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。     

基于单向多汇聚节点的WSN分层路由协议

针对分层无线传感器网络的簇首节点容易成为网络瓶颈制约网络性能的不足,提出一种低能耗的路由协议。采用多汇聚（Sink）节点模式来构建网络,利用RSSI（接收信号强度指示）测出各传感器节点与各Sink节点之间的距离,并依据距离的远近为Sink节点划分作用域。通过传感器节点单向与所属Sink节点通信来降低簇首节点的负担。仿真实验结果表明提出的路由协议能有效克服簇首节点网络瓶颈问题,从而降低网络能耗,提高网络生存时间,对于无线传感器网络应用于大范围数据收集的网络具有重要的价值。     

基于能量水平的多Sink节点传感器网络路由算法

单Sink节点传感器网络存在着部分关键路径上节点能量消耗过快、路由选择算法单一以及Sink节点失效等问题.首先提出了多Sink节点传感器网络数据收集的系统框架;给出了拓扑发现和维护策略;然后提出了基于最小能量消耗路由算法.在分析了该算法的不足后提出了基于能量水平的路由算法,按照计算得到的能量水平选择最优的路径进行数据传送.实验证明,基于能量水平的路由算法比基于最小能量消耗路由算法能更有效提高传感器网络的使用寿命.     

保证覆盖的无线传感器网络梯度部署方法

在大规模随机部署的无线传感器网络中,数据通常逐跳汇聚到Sink节点,因而与Sink邻近的节点需要转发大量的数据,从而导致了Sink邻近区域内的节点因能量耗尽而引起网络失效。此时,外层区域的节点仍剩余大量的能量。本文首先提出了网络生存期最大化部署的问题,分析了无线传感器网络数据转发的特点,基于此特点给出了梯度的节点密 密度部署方法,以提高能量利用率,最小化剩余能量,最后通过理论和实验分析了梯度部署方法的性能。     

基于能量感知的无线传感器网络层次型路由协议

为了有效平衡负载,满足大规模网络的需要,提出了一种基于能量感知的无线传感器网络层次型路由协议。该协议基于能量消耗模型,根据节点与基站的距离将网络中的节点划分为不同的层次。每层次内的节点轮流当选负责收集该层内所有节点数据的汇聚节点。汇聚节点的数据逐层转发和聚合,最后传送到剩余能量较大的一个汇聚节点——超节点,由其将数据发送到基站。汇聚节点变迁、超节点变迁机制用于均衡节点能量消耗,延长网络生命周期。NS2仿真结果表明,该协议可以有效节省能量,延长网络生存时间。     

基于改进ACO的WSN感知数据传输策略研究

无线传感器网络(WSN)能够利用传感器节点快速准确地获取物理世界的信息从而作为物联网的感知层在监控领域得到了广泛的应用,而能量利用率是能量受限无线传感器网络的一个关键属性,直接影响网络的生命周期.经典的分层路由LEACH(及其变种)算法是无线传感器网络中最常见的节能路由协议.该文提出了一种改进的LEACH算法,由sin...     

一种长距离链式无线传感器网络节点部署方法

为了更可靠、高效地将无线传感器网络应用到长距离工程监测中,针对其单覆盖的特点,提出多汇聚节点的双链式结构部署节点的方法,并用不等间距的优化部署方法部署传感器节点,进一步均衡整个网络能耗,同时给出了各跳间距的计算公式;分析和仿真表明,多汇聚节点的双链式优化部署方法适合长距离传输,并可克服个别传感器节点因转发数据而过度消耗能量过早死亡的缺陷,使得各传感器节点均衡能耗,显著地延长了网络的生命周期.     

