residual energy. Our data dissemination protocol is simple and has low overhead to construct and maintain. Also, we have presented a new method for sink location update, which leads to the least cost in data transfer. Simulation results illustrate that by utilizing hierarchical functionality and determining an optimal size for grid cells, energy consumption is decreased, which leads to increasing network lifetime. Copyright © 2015 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.     

A cluster‐based fault‐tolerant routing protocol for wireless sensor networks

Energy conservation and fault tolerance are two critical issues in the deployment of wireless sensor networks (WSNs). Many cluster‐based fault‐tolerant routing protocols have been proposed for energy conservation and network lifetime maximization in WSNs. However, these protocols suffer from high frequency of re‐clustering as well as extra energy consumption to tolerate failures and consider only some very normal parameters to form clusters without any verification of the energy sufficiency for data routing. Therefore, this paper proposes a cluster‐based fault‐tolerant routing protocol referred as CFTR. This protocol allows higher energy nodes to become Cluster Heads (CHs) and operate multiple rounds to diminish the frequency of re‐clustering. Additionally, for the sake to get better energy efficiency and balancing, we introduce a cost function that considers during cluster formation energy cost from sensor node to CH, energy cost from CH to sink, and another significant parameter, namely, number of cluster members in previous round. Further, the proposed CFTR takes care of nodes, which have no CH in their communication range. Also, it introduces a routing algorithm in which the decision of next hop CH selection is based on a cost function conceived to select routes with sufficient energy for data transfer and distribute uniformly the overall data‐relaying load among the CHs. As well, a low‐overhead algorithm to tolerate the sudden failure of CHs is proposed. We perform extensive simulations on CFTR and compare their results with those of two recent existing protocols to demonstrate its superiority in terms of different metrics.     

Pareto-optimal clustering scheme using data aggregation for wireless sensor networks

The presence of cluster heads (CHs) in a clustered wireless sensor network (WSN) leads to improved data aggregation and enhanced network lifetime. Thus, the selection of appropriate CHs in WSNs is a challenging task, which needs to be addressed. A multicriterion decision-making approach for the selection of CHs is presented using Pareto-optimal theory and technique for order preference by similarity to ideal solution (TOPSIS) methods. CHs are selected using three criteria including energy, cluster density and distance from the sink. The overall network lifetime in this method with 50% data aggregation after simulations is 81% higher than that of distributed hierarchical agglomerative clustering in similar environment and with same set of parameters. Optimum number of clusters is estimated using TOPSIS technique and found to be 9–11 for effective energy usage in WSNs.     

A modified whale-dragonfly algorithm and self-adaptive cuckoo search-based clustering strategy for augmenting network lifetime in wireless sensor networks

Designing an energy efficient and durable wireless sensor networks (WSNs) is a key challenge as it personifies potential and reactive functionalities in harsh antagonistic environment at which wired system deployment is completely infeasible. Majority of the clustering mechanisms contributed to the literature concentrated on augmenting network lifetime and energy stability. However, energy consumption incurred by cluster heads (CHs) are high and thereby results in minimized network lifetime and frequent CHs selection. In this paper, a modified whale-dragonfly optimization algorithm and self-adaptive cuckoo search-based clustering strategy (MWIDOA-SACS) is proposed for sustaining energy stability and augment network lifetime. In specific, MWIDOA-SACS is included for exploiting the fitness values that aids in determining two optimal nodes that are selected as optimal CH and cluster router (CR) nodes in the network. In MWIDOA, the search conduct of dragon flies is completely updated through whale optimization algorithm (WOA) for preventing load balancing at CHs. It minimized the overhead of CH by adopting CHs and CR for collecting information from cluster members and transmitting the aggregated data from CHs to the base station (BS). It included self-adaptive cuckoo search (SACS) for achieving sink mobility using radius, energy stability, received signal strength, and throughput for achieving optimal data transmission process after partitioning the network into unequal clusters. Simulation experiments of the proposed MWIDOA-SACS confirmed better performance in terms of total residual energy by 21.28% and network lifetime by 26.32%, compared to the competitive CH selection strategies.     

