能量均衡的无线传感器网络分簇方法

在对节点通信模式和簇群划分过程分析的基础上,提出一种在节点分布不均匀的条件下,构建能量均衡簇群的方法.该算法兼顾了簇群成员节点与簇头通信的能量消耗和簇群能耗负载,实现各簇群间能耗的平衡.仿真表明,该方法在网络生命期、节点平均生命期和网络扩展性方面比基于最短距离的分簇算法具有更好的性能.     

能耗均衡的自供能无线传感器网络分簇路由算法

当前的采能技术已经能够让传感器节点自动从环境中获得适量的能量补给,针对现有自供能无线传感器网络分簇路由算法中未考虑位于不同地理区域的节点所获补给能量大小的不同,而导致能量补给少区域的簇头数过少、簇规模过大、全网能耗不均衡等问题,本文提出了一种能耗均衡的自供能无线传感器网络分簇路由算法-EBCS（energy balanced clustering with self-energized）,该算法结合实际能量补给场景对簇头选举机制进行了改进,并采用了一种自适应式簇间通信机制,充分保存与利用补给能量。理论和仿真实验表明：EBCS算法能够较好维持预设的簇头比例,在网络平均剩余能量、当前可用节点数量等性能方面优于另外两种现有算法。     

高效节能的WSN非均匀分簇节点调度算法研究

针对目前无线传感器网络分簇算法中存在的节点能量消耗不均衡,大量节点工作导致信息冗余和能量浪费等问题,提出一种高效节能的WSN非均匀分簇节点调度算法EEBUC（Energy-Efficient and Balanced Unequal Clustering Nodes Scheduling）。该算法在簇的形成阶段,考虑候选簇首离汇聚点的距离、所在区域的节点密度和节点能量形成非均匀的竞争范围,构造大小不等的簇,平衡簇内和簇间的通信能耗;同时结合调度簇内冗余节点方法,减少网络中每轮工作节点数量,提高网络能量利用率。利用OMNET++仿真软件进行仿真,实验结果表明,EEBUC算法能有效节约网络能量,均衡节点能耗,比LEACH 协议和EEUC协议分别延长网络寿命203%和50%。     

基于RSSI的无线传感网络梯度分簇算法

无线传感器网络(WSN)通常采用分簇结构以减少通信量,降低网络的能量消耗。针对无线传感网在数据收集模式下节点的负载不均衡问题,提出一种基于可接收信号强度指示（RSSI）的WSN梯度分簇(RGC)算法,以节点RSSI值为基础建立梯度,形成层次性结构。从具有不同梯度与相同梯度的相邻簇首节点两方面着手,设计了负载均衡的分簇算法,有效降低其复杂度和能耗,延长网络生命周期。实验证明了该算法的正确性和有效性。     

无线传感器网络中一种能量均衡的分簇策略

以无线传感器网络中的能量消耗模型为基础,提出了一种能量均衡的无线传感器网络分簇路由协议EECHS(energy-effficient cluster-head selection)。该协议通过节点的剩余能量和节点距离基站的距离来调节其成为簇首的概率,并进一步调节簇的大小。仿真结果表明,与改进后的DCHS协议相比,该策略使网络的生命周期和稳定周期分别提高了31%和45%以上。     

传感器网络中一种新的基于能量的分簇算法

传感器网络节点大部分采用电池供电,致使节点能量非常有限。为了节省能量进而延长网络寿命,文中提出了一种新的簇头选择算法EBC,EBC算法除了能够在局部网络内完成数据采集和数据处理外,还能够形成由簇头和网关节点组成的骨干网并完成整个网络通信。通过在Mambo节点上的实验证明,该算法能够有效地均衡整个网络的能量,并很好地应用于实际的传感器网络中。     

Distributed load balancing mechanism for detouring schemes of geographic routing in wireless sensor networks

Well-known ‘routing hole’ problem of geographic routing is hardly avoided in wireless sensor networks because of various actual geographical environments. Existing geographic routing protocols use perimeter routing strategies to find a detour path around the boundary of holes when they encounter the local minimum during greedy forwarding. However, this solution may lead to uneven energy consumption around the holes since it consumes more energy of the boundary sensors. It becomes more serious when holes appear in most of routing paths in a large-scale sensor network. In this paper, we propose a novel distributed strategy to balance the traffic load on the boundary of holes by virtually changing the sizes of these holes. The proposed mechanism dynamically controls holes to expand and shrink circularly without changing the underlying forwarding strategy. Therefore, it can be applied to most of the existing geographic routing protocols which detour around holes. Simulation results show that our strategy can effectively balance the load around holes, thus prolonging the network life of sensor networks when an existing geographic routing protocol is used as the underlying routing protocol.     

