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.     

一种能量有效的无线传感器网络路由算法

无线传感器网络中传感器节点能量有限,为了提高能量利用率,针对现有算法随机选择簇首、簇结构不合理等缺陷提出了一种新的能量有效的分簇路由算法EERA.EERA采用新的簇首选举、成簇,以及构建簇间路由算法,基于节点剩余能量与节点的相对位置选择簇首、成簇,使剩余能量较多的节点优先成为簇首并且各簇首能较均匀的分布在网络区域内;构建簇间路由时将最小跳数路由算法与改进的MTE算法结合起来,在簇间形成最小跳数、最小能耗路径.仿真结果表明,EERA算法可以均衡全网能量消耗,延长网络的生命周期.     

基于准格型策略的无线传感网协作覆盖算法

该文提出了一种基于准格型策略的无线传感网协作覆盖QGCC(Quasi-Grid based Cooperative Coverage)算法,通过在随机分布节点中构造准格型结构并结合协作感测模型,减少活动节点数量,延长覆盖周期。QGCC设计了低复杂度的分布式虚拟网格确定方法及能量高效的节点调度策略,定义了不规则度指标以分析网络的不规则程度对覆盖性能的影响。仿真实验表明,相比于参照算法,QGCC能够较大程度地减少活动节点的数量,大幅延长网络的覆盖周期;此外,该算法的覆盖周期和节点密度具有近似线性的关系,且比参考算法具有更大的斜率,说明其对冗余节点具有更高的利用效率。     

An Energy Efficient Autonomous Method for Coverage Optimization in Wireless Multimedia Sensor Networks

In this paper, a distributed method for coverage optimization of random deployed WMSNs utilizing motility and mobility capabilities of nodes, is proposed. The aims followed by the method are first, maximizing the coverage ratio by minimizing both the covered overlapping areas, and the coverage holes after random deployment, and second, enhancing energy efficiency of the coverage optimization procedure, by minimizing the needed rotations and specially movements, comparing with the previous schemes. To these aims, the most appropriate location and orientation of the nodes are calculated round by round considering all the possible nested compositions of rotation and movement. But, rotating and moving the nodes are performed after terminating the algorithm rounds and achieving the decisive results. So, the proposed method does not impose the overhead of trial and error of rotation or relocation on the network nodes. The performance of the proposed approach has been compared with the previous works for different network configurations; simulation results show that the proposed approach outperforms the previous schemes in terms of both coverage ratio and energy efficiency.     

Energy Efficient Clustering Algorithm Based on Particle Swarm Optimization Technique for Wireless Sensor Networks

Wireless Personal Communications - In this paper, we propose a Gated Recurrent Unit(GRU) neural network traffic prediction algorithm based on transfer learning. By introducing two gate structures,...     

一种基于多目标遗传优化的无线多媒体传感器网络节能覆盖方法

提出一种基于多目标遗传优化的节能覆盖方法.以节点不同开启顺序建立个体基因组,采用双交叉保留优秀个体,在保证覆盖度的同时,开启尽可能少的节点.本方法延长了网络生命期,均衡了网络中各节点能耗,同D-Greedy及DCS-dist等方法相比,也表现出了较好的性能.     

Data Association Coverage Algorithm Based on Energy Balance and Controlled Parameters in Wireless Sensor Networks

Based on a position-independent and computationally simple node scheduling algorithm, a scheduling algorithm based on energy balance is proposed. The analysis and simulation results showed that the algorithm can extend the lifespan of the entire network whereas ensuring energy balance. Data aggregation was a relatively time-consuming operation in sensor networks, especially in high-density networks. Therefore, minimizing the problem of data aggregation delay had become a hot topic of research. The algorithm adopted a clustering idea of low power in the cluster and high power between clusters, combined with channel allocation to reduce data aggregation delay, and data aggregation between clusters can be performed without collisions. The number of channels used in different network topologies tends to be constant.

     

An Energy Efficient Clustering Algorithm Based on Annulus Division Applied in Wireless Sensor Networks

Wireless Personal Communications - Energy efficiency and energy balance are two important performance indexes in wireless sensor networks which determine the lifetime of networks. This paper...     

