A Coverage-Based Scheduling Algorithm for WSNs

Node scheduling in wireless sensor networks (WSNs) plays a vital role in conserving energy and lengthening the lifetime of networks, which are considered as prime design challenges. In large-scaled WSNs, especially where sensor nodes are deployed randomly, 100 % coverage is not possible all the times. Additionally, several types of applications of WSNs do not require 100 % coverage. Following these facts, in this paper, we propose a coverage based node scheduling algorithm. The algorithm shows that by sacrificing a little amount of coverage, a huge amount of energy can be saved. This, in turns, helps to increase the lifetime of the network. We provide mathematical analysis, which verifies the correctness of the proposed algorithm. The proposed algorithm ensures balanced energy consumption over the sensor networks. Moreover, simulation results demonstrate that the proposed algorithm almost doubles the lifetime of a wireless sensor network by sacrificing only 5–8 % of coverage.     

基于感知数据分析的传感器网络覆盖控制

提出“决策覆盖”的覆盖控制理论和方法.以保证有效覆盖度为目标,通过对传感器网络局部感知数据的实时分析,计算节点的工作优先级并且动态地调整局部物理覆盖度,实现节点状态的反馈调度.“决策覆盖”克服了现有覆盖控制在灵活性和适应性方面的缺陷,突破了在节点发生故障和网络遭受攻击后服务质量难以保证的瓶颈.结合传统的覆盖区域计算及概率分析的结论,本文对现有覆盖控制算法进行了改进,相对于原始算法,改进后的算法在覆盖有效性和健壮性上均有明显提升.     

移动WSNs中一种覆盖空洞的修复算法

基于无线传感网络的应用依赖于节点对监测区域的可靠覆盖.由于能耗殆尽或故障,节点感测能力可能失效,形成覆盖空洞区域.为此,提出基于模糊推理系统(FIS)的修复节点选取(FISS)算法.FISS算法采用自适应感测半径调整策略,利用节点的移动修复覆盖空洞.将节点的剩余能量和覆盖重叠率作为FIS的输入,并由FIS估计节点成为修...     

An energy efficient hole repair node scheduling algorithm for WSN

A sensor node in the wireless sensor network has limited energy and it normally cannot be replaced due to the random deployment, so how to prolong the network life time with limited energy while satisfying the coverage quality simultaneously becomes a crucial problem to solve for wireless sensor networks (WSN). In this work, we propose an energy efficient algorithm based on the sentinel scheme to reduce the sleeping node detection density by defining a new deep sleeping state for each sensor node. The average energy consumed by probing neighboring nodes is introduced as a factor to calculate the detection rate. In addition, after some theoretical analysis of the existence of coverage holes in WSN, a triangle coverage repair procedure is defined to repair coverage holes. Simulation results show that our proposed algorithm obtained better performance in terms of the coverage quality and network life time compared with some existing algorithms in the literature.     

Secure coverage-preserving node scheduling scheme using energy prediction for wireless sensor networks

With the fast development of the micro-electro-mechanical systems(MEMS),wireless sensor networks(WSNs)have been extensively studied.Most of the studies focus on saving energy consumption because of restricted energy supply in WSNs.Cluster-based node scheduling scheme is commonly considered as one of the most energy-efficient approaches.However,it is not always so efficient especially when there exist hot spot and network attacks in WSNs.In this article,a secure coverage-preserved node scheduling scheme for WSNs based on energy prediction is proposed in an uneven deployment environment.The scheme is comprised of an uneven clustering algorithm based on arithmetic progression,a cover set partition algorithm based on trust and a node scheduling algorithm based on energy prediction.Simulation results show that network lifetime of the scheme is 350 rounds longer than that of other scheduling algorithms.Furthermore,the scheme can keep a high network coverage ratio during the network lifetime and achieve the designed objective which makes energy dissipation of most nodes in WSNs balanced.     