Multi objective clustering for wireless sensor networks

Ambient Intelligence is the next wave in computing and communication technology. Nano-sensors, wireless networks and unified intelligent software are the main elements of this issue. Inputs of ambient intelligence are taken from sensors in the environment. Wireless sensor networks consists of small and low cost sensors that collect and report environmental data. Wireless sensors are dispersed in an area that some phenomenon or event should be monitored. When a sensor detects the monitored event (heat, pressure, sound, light, areas having magnetic properties, vibration, etc.), the event is reported to one of the sites. This site performs an appropriate task such as sending a message or local processing based on the type of network, and then provides the appropriate response. One of the major challenges in wireless sensor networks is optimizing the energy consumption. Studies have shown that by clustering network nodes, it is possible to use their energy more efficiently. This study proposes a clustering based routing method to be used in wireless sensor networks. Multi-objective optimization algorithm named as Non-dominated sorting genetic algorithm-II is used for clustering and seven objective functions are described. It is aimed to carry out several goals at once by using multi objective algorithm. While communication cost between the objective functions and cluster-head and Sink, and cluster-head and non-cluster-head is tried to be minimized, selection of the cluster heads only from the nodes near Sink is also tried to be prevented and it is also taken into consideration for clusters to include more nodes as much as possible. Each solution of the solution set obtained with Non-dominated sorting genetic algorithm-II points a different network topology. Each solution in solution set is the best solution according to some of objective functions. It is provided that Sink simulate each solution in solution set according to a certain scenario and choose one suitable for the desired criteria. In proposed method, both operating the Non-dominated sorting genetic algorithm-II and, simulation and evaluation of the obtained solutions comes out in Sink which has sufficient operation and power sources. According to the results, the proposed method can make the life span of network five times longer than LEACH, which is the most famous clustering algorithm. Besides, while the proposed method extends the life span of network, it is also seen that it increases the number of the packet reaching Sink two times more than LEACH. The data provided by proposed method includes information about larger areas when compared to LEACH.     

基于簇的无线传感网络流量负载的时隙调度协议*

针对大规模的无线传感器网络MAC协议在能量有效、低延时等方面的不足,提出一种基于簇的自适应时隙调度协议（ATSP）。整个网络由一些较小单位的簇组成,在每个簇内构造一棵数据聚集树,根据数据聚集树对节点每轮需要发送的数据流量进行加权,决定该节点的时隙大小;然后由簇头动态调节簇内节点时隙更新频率和顺序,可以降低时隙划分的能量和时间代价,减少节点的空闲侦听时间,避免串音。仿真表明,该协议有效地提高了网络能量有效性,延长了网络生存周期,降低数据包的延时。     

一种无线传感器网络的能量平衡调度算法

在一种位置无关且计算简单的节点调度算法的基础上,提出一种基于能量平衡的调度算法,该算法的目的在于保证整个网络中的大部分节点能量的平衡。分析和仿真结果表明,该算法在保证能量平衡的同时可以延长整个网络的寿命。     

无线传感器网络中节点选择机制综述*

节点选择是保证无线传感器网络满足系统QoS需求的最重要问题之一,一种性能较好的节点选择机制可以在保证数据精度的前提下延长网络生命周期。针对WSN节点选择问题进行了描述及分类,着重研究了几类当前具有代表性的节点选择机制,并分析比较了各自的性能及缺点;最后对节点选择的进一步研究方向进行了展望。     

基于蚁群策略的无线传感器网络能耗均衡分簇算法

在多跳路由中簇头选择控制因子单一的问题将缩短整个无线传感器网络的生存周期。为此,以剩余能量、节点度和连接距离为依据构造适应度函数,根据簇头评估函数值来保证簇头的最优选择。同时加入适应度因子和剩余能量权衡因子优化蚁群算法,有效控制完整路径中信息素的增减量,以此应用到数据在簇头间的多跳传输,保护了低能量的簇头,有利于各节点能耗趋于平均值,使网络可以更加持久地监测和传输数据。与LEACH和HEED算法相比,本文算法在能耗均衡、生存周期延长方面更加有效。     

双层无线传感网络的3连通近似算法

主要研究双层无线传感网络模型,即数据信息流只能在传感器和中继器或中继器和中继器之间传输,而不能在传感器之间传输。近似算法基于两个子问题：k圆盘覆盖问题和单层传感网络的k连通问题,而后在部分中继器周围设置“等六边形”结构的中继器点,最终达到整个网络的3-连通水平。该算法的最终性能比为8α+β,其中α为k圆盘覆盖近似算法的性能比,β为单层传感网络的k连通近似算法的性能比。     