移动社会网络中社会性路由算法研究

在无法部署Sink的无线传感器网络中, 数据采集者(即:能够收集数据的人或移动设备)在网络的任意位置收集数据, 即泛在数据收集。网络区域中的节点数量庞大, 能量有限, 如何能有效地采集到全部节点的数据是一个难点。提出一个网络生命周期最大化的泛在数据收集协议MULAC。MULAC以用户所在当前位置为圆心, 半径为r的区域内选择一个节点v。以v为根构造一棵最大化生命周期树T。网络中的节点可以通过T传送数据给v, 数据采集者可以通过v接收到网络中的全部数据。当数据采集者移动到其他位置, T将根据用户新的位置改变根节点, 并且以最小的能量耗费调整树结构, 从而延长全网的寿命。在收集数据过程中保证无线传感器网络生命周期最大化是一个NP完全问题, MULAC能够近似最优的解决此问题。仿真实验和理论分析表明, MULAC能有效延长网络生命周期。     

基于均匀分簇的正三角模型节点轮换路由算法

针对节点随机分布的无线传感器网络能耗问题,提出一种在均匀分簇后采用正三角模型对簇内节点进行调度的低能耗路由算法。该算法首先计算网络内节点总能耗最小时的分簇数目,再由Sink节点选择相应数目的剩余能量最大、地理位置最优的节点为簇首,完成均匀分簇。簇内节点采用正三角模型和节点覆盖概率进行工作节点的选择。仿真结果表明,该路由算法可以均衡节点能耗,延长网络工作轮数,降低网络延迟,并体现出了更优的网络鲁棒性。     

A novel knowledge-guided evolutionary scheduling strategy for energy-efficient connected coverage optimization in WSNs

One of the most important challenges in designing wireless sensor network is how to construct full-connected network containing least active sensor nodes with satisfied quality of services, such as the coverage rate and energy consumption. This energy-efficiency full-connected coverage optimization problem is modeled as a single-objective optimization problem with constraint. To solve this problem, a knowledge-guided evolutionary scheduling strategy is proposed. Three highlights of this strategy are: (1) Knowledge is defined as the importance of sensor node, which depends on the distance between sensor node and sink node. (2) The genes of an individual correspond to senor nodes in descending order of their importance. (3) Considering sensor nodes’ importance and redundancy rate, knowledge-guided mutation operator and repair strategy are present. Simulation results show that the proposed method can find the optimal full-connected wireless sensor network containing least sensor nodes and consuming less energy for communication by less computation time. Though the coverage rate of the optimum is larger, it still satisfies the coverage constraint. Moreover, this strategy fits for the problems that the communication radius of sensor node is less than two times of its sensing radius.     

Multi-constraint multi-objective QoS aware routing heuristics for query driven sensor networks using fuzzy soft sets

In this paper, a fuzzy based distributed power aware routing scheme considering both energy and bandwidth constraints, especially for query driven applications in the asynchronous duty-cycled wireless sensor networks are devised. The proposed multi-constraint, multi-objective routing optimization approach under strict resource constraints guarantees reliability and fast data delivery along with efficient power management in spite of unreliable wireless links and limited power supply. In query driven applications, the request from the sink to the individual sensor node will be a broadcast message, whereas the individual sensor nodes replies back to sink as unicast messages. In the proposed work, the fuzzy approach and “A Star” algorithm are utilized for satisfying energy and bandwidth constraints to route the broadcast messages of the sink while querying all the sensor nodes in the network. Every node will be provided with a guidance list, which is used to decide the next best neighbor node with good route quality for forwarding the received multi-hop broadcast messages. The route quality of the every node is estimated with fuzzy rules based on the network parameters such as maximum remaining energy, minimum traffic load and better link quality to increase the network lifetime. The provision of overhearing the broadcast messages and acknowledgements within the transmission range minimizes the effort to search for the active time of nodes while routing the broadcast messages with asynchronous scheduling. Further, in the proposed work only the time slot of its nearest neighbor relay node (to which packets are to be forwarded) is learnt to reduce the number of message transmissions in the network. For the unicast message replies, the fuzzy membership function is modified and devised based on the routing metrics such as higher residual energy, minimum traffic loads and minimum hop count under energy and bandwidth constraints. Also, the multi-hop heuristic routing algorithm called Nearest Neighbor Tree is effectively used to reduce the number of neighbors in the guidance list that are elected for forwarding. This helps to increase the individual sensor node’s lifetime, thereby maximizes the network lifetime and guarantees increased network throughput. The simulation results show that the proposed technique reduces repeated transmissions, decreases the number of transmissions, shortens the active time of the sensor nodes and increases the network lifetime for query driven sensor network applications invariant to total the number of sensor nodes and sinks in the network. The proposed algorithm is tested in a small test bed of sensor network with ten nodes that monitors the room temperature.     