Distributed fuzzy logic based energy‐aware and coverage preserving unequal clustering algorithm for wireless sensor networks

In an energy‐constrained wireless sensor networks (WSNs), clustering is found to be an effective strategy to minimize the energy depletion of sensor nodes. In clustered WSNs, network is partitioned into set of clusters, each having a coordinator called cluster head (CH), which collects data from its cluster members and forwards it to the base station (BS) via other CHs. Clustered WSNs often suffer from the hot spot problem where CHs closer to the BS die much early because of high energy consumption contributed by the data forwarding load. Such death of nodes results coverage holes in the network very early. In most applications of WSNs, coverage preservation of the target area is a primary measure of quality of service. Considering the energy limitation of sensors, most of the clustering algorithms designed for WSNs focus on energy efficiency while ignoring the coverage requirement. In this paper, we propose a distributed clustering algorithm that uses fuzzy logic to establish a trade‐off between the energy efficiency and coverage requirement. This algorithm considers both energy and coverage parameters during cluster formation to maximize the coverage preservation of target area. Further, to deal with hot spot problem, it forms unequal sized clusters such that more CHs are available closer to BS to share the high data forwarding load. The performance of the proposed clustering algorithm is compared with some of the well‐known existing algorithms under different network scenarios. The simulation results validate the superiority of our algorithm in network lifetime, coverage preservation, and energy efficiency.     

3HA: Hybrid Hole Healing Algorithm in a Wireless Sensor Networks

In wireless sensor networks (WSNs), the appearance of coverage holes over a large target field is mostly possible. Those holes reduce network performance and may affect the network efficiency. Several approaches were proposed to heal coverage holes in WSNs, but they still suffer from some weaknesses. In this paper we suggest a distributed algorithm, named hybrid hole healing algorithm (3HA), to find the minimum effective patching positions to deploy additional nodes to cover the holes. A hole manager node of each hole is responsible for operating the 3HA algorithm which requires two phases. The first phase finds all candidate patching positions using a Voronoi diagram. It takes all Voronoi vertices within the hole as the initial patching positions list. The second phase reduces as much as possible this list based on integer linear programming and on a probabilistic sensor model. The 3HA algorithm repeats the above phases in rounds, until all Voronoi vertices are covered. Simulation results show that our solution offers a high coverage ratio for various forms and sizes of holes and reduces the number of additional sensors when compared to some algorithms like the Perimeter-based, the Delaunay triangulation-based, the Voronoi-based, and the Trees-based coverage hole healing methods.

     

Relocation routing for energy balancing in mobile sensor networks

Wireless sensor networks (WSNs) have been widely investigated in the past decades because of its applicability in various extreme environments. As sensors use battery, most works on WSNs focus on energy efficiency issues (e.g., local energy balancing problems) in statically deployed WSNs. Few works have paid attention to the global energy balancing problem for the scenario that mobile sensor nodes can move freely. In this paper, we propose a new routing protocol called global energy balancing routing protocol (GEBRP) based on an active network framework and node relocation in mobile sensor networks. This protocol achieves global energy efficiency by repairing coverage holes and replacing invalid nodes dynamically. Simulation and experiment results demonstrate that the proposed GEBRP achieves superior performance over the existing scheme. In addition, we analyze the delay performance of GEBRP and study how the delay performance is affected by various system parameters.Copyright © 2013 John Wiley & Sons, Ltd.     

Deterministic K‐means secure coverage clustering with periodic authentication for wireless sensor networks