一种能量高效的无线传感器网络分簇路由算法

无线传感器网络中节点的能量有限,提高能量的有效性便成为无线传感器网络路由协议设计的首要目标。设计了一种能量高效的分簇路由算法,它提出让候选节点在一定的覆盖范围内以剩余能量为标准来竞选簇头,以使簇头分布均匀;处于簇类交界的节点则根据能量和距离来选择归属的簇头,以平衡网络负载;新算法还采用多跳的簇间通信方式来降低大部分簇头节点的通信负载。仿真结果表明:新算法能够有效降低网络能耗,延长网络生存时间。     

无线传感器网络能量均衡的多sink分簇路由算法

针对无线传感器网络中传感器节点能量有限以及节点能耗不均衡的问题,提出了一种基于能量均衡的多sink分簇路由算法（EBMCR）。该算法在簇头选择阶段,综合考虑了节点的剩余能量级和节点到sink的距离等因素选择簇头节点;在簇间通信过程,采用多跳传输的方式,综合考虑了路径能量消耗、路径最小剩余能量和节点到sink的跳数等因素,选择节点到多个sink的最优路径。仿真结果表明,该算法能够有效地均衡网络能量,延长网络生命周期。     

Energy-efficient distributed clustering in wireless sensor networks

The deployment of wireless sensor networks in many application areas requires self-organization of the network nodes into clusters. Clustering is a network management technique, since it creates a hierarchical structure over a flat network. Quite a lot of node clustering techniques have appeared in the literature, and roughly fall into two families: those based on the construction of a dominating set and those which are based solely on energy considerations. The former family suffers from the fact that only a small subset of the network nodes are responsible for relaying the messages, and thus cause rapid consumption of the energy of these nodes. The latter family uses the residual energy of each node in order to decide about whether it will elect itself as a leader of a cluster or not. This family’s methods ignore topological features of the nodes and are used in combination with the methods of the former family. We propose an energy-efficient distributed clustering protocol for wireless sensor networks, based on a metric for characterizing the significance of a node, w.r.t. its contribution in relaying messages. The protocol achieves small communication complexity and linear computation complexity. Experimental results attest that the protocol improves network longevity.     

Energy-efficient clustering in lossy wireless sensor networks

Recent experimental studies have revealed that a large percentage of wireless links are lossy and unreliable for data delivery in wireless sensor networks (WSNs). Such findings raise new challenges for the design of clustering algorithms in WSNs in terms of data reliability and energy efficiency. In this paper, we propose distributed clustering algorithms for lossy WSNs with a mobile collector, where the mobile collector moves close to each cluster head to receive data directly and then uploads collected data to the base station. We first consider constructing one-hop clusters in lossy WSNs where all cluster members are within the direct communication range of their cluster heads. We formulate the problem into an integer program, aiming at maximizing the network lifetime, which is defined as the number of rounds of data collection until the first node dies. We then prove that the problem is NP-hard. After that, we propose a metric-based distributed clustering algorithm to solve the problem. We adopt a metric called selection weight for each sensor node that indicates both link qualities around the node and its capability of being a cluster head. We further extend the algorithm to multi-hop clustering to achieve better scalability. We have found out that the performance of the one-hop clustering algorithm in small WSNs is very close to the optimal results obtained by mathematical tools. We have conducted extensive simulations for large WSNs and the results demonstrate that the proposed clustering algorithms can significantly improve the data reception ratio, reduce the total energy consumption in the network and prolong network lifetime compared to a typical distributed clustering algorithm, HEED, that does not consider lossy links.     

无线传感器网络中一种有效的分布式簇划分算法

提出了一种快速有效的分布式簇划分算法，为每个节点设定一个初始时间，最先到期的节点成为簇头。考虑到簇头选举的合理性，时间衰减与节点连通度相关，并辅以随机化的方法消除时间同步对算法的影响。通过仿真验证该簇划分算法的有效性，并定量分析了通信半径与平均簇头个数的关系。     

无线传感器网络分簇方法的优化

现有的分布式分簇算法都是针对节点分布均匀的传感器网络设计的,不适用于节点分布不均匀的传感器网络,簇负载均衡和降低能耗成了节点不均匀部署的传感器网络的一个重要挑战。针对节点分布不均匀网络提出了一种基于区域密度的分布式分簇算法（RDCA）,算法中节点测试其所在区域的节点密度,根据区域节点密度,调节其通信的覆盖范围,从而使成簇后簇负载达到平衡。仿真实验结果显示,在节点部署不均匀的传感器网络中,本算法与LEACH、HEED相比较,可以更好地实现簇的负载平衡,有效地提高成簇后网络的稳定周期。