无线传感器网络中多sink节点优化部署方法

大规模无线传感器网络(WSN)环境下,当网络结构采用单一的sink节点时,容易造成sink节点周围的普通传感节点因为转发大量其他节点的数据,迅速消耗掉自身能量而使网络失效。为了延长网络寿命,需要降低传感节点到sink节点的跳数,而采用多sink结构是一个有效的方法。为此,需要考虑一定规模的网络中,应该布置多少sink节点,才能使得网络寿命最大化的同时网络成本最低。基于栅格网络结构,提出了多sink节点下的网络寿命模型和网络成本模型,并采用一种新颖的方法计算最大网络寿命成本比(RLC),推导出了保证网络寿命最大化的同时网络成本最低的sink节点个数的表达式。理论结果表明,该值与网络规模、关键节点数、节点收发功率以及普通节点和sink节点的成本等参数有关。最后通过仿真实验证明了该结论的正确性。     

WSN中基于能量代价的能量优化路由算法

针对无线传感器网络路由算法中的节点能耗问题,提出了一种基于能量代价的能量优化路由算法。算法综合考虑数据传输中节点能耗的有效性和均衡性,设计了一种新的能量代价函数,实现了二者的优化匹配。传感器节点按此函数计算前向部居节点的能量代价,选择能量代价最小的节点作为下一跳。算法基于部居节点信息进行路由选择,具有较低的计算时间复杂度。最后,对路由算法的性能进行了仿真分析,并与典型的路由算法进行了对比,结果表明,本路由算法能够有效延长网络生存时间,节约并均衡节点的能量消耗。     

一种适用于煤矿井下无线传感网的能量均衡路由协议

矿井无线传感网的拓扑呈长距离带状,节点间能耗不均问题十分严重。非均匀分簇策略能从全局均衡节点能量负载,在矿井中具有良好的适用性。针对矿井传感网的带状特性提出了一个簇规模自适应调节的能量均衡分簇路由协议。协议根据节点离汇聚点的距离、剩余能量及分布密度来构造规模不等的簇。簇首的竞选以节点相对于周围候选者的能量水平为依据,避免了低能量节点被当选为簇首。簇间多跳路由算法依簇首近似线型的分布特点设计,不但考虑链路能耗最优,亦注重转发节点间的能量均衡。模拟实验结果表明,该路由协议显著平衡了网中节点能耗,延长了网络生存时间。     

基于LEACH的WSNs分簇优化策略

针对LEACH算法中能量消耗不均匀的缺陷,本文提出了一种改进的路由协议来提高无线传感器网络的能量效率。在簇首选择阶段,引入节点剩余能量和初始能量来调节传感器节点随机数的大小;在成簇阶段,该算法将节点的剩余能量和距离汇聚节点的远近作为成簇的依据,使簇首的分布更加合理;在数据传输阶段,将节点与汇聚节点之间的距离及节点的剩余能量相结合,提出一种单跳与多跳相结合的传输方式,从而减少了能量消耗。仿真实验表明,改进后的算法能够更好的减少能耗,延长无线传感器网络的生命周期。     

节能高效的无线传感器网络非均匀分簇路由协议

为了有效均衡无线传感器网络能耗、缓解能量洞问题、延长网络生命周期,提出了一种节能高效的非均匀分簇路由协议,其核心思想是采用结合计时广播和簇头轮换机制的非均匀分簇（BR—EEUC）算法对网络分簇,并根据代价函数选择代价较低的簇头作为中继节点,形成以汇聚节点为根节点的多跳路由,从而大大降低了能量开销。通过在OMNet＋＋平台上的仿真实验结果表明：与LEACH和EEUC等路由协议相比,该协议有效地均衡了网络能量消耗,延长了网络寿命。     