Innovative and emerging developments in sensor networks are proven to be the backbone for real‐time applications such as satellite communications, military and border area surveillance systems, health care systems, traffic monitoring systems, seismic and underwater monitoring systems, and agriculture and habitat environment systems. Coverage and clustering techniques enable the sensor network to operate in group‐based and region‐based communication and thus save the node energy. Energy‐efficient protocols save the node energy and increase the network life cycle in a resource‐constrained sensor network. Cluster head (CH) node manages and controls the operations such as network topology, coverage area, and routing paths (multi‐paths and fault‐tolerant paths) of the network. In this paper, we present deterministic K‐means secure coverage clustering (K‐SCC) with periodic authentication. The proposed protocol uses coverage clustering technique with periodic authentication between the CH node and sensor nodes to establish the secure channel in the network. Maximum cover of K nodes is maintained in the secure coverage cluster to achieve authenticated communication between the sensor nodes in the network. The proposed K‐SCC protocol is compared with the existing protocols such as deterministic‐SCC and random‐SCC protocols. Simulation results indicate that the proposed K‐SCC protocol achieves an average of 84% coverage ratio (cluster/sensor node ratio) as compared with 62% coverage ratio in the existing SCC protocols. Simulations also indicate that the proposed K‐SCC protocol consumes 20% less energy as compared with the existing SCC protocol. Copyright © 2015 John Wiley & Sons, Ltd.     

An Energy-Efficient Routing Algorithm Based on Relative Identification and Direction for Wireless Sensor Networks

In studies of wireless sensor networks (WSNs), routing protocols in network layer is an important topic. To date, many routing algorithms of WSNs have been developed such as relative direction-based sensor routing (RDSR). The WSNs in such algorithm are divided into many sectors for routing. RDSR could simply reduce the number of routes as compared to the convention routing algorithm, but it has routing loop problem. In this paper, a less complex, more efficient routing algorithm named as relative identification and direction-based sensor routing (RIDSR) algorithm is proposed. RIDSR makes sensor nodes establish more reliable and energy-efficient routing path for data transmission. This algorithm not only solves the routing loop problem within the RDSR algorithm but also facilitates the direct selection of a shorter distance for routing by the sensor node. Furthermore, it saves energy and extends the lifetime of the sensor nodes. We also propose a new energy-efficient algorithm named as enhanced relative identification and direction-based sensor routing (ERIDSR) algorithm. ERISDR combines triangle routing algorithm with RIDSR. Triangle routing algorithm exploits a simple triangle rule to determine a sensor node that can save more energy while relaying data between the transmitter and the receiver. This algorithm could effectively economize the use of energy in near-sensor nodes to further extend the lifetime of the sensor nodes. Simulation results show that ERIDSR get better performance than RDSR, and RIDSR algorithms. In addition, ERIDSR algorithm could save the total energy in near-sensor nodes more effectively.     

An Energy Efficient Barrier Coverage Algorithm for Wireless Sensor Networks

Intrusion detection is one of the most important applications of wireless sensor networks. When mobile objects are entering into the boundary of a sensor field or are moving cross the sensor field, they should be detected by the scattered sensor nodes before they pierce through the field of sensor (barrier coverage). In this paper, we propose an energy efficient scheduling method based on learning automata, in which each node is equipped with a learning automaton, which helps the node to select best node to guarantee barrier coverage, at any given time. To apply our method, we used coverage graph of deployed networks and learning automata of each node operates based on nodes that located in adjacency of current node. Our algorithm tries to select minimum number of required nodes to monitor barriers in deployed network. To investigate the efficiency of the proposed barrier coverage algorithm several computer simulation experiments are conducted. Numerical results show the superiority of the proposed method over the existing methods in term of the network lifetime and our proposed algorithm can operate very close to optimal method.     

多蜜源蜂群算法在无线传感器网络覆盖的优化

基于人工蜂群算法以及无线传感器网络相关技术,提出了一种基于互动策略的多蜜源蜂群算法。该算法采用灵敏度与信息素结合的选择策略代替轮盘赌选择方式以实现跟随蜂的开采过程并引入互动策略实现跟随蜂的邻域搜索。此外,在每次迭代结束时,根据OBL策略产生新蜜源以更新最差蜜源。仿真结果表明,该算法能够使检测区域内传感器节点的分布更加均匀,且通过较少次数的迭代,实现更优的网络覆盖率,这对于延长整个无线传感器网络的生命周期,降低网络的能耗,有着重要的影响。     

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.     