Energy efficient clustering algorithms for wireless sensor networks: novel chemical reaction optimization approach

Clustering has been accepted as one of the most efficient techniques for conserving energy of wireless sensor networks (WSNs). However, in a two-tiered cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving data from their member sensor nodes, aggregating them and transmitting that data to the base station (BS). Therefore, proper selection of CHs and optimal formation of clusters play a crucial role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient CH selection and energy balanced cluster formation algorithms, which are based on novel chemical reaction optimization technique (nCRO), we jointly called these algorithms as novel CRO based energy efficient clustering algorithms (nCRO-ECA). These algorithms are developed with efficient schemes of molecular structure encoding and potential energy functions. For the energy efficiency, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes in the CH selection phase. In the cluster formation phase, we consider various distance and energy parameters. The algorithm is tested extensively on various scenarios of WSNs by varying number of sensor nodes and CHs. The results are compared with original CRO based algorithm, namely CRO-ECA and some existing algorithms to demonstrate the superiority of the proposed algorithm in terms of energy consumption, network lifetime, packets received by the BS and convergence rate.     

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.     

A boolean spider monkey optimization based energy efficient clustering approach for WSNs

Wireless sensor network (WSN) consists of densely distributed nodes that are deployed to observe and react to events within the sensor field. In WSNs, energy management and network lifetime optimization are major issues in the designing of cluster-based routing protocols. Clustering is an efficient data gathering technique that effectively reduces the energy consumption by organizing nodes into groups. However, in clustering protocols, cluster heads (CHs) bear additional load for coordinating various activities within the cluster. Improper selection of CHs causes increased energy consumption and also degrades the performance of WSN. Therefore, proper CH selection and their load balancing using efficient routing protocol is a critical aspect for long run operation of WSN. Clustering a network with proper load balancing is an NP-hard problem. To solve such problems having vast search area, optimization algorithm is the preeminent possible solution. Spider monkey optimization (SMO) is a relatively new nature inspired evolutionary algorithm based on the foraging behaviour of spider monkeys. It has proved its worth for benchmark functions optimization and antenna design problems. In this paper, SMO based threshold-sensitive energy-efficient clustering protocol is proposed to prolong network lifetime with an intend to extend the stability period of the network. Dual-hop communication between CHs and BS is utilized to achieve load balancing of distant CHs and energy minimization. The results demonstrate that the proposed protocol significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.     

A Sink-Oriented Layered Clustering Protocol for Wireless Sensor Networks

Clustering is an effective technique to prolong network lifetime for energy-constrained wireless sensor networks. Due to the many-to-one traffic pattern in a multi-hop network, the nodes closer to the sink also help to relay data for those farther away from the sink, and hence they consume much more energy and tend to die faster. This paper proposes a sink-oriented layered clustering (SOLC) protocol to better balance energy consumption among nodes with different distances to the sink. In SOLC, the sensor field is divided into concentric rings, and the SOLC protocol consists of intra-ring clustering and inter-ring routing. We compute the optimal ring width and the numbers of cluster heads in different rings to balance energy consumption between intra-cluster data processing and inter-cluster data relaying. Cluster heads in a ring closer to the sink has smaller sizes than those in the rings farther away from the sink, and hence they can spend less energy for intra-cluster data processing and more energy for inter-cluster data relay. Simulation results show that the SOLC protocol can outperform several existing clustering protocols in terms of improved network lifetime.     

Novel chemical reaction optimization based unequal clustering and routing algorithms for wireless sensor networks

Energy conserving of sensor nodes is the most crucial issue in the design of wireless sensor networks (WSNs). In a cluster based routing approach, cluster heads (CHs) cooperate with each other to forward their data to the base station (BS) via multi-hop routing. In this process, CHs closer to the BS are burdened with heavier relay traffic and tend to die prematurely which causes network partition is popularly known as a hot spot problem. To mitigate the hot spot problem, in this paper, we propose unequal clustering and routing algorithms based on novel chemical reaction optimization (nCRO) paradigm, we jointly call these algorithms as novel CRO based unequal clustering and routing algorithms (nCRO-UCRA). In clustering, we partition the network into unequal clusters such that smaller size clusters near to the sink and larger size clusters relatively far away from the sink. For this purpose, we develop the CH selection algorithm based on nCRO paradigm and assign the non-cluster head sensor nodes to the CHs based on derived cost function. Then, a routing algorithm is presented which is also based on nCRO based approach. All these algorithms are developed with the efficient schemes of molecular structure encoding and novel potential energy functions. The nCRO-UCRA is simulated extensively on various scenarios of WSNs and varying number of sensors and the CHs. The results are compared with some existing algorithms and original CRO based algorithm called as CRO-UCRA to show the superiority in terms of various performance metrics like residual energy, network lifetime, number of alive nodes, data packets received by the BS and convergence rate.     