Energy Efficient Clustering Algorithm Using RFD Based Multi-hop Communication in Wireless Sensor Networks

In recent years, researchers have focused on many challenging aspects in the area of Wireless Sensor networks (WSNs). Development of energy efficient data collection protocols became the major concern in WSN. Clustering is one of the suitable techniques for energy efficiency. However, in clustering, the cluster are formed with uneven size. This unbalances the energy consumption among clusters which in turn reduce the lifetime of the network. In this paper, in order to balance the energy among clusters, a multi-hop concept is introduced for both intra and inter cluster communication. Firstly, the RFDMRP: River Formation Dynamics based Multi-hop Routing Protocol has been proposed. Later, this protocol is integrated with clustering and a new hybrid technique, named as hybrid clustering communication algorithm using RFDMRP (HCCRFD) is introduced. HCCRFD improves energy conservation by reducing overall packet transmission distance of intra and inter cluster communication, which results in increased network lifetime. Energy consumption of proposed algorithm has been analyzed mathematically. Also, the algorithms were simulated using MATLAB and outputs observed. The observed outputs were compared with existing protocols such as LEACH, DEEC, ERA, and \(ACH^2\) in three different scenarios namely homogenous, heterogeneous environment, and node density. The comparison reveals that the proposed algorithm perform better than the existing protocols with respect to energy conservation and network lifetime.     

A Learning Automata Based Area Coverage Algorithm for Wireless Sensor Networks

One way to reduce energy consumption in wireless sensor networks is to reduce the number of active nodes in the network. When sensors are redundantly deployed, a subset of sensors should be selected to actively monitor the field （referred to as a ＂cover＂）, whereas the rest of the sensors should be put to sleep to conserve their batteries. In this paper, a learning automata based algorithm for energy-efficient monitoring in wireless sensor networks （EEMLA） is proposed. Each node in EEMLA algorithm is equipped with a learning automaton which decides for the node to be active or not at any time during the operation of the network. Using feedback received from neighboring nodes, each node gradually learns its proper state during the operation of the network. Experimental results have shown that the proposed monitoring algorithm in comparison to other existing methods such as Tian and LUC can better prolong the network lifetime.     

Exploiting Mobility for Efficient Coverage in Sparse Wireless Sensor Networks

Reliable monitoring of a large area with a Wireless Sensor Network (WSN) typically requires a very large number of stationary nodes, implying a prohibitive cost and excessive (radio) interference. Our objective is to develop an efficient system that will employ a smaller number of stationary nodes that will collaborate with a small set of mobile nodes in order to improve the area coverage. The main strength of this collaborative architecture stems from the ability of the mobile sensors to sample areas not covered (monitored) by stationary sensors. An important element of the proposed system is the ability of each mobile node to autonomously decide its path based on local information (i.e. a combination of self collected measurements and information gathered by stationary sensors in the mobile’s communication range), which is essential in the context of large, distributed WSNs. The contribution of the paper is the development of a simple distributed algorithm that allows mobile nodes to autonomously navigate through the field and improve the area coverage. We present simulation results based on a real sparse stationary WSN deployment for the coverage improvement scenario.     

一种无线传感器网络的能耗平衡覆盖模型

针对无线传感器网络节点能量有限、最小覆盖方法能耗不均衡的问题,该文提出了一种能耗平衡的连通覆盖模型,并对模型进行了分析与仿真。模型利用Voronoi划分和Delaunay三角剖分对传感器网络进行分割,判别重复覆盖目标区域的冗余传感器节点,采用节点到sink点的跳数对节点分层,进而提出选择休眠节点的方法。仿真结果表明,由模型建立的非最小连通覆盖集所导出的无线传感器网络,能够平衡节点能耗、使用优化路由、减弱路由关键点的影响。     

Reliable and Energy Efficient Communication Algorithm in Hierarchical Wireless Sensor Networks

Wireless sensor networks are data centric networks, which transmit gathered data to sink nodes. Considering energy constraints, how to make full use of the limited energy to reliably transmit data as much as possible becomes a main research region in sensor networks. In this paper, we focus on energy consumption and reliability of different communication modes. Single hop communication mode is simple and easy to implement, but the distant cluster members, especially those on the edge of the networks, need to enlarge transmission power. On the other hand multi-hop communication is not constrained by the communication distance. The relay communication mode guarantees data transmission to a remote cluster head. Considering of the reliability and energy consumption, we propose a voting based clustering communication algorithm. And the optimal cluster number is calculated based on the geometry locations. Finally, several experiments have been done to validate the analysis in this paper.     