Optimized mobile sink based grid coverage-aware sensor deployment and link quality based routing in wireless sensor networks

Mobile sink (MS) has been used in wireless sensor networks (WSN) to increase the network lifetime by changing the location over time. The major quality of service given by WSN is coverage energy consumption (EC) and network lifetime. There are many methods implemented for enhance the coverage hole restoration and reduce the EC. We propose a novel MSCOLER (MS based Coverage Optimization and Link-stability Estimation Routing) protocol for Optimal Coverage restoration and Link stability Estimation. An optimization algorithm is used to optimize the coverage hole and move the redundant node besides the hole. During the routing process, link quality based routing is used to discover the relay nodes with the estimation of link stability to enhance the entire network lifetime and practically make the perfect transmission distance for energy saving. Experimental results demonstrate that proposed protocol can solve the coverage restoration problem, decrease the EC and reduce the network lifetime. The performance is evaluated regarding Average of residual energy (ARE), Receiving packets ratio (RPR), Moving energy consumption (MEC), Network lifetime (NL), Percentage of coverage (%C) and Average Energy Consumption (AEC).     

用马尔科夫模型优化分布式最小连通支配集算法

 为了提高无线传感器网络(WSNs)的能量利用效率、延长网络的生存时间,对基于极大独立集的最小连通支配集算法(MISB)进行优化,提出了一种新的算法.本文首先应用离散马尔科夫链为节点建立模型,并且根据模型预测节点的能量消耗;本算法进行多轮选举,每一轮开始时根据节点的度和能量选举支配点,依据模型预测的能量消耗决定本轮的运行时间,本轮运行结束时从新选举支配点,开始新一轮.仿真结果表明,本算法和原算法相比可以更好地平衡网络的能量消耗,提高全网的能量利用率,极大地延长网络的生存时间.     

一种基于有向感知模型的传感器节点覆盖算法

覆盖控制作为无线传感器网络中的一个基本问题,反映了传感器网络所能提供的“感知”服务质量.优化传感器网络覆盖对于合理分配网络的空间资源,更好地完成环境感知、信息获取任务以及提高网络生存能力都具有重要的意义.针对无线传感器网络方向个数固定的有向感知模型提出一种覆盖增强算法,采用复杂网络社团结构算法划分对网络进行节点子集划分,重新调整节点的感知方向,增强网络的覆盖率,同时有效降低了算法的时间复杂度.     

一种基于冗余度的无线传感器网络节能策略

在无线传感器网络中,传感节点由于采用电池供电,因此寿命有限。如何有效节省传感器节点的能量,延长网络的使用寿命,一直是广泛研究的焦点。文章提出一种适用于高冗余度布置的无线传感器网络结构中,节省传感器节点能量消耗的方法-接续调度法。该方法通过协调点对小区域内节点的调度,使区域内节点依次分时段工作。通过这种接续调度,避免了节点间的冲突和串扰,达到延长整体网络寿命的效果。     

基于能量预测的无线传感器网络节点覆盖调度算法

针对无线传感器网络中存在的热区问题,采用非均匀部署方案,并在此基础上提出基于能量预测的无线传感器网络节点覆盖调度算法。并对算法进行了仿真实验和性能分析。结果表明该算法可以延长的网络生命周期并在较长的时间里保持较高的网络覆盖率,能够达到网络内大多数节点能耗均衡的设计目标。     

基于节点休眠的水下无线传感器网络覆盖保持分簇算法

为有效延长水下无线传感器网络的生命周期、保持网络覆盖率,该文提出一种基于节点休眠的覆盖保持分簇算法。首先计算网络节点的覆盖冗余度,并对覆盖冗余度高的节点执行休眠策略,然后以网络覆盖率及节点能耗均衡性为目标,采用多目标算法进行求解,再利用TOPSIS法从非支配解集中选出较优解,当有节点死亡时,通过唤醒策略保持网络覆盖率。仿真结果表明,与目前较好的网络规划算法相比,该文算法能够更好地降低网络能耗,延长网络生命周期并保持网络对环境的覆盖率。