基于移动Agent和WSN的突发事件场景数据收集算法研究

该文针对无线传感器网络应用于突发事件监测场景的能量消耗和网络延迟问题,提出了基于移动Agent的无线传感器网络簇式数据收集算法.动态成簇过程基于事件严重程度,并由其决定簇的生命周期和覆盖范围.Sink和簇头之间形成以Sink节点为簇头的虚拟簇.移动Agent迁移路径规划过程中下一跳节点的选取基于节点剩余能量、路径损耗及受刺激强度.移动Agent通过节点遍历的方式完成对所有簇内成员节点信息的收集.仿真结果表明,相对于C/S数据收集模型,基于移动Agent的模型具有更好的节能效果,并能一定程度地减少网络延迟,尤其适用于大规模无线传感器网络应用.     

Energy Efficient Layered Cluster Head Rotation Based Routing Protocol for Underwater Wireless Sensor Networks

Energy efficiency is of paramount concern in underwater sensor networks. The very nature of underwater environment makes it difficult to deploy an energy efficient network that enhances network lifetime. The existing protocols of terrestrial networks cannot be implemented directly to underwater scenarios and as such new protocols have to be designed because of speed of signal propagation under water. Improving the energy efficiency in UWSNs is an active area of research and many protocols to that end have been proposed. The routing protocol that this paper proposes is Energy Efficient Layered Cluster Head Rotation (EE-LCHR) routing protocol. This protocol makes use of the multi sink architecture and creates virtual layers containing a number of sensor nodes such that the hop count from the sensor nodes in a particular layer to the surface sink is the same. Also each layer has a number of clusters with a cluster head that keeps on rotating depending on the fitness value of the sensor nodes. The proposed protocol as compared to other extant protocols like EE-DBR and DBR improves network lifetime. The presence of virtual layers and rotation of cluster heads together ensure that energy balance is better achieved in our proposed protocol which leads to an enhanced network lifetime.

     

A grid based clustering and routing algorithm for solving hot spot problem in wireless sensor networks

Energy conservation of the sensor nodes is the most important issue that has been studied extensively in the design of wireless sensor networks (WSNs). In many applications, the nodes closer to the sink are overburdened with huge traffic load as the data from the entire region are forwarded through them to reach the sink. As a result, their energy gets exhausted quickly and the network is partitioned. This is commonly known as hot spot problem. Moreover, sensor nodes are prone to failure due to several factors such as environmental hazards, battery exhaustion, hardware damage and so on. However, failure of cluster heads (CHs) in a two tire WSN is more perilous. Therefore, apart from energy efficiency, any clustering or routing algorithm has to cope with fault tolerance of CHs. In this paper, we address the hot spot problem and propose grid based clustering and routing algorithms, combinedly called GFTCRA (grid based fault tolerant clustering and routing algorithms) which takes care the failure of the CHs. The algorithms follow distributed approach. We also present a distributed run time management for all member sensor nodes of any cluster in case of failure of their CHs. The routing algorithm is also shown to tolerate the sudden failure of the CHs. The algorithms are tested through simulation with various scenarios of WSN and the simulation results show that the proposed method performs better than two other grid based algorithms in terms of network lifetime, energy consumption and number of dead sensor nodes.     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

无线传感器网络中移动sink节点的路径规划

在无线传感器网络中,大量感知数据汇集到sink节点的采集方法会导致sink节点附近的节点能量耗尽,造成能量空洞。针对该问题,利用移动的sink节点进行数据收集是一种解决方法,其中移动sink的路径规划成为一个重要的问题。提出了一个移动sink路径规划算法,将无线传感器中随机分布的节点划分为不同的子区域,寻找sink节点移动的最佳转向点,最终得到最优的移动路径,以实现无线传感器网络生命周期最大化。仿真实验表明,与现有方案相比,该算法能显著延长网络的生命周期。     