基于改进PSO的WMSNs覆盖增强算法

对无线多媒体传感器网络(WMSNs)的覆盖增强问题进行了研究.在WMSNs网络中,视频、图像节点的视角范围有限,只能监控周围的部分区域.由于节点数量众多、部署方式受限等原因,网络中往往存在大量的监测重叠与监控盲区,需要对各节点的感知方向进行优化,以提高网络的监控质量.文中基于有向感知模型,提出了一种覆盖增强算法MCE.MCE对各节点的感知方向进行调整,并使用了改进的PSO算法来计算求解.仿真实验表明,MCE算法能够有效地提高网络的覆盖率.     

基于能量优化的无线传感器网络安全路由算法

针对无线传感器网络路由面临安全威胁和节点能量有限的不足,提出一种基于能量优化的安全路由算法(EOSR).该算法把优化能量、提高路由安全性和缩短传输时延同时作为设计目标,采用多目标决策,在保证安全性和快速传输的同时,让能量储备较多的节点承担较多的数据转发任务,可获得最优路由和延长网络生命期.通过预置公私密钥对,有效地提高了路由的安全性.给出了该算法中路由发现、路由选择和路由删除的具体步骤,通过仿真实验证明该算法的有效性.     

一种基于蚁群算法的WSN能效均衡路由

为了解决无线传感器网络的能耗不均衡问题,提出了一种基于蚁群算法(ACO)的自适应能量均衡路由算法(EBEA).该算法将节点的能量密度融入到启发因子中,利用蚂蚁的动态适应性在全局范围内寻求最优路径让网络达能量均衡的效果.仿真实验结果表明,与LEACH算法相比,该算法能够均衡整个网络的能耗,并有效的避免了网络分割或者"能量空洞"现象,延长网络的生命周期.     

基于容忍覆盖区域的无线传感器网络节点调度算法

节点调度机制是解决无线传感器网络节点能量受限问题的重要方法.传统的位置信息无关的节点调度方案以节点的感知区域覆盖为调度目标,导致处于边界区域的节点由于没有太多机会进入休眠状态而先死亡,进而引起死亡节点向监测中心扩散现象,我们称这种现象为"不均等休眠"问题.针对该问题,从理论上对节点覆盖模型进行分析,提出容忍覆盖区域的概...     

无线传感器网络基于参数可调增强型覆盖控制算法

覆盖问题是无线传感器网络领域的一个基本问题,也是无线传感器网络特性当中的一个重点问题.如何通过某种算法达到以最少传感器节点对监测区域的有效覆盖已成为目前研究的一项重要课题.因此,提出一种增强型覆盖控制算法(Enhanced Coverage Control Algorithm, ECCA).该算法通过概率理论知识可以有效地求解出对监测区域进行有效覆盖下的最少节点,给出了传感器节点概率的期望值计算方法以及目标节点首次被传感器节点覆盖和多次覆盖后的期望值求解过程,验证随机变量相互之间不独立时的比例函数关系.仿真结果表明,ECCA算法可以使用较少的传感器节点数量完成对监测区域的有效覆盖,提高了对监测区域的覆盖质量.     

Node Degree Based Energy Efficient Two-Level Clustering for Wireless Sensor Networks

Wireless Personal Communications - Recently fuzzy based hierarchical routing protocols such as F-MCHEL and F-SCH were proposed to improve the lifetime of a wireless sensor network. In certain cases...     

异构传感器网络覆盖势力剖分算法

对于普遍存在的异构传感器网络,目前尚缺乏有力的方法解决其覆盖势力的剖分问题。对此,该文提出一种本地化的覆盖势力剖分算法CFA(Coverage Force Algorithm)。该算法根据节点感应能力的差异,构建基于感应异构性的通用Voronoi图,能有效对网络中异构节点的覆盖势力范围进行剖分。实验证明,CFA算法解决了异构网络覆盖性能分析问题,和传统的Voronoi图方法相比,具有广普性和本地化的特点。