基于蚁群的无线传感器网络能量均衡非均匀分簇路由算法

无线传感器网络(WSN)路由中,节点未充分考虑路径剩余能量及链路状况进行的路由会造成网络中部分节点网络寿命减少,严重影响网络的生存时间。为此,将蚁群优化算法与非均匀分簇路由算法相结合,提出一种基于蚁群优化算法的无线传感器非均匀分簇路由算法。该算法首先利用考虑节点能量的优化非均匀分簇方法对节点进行分簇,然后以需要传输数据的节点为源节点,汇聚节点为目标节点,利用蚁群优化算法进行多路径搜索,搜索过程充分考虑了路径传输能耗、路径最小剩余能量、传输距离和跳数、所选链路的时延和带宽等因素,最后选出满足条件的多条最优路径,完成源目的节点间的信息传输。实验表明,该算法充分考虑路径传输能耗和路径最小剩余能量、传输跳数及传输距离,能有效延长无线传感器网络的生存期。     

Time situate recurrence estimation technique for efficient data collection in war field sensor network

In a war field sensor network, the data collection process is based on the energy that exists in the sink node as well as in intermediate nodes. Since sensor nodes are typically much dense, data collected by sensor nodes have considerable redundancy. An effective data collection approach is developed to eliminate redundancy, reduce the number of broadcasts, and to save energy. We have deployed the new source-aware method to collect the data in a fast and efficient manner. The source- aware is needed at every node for sink conformation, which is used to find the correct next sink neighbor in the network. We propose a time situate recurrence estimation procedure (TSRE) with the support of uncertain rule sets to collect the data efficiently. This strategy follows the set of guidelines in which every node assigns different esteem for the configuration of the data collection and this range of esteems specify the feasible advantages of the data. Also, the strategy performs a time situate recurrence estimation procedure to complete the interruption identification framework with the assistance of a received sink pattern. This method recognizes the interruption effectively and produces favorable outcomes and also find a separate path in the network. In these ways all source nodes will assign each neighbor for data collection. In this network, every source will use node sink for data transmission in the system. Based on the received sink pattern, this approach improves the data collection efficiency of the task or the application being executed and reduces the energy consumption in the network. The novelty of this approach is verified by comparison with the existing method which shows enhancement in the throughput efficiency, data collection efficiency and delay minimization of the overall network.     

一种输出功率分级的无线传感网络数据收集机制

The data gathering manner of wireless sensor networks, in which data is forwarded towards the sink node, would cause the nodes near the sink node to transmit more data than those far from it. Most data gathering mechanisms now do not do well in balancing the energy consumption among nodes with different distances to the sink, thus they can hardly avoid the problem that nodes near the sink consume energy more quickly, which may cause the network rupture from the sink node. This paper presents a data gathering mechanism called PODA, which grades the output power of nodes according to their distances from the sink node. PODA balances energy consumption by setting the nodes near the sink with lower output power and the nodes far from the sink with higher output power. Simulation results show that the PODA mechanism can achieve even energy consumption in the entire network, improve energy efficiency and prolong the network lifetime.     

无线传感器网络多汇聚节点动态路径切换机制

为了解决在具有多个汇聚节点的传感器网络中由于节点能耗不均匀而产生一些节点能量提前耗尽的问题,提出一种节点动态路径切换机制.该机制利用梯度传输协议计算出每一个节点至各汇聚节点的成本字段,选出距离各节点最近和次近的汇聚节点并进行分群.节点在信息传输时将依据上游节点电力层级进行对比,动态选取较高电力层级的上游节点作为其下一跳节点,建立到最近或次近汇聚节点的传输路径.实验结果表明,采用该机制可以在不同来源产生环境下达到延长整个网络存活时间的效果.