A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks

Clustering has been proven to be one of the most efficient techniques for saving energy of wireless sensor networks (WSNs). However, in a hierarchical cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving and aggregating the data from their member sensor nodes and transmitting the aggregated data to the base station. Therefore, the proper selection of CHs plays vital role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient cluster head selection algorithm which is based on particle swarm optimization (PSO) called PSO-ECHS. The algorithm is developed with an efficient scheme of particle encoding and fitness function. For the energy efficiency of the proposed PSO approach, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes. We also present cluster formation in which non-cluster head sensor nodes join their CHs based on derived weight function. The algorithm is tested extensively on various scenarios of WSNs, varying number of sensor nodes and the CHs. The results are compared with some existing algorithms to demonstrate the superiority of the proposed algorithm.     

无线传感网络中基于蚁群的路由算法

In the wireless sensor networks, high efficient data routing for the limited energy resource networks is an important issue. By introducing Ant-colony algorithm, this paper proposes the wireless sensor network routing algorithm based on LEACH. During the construction of sensor network clusters, to avoid the node premature death because of the energy consumption, only the nodes whose residual energy is higher than the average energy can be chosen as the cluster heads. The method of repeated division is used to divide the clusters in sensor networks so that the numbers of the nodes in each cluster are balanced. The basic thought of ant-colony algorithm is adopted to realize the data routing between the cluster heads and sink nodes, and the maintenance of routing. The analysis and simulation showed that the proposed routing protocol not only can reduce the energy consumption, balance the energy consumption between nodes, but also prolong the network lifetime.     

Fuzzy-based unequal clustering protocol for underwater wireless sensor networks

Underwater wireless sensor network (UWSN) is a network made up of underwater sensor nodes, anchor nodes, surface sink nodes or surface stations, and the offshore sink node. Energy consumption, limited bandwidth, propagation delay, high bit error rate, stability, scalability, and network lifetime are the key challenges related to underwater wireless sensor networks. Clustering is used to mitigate these issues. In this work, fuzzy-based unequal clustering protocol (FBUCP) is proposed that does cluster head selection using fuzzy logic as it can deal with the uncertainties of the harsh atmosphere in the water. Cluster heads are selected using linguistic input variables like distance to the surface sink node, residual energy, and node density and linguistic output variables like cluster head advertisement radius and rank of underwater sensor nodes. Unequal clustering is used to have an unequal size of the cluster which deals with the problem of excess energy usage of the underwater sensor nodes near the surface sink node, called the hot spot problem. Data gathered by the cluster heads are transmitted to the surface sink node using neighboring cluster heads in the direction of the surface sink node. Dijkstra's shortest path algorithm is used for multi-hop and inter-cluster routing. The FBUCP is compared with the LEACH-UWSN, CDBR, and FBCA protocols for underwater wireless sensor networks. A comparative analysis shows that in first node dies, the FBUCP is up to 80% better, has 64.86% more network lifetime, has 91% more number of packets transmitted to the surface sink node, and is up to 58.81% more energy efficient than LEACH-UWSN, CDBR, and FBCA.     

Modulated relay based stable election protocol for large-scale wireless sensor networks

Internet of things (IoT) applications based on wireless sensor networks (WSNs) have recently gained vast momentum. These applications vary from health care, smart cities, and military applications to environmental monitoring and disaster prevention. As a result, energy consumption and network lifetime have become the most critical research area of WSNs. Through energy-efficient routing protocols, it is possible to reduce energy consumption and extend the network lifetime for WSNs. Using hybrid routing protocols that incorporate multiple transmission methods is an effective way to improve network performance. This paper proposes modulated R-SEP (MR-SEP) for large-scale WSN-based IoT applications. MR-SEP is based on the well-known stable election protocol (SEP). MR-SEP defines three initial energy levels for the nodes to improve the network energy distribution and establishes multi-hop communication between the cluster heads (CHs) and the base station (BS) through relay nodes (RNs) to reduce the energy consumption of the nodes to reach the BS. In addition, MR-SEP reduces the replacement frequency of CHs, which helps increase network lifetime and decrease power consumption. Simulation results show that MR-SEP outperforms SEP, LEACH, and DEEC protocols by 70.2%, 71.58%, and 74.3%, respectively, in terms of lifetime and by 86.53%, 86.68%, and 86.93% in terms of throughput.