基于蚁群优化解决传感器网络中的能量洞问题

基于多跳的无线传感器网络,越靠近sink的传感器节点因需要转发更多的数据,其能量消耗就越快,从而在sink周围形成了一种称为“能量洞”的现象.“能量洞”问题会导致整个网络由于内部节点能量过早耗尽而结束寿命,同时,网络中离sink较远的节点仍有大量能量剩余.研究“能量洞”现象,基于改进的分级环模型,总结出调节各环内节点的数据传输距离是实现网络节能的有效方法.证明搜索各区域最优的传输距离是一个多目标优化问题,即是NP难问题.从而提出一种基于蚁群优化的分布式算法,各区域根据其节点分布情况自适应地探索近似最优的传输距离,延长网络寿命.模拟实验结果表明,该算法在较短的时间内能够收敛到合理的解,并且得到的网络寿命接近于理想情况下的最优时间,与现有的类似算法相比,该算法提供了更长的网络寿命,并能适用于非均匀节点分布情况.     

基于免疫克隆的WSN能量空洞避免算法

基于同心环模型分析无线传感器网络中的能量空洞,描述动态最长-最短圆环寿命问题,建立该问题的数学模型,提出一种基于免疫克隆的能量空洞避免算法,通过寻找随着圆环宽度不断变化的最优传输距离序列来延长网络寿命。仿真结果表明,该算法能均衡网络能量消耗,有效提高网络寿命。     

解决无线传感器网络能量洞问题的贪婪算法

无线传感器网络中的能量洞问题是影响网络寿命的关键因素之一。在基于环模型的多跳传感器网络中,通过优化所有环的传输距离可以有效地延长网络寿命。提出了一种近似的贪婪算法（ASGT）,该算法将最优传输距离序列问题转化为最优生成树问题,在降低搜索（算法）复杂度的同时得到与最优解近似的结果。模拟实验证明了采用ASGT算法的网络寿命逼近于理想最优序列下的网络生命时间,并且与已有的文献算法相比,ASGT可以延长网络寿命两倍以上。     

Balancing Energy Consumption to Maximize Network Lifetime in Data-Gathering Sensor Networks

Unbalanced energy consumption is an inherent problem in wireless sensor networks characterized by multihop routing and many-to-one traffic pattern, and this uneven energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed data-gathering sensor networks. We formulate the energy consumption balancing problem as an optimal transmitting data distribution problem by combining the ideas of corona-based network division and mixed-routing strategy together with data aggregation. We first propose a localized zone-based routing scheme that guarantees balanced energy consumption among nodes within each corona. We then design an offline centralized algorithm with time complexity O(n) (n is the number of coronas) to solve the transmitting data distribution problem aimed at balancing energy consumption among nodes in different coronas. The approach for computing the optimal number of coronas in terms of maximizing network lifetime is also presented. Based on the mathematical model, an energy-balanced data gathering (EBDG) protocol is designed and the solution for extending EBDG to large-scale data-gathering sensor networks is also presented. Simulation results demonstrate that EBDG significantly outperforms conventional multihop transmission schemes, direct transmission schemes, and cluster-head rotation schemes in terms of network lifetime.     

基于网络效率的线性无线传感器网络优化部署算法

基于多跳的无线传感器网络,靠近sink的传感器节点因需要转发更多的数据,其能量消耗较多,从而在sink周围形成"能量空洞".采用更符合实际的单位部署成本的网络寿命,即网络效率作为优化目标.在仅已知网络规模和节点感知半径r的情况下,如何通过有效的节点部署来避免"能量空洞"并使网络效率最大,是一个极具挑战性的研究课题.提出了一种高效节点部署算法,求解出了最优工作节点数、最佳中继节点部署方案、最优节点传输距离.理论分析与模拟实验结果表明,算法不仅能够避免"能量空洞",而且相对于已有均匀与非均匀算法都能有效提高网络效率,因此该算法对构建低成本的无线传感网络应用系统具有重要意义.     

Avoiding Energy Holes in Wireless Sensor Networks with Nonuniform Node Distribution

In this paper, we investigate the theoretical aspects of the nonuniform node distribution strategy used to mitigate the energy hole problem in wireless sensor networks (WSNs). We conclude that in a circular multihop sensor network (modeled as concentric coronas) with nonuniform node distribution and constant data reporting, the unbalanced energy depletion among all the nodes in the network is unavoidable. Even if the nodes in the inner coronas of the network have used up their energy simultaneously, the ones in the outermost corona may still have unused energy. This is due to the intrinsic many-to-one traffic pattern of WSNs. Nevertheless, nearly balanced energy depletion in the network is possible if the number of nodes increases in geometric progression from the outer coronas to the inner ones except the outermost one. Based on the analysis, we propose a novel nonuniform node distribution strategy to achieve nearly balanced energy depletion in the network. We regulate the number of nodes in each corona and derive the ratio between the node densities in the adjacent (i + 1)th and ith coronas by the strategy. Finally, we propose (q-switch routing, a distributed shortest path routing algorithm tailored for the proposed nonuniform node distribution strategy. Extensive simulations have been performed to validate the analysis.     

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。     

A pre-determined node deployment strategy to prolong network lifetime in wireless sensor network

Energy is one of the scarcest resources in a wireless sensor network (WSN). Therefore, the need to conserve energy is of utmost importance in WSN. There are many ways to conserve energy in such a network. One fundamental way of conserving energy is judicious deployment of sensor nodes within the network area so that the energy flow remains balanced throughout the network. This avoids the problem of occurrence of ‘energy holes’ and ensures prolonged network lifetime. We have investigated the problem of uniform node distribution and shown its incapability to deal with the energy hole problem. Next we have derived the principle of non-uniform node distribution that ensures energy balancing. Further, we have developed a non-uniform, location-wise pre-determined node deployment strategy based on this principle leading to an increase in network lifetime. Finally exhaustive simulation is performed to substantiate our claim of energy balancing and subsequent enhancement of network lifetime. The results are compared with an existing work to prove the efficacy of our scheme.     

基于环的节点非均匀分布分簇算法

针对无线传感器网络（WSN）中基于环的节点非均匀分布网络模型下的能量空洞问题,提出了一种基于环的节点非均匀分布分簇算法（RCANND）。该算法在节点非均匀分布的网络模型下,通过每环的能耗最小化,计算每一环的最优簇首数;通过节点剩余能量、距基站距离以及与邻居节点的平均距离计算簇首选择度。在簇内以簇首选择度序列表进行簇首轮转,降低分簇次数,提高网络能量的利用效率。对提出的算法进行仿真对比实验,仿真结果表明,相同半径、不同分布模型下节点的平均能耗波动很小;相同分布模型、不同半径下节点的平均能耗波动也不明显。以网络中50%节点存活作为网络生命周期,在节点非均匀分布情况下,所提算法的网络生命周期比混合能量高效分布式不等分簇算法（UHEED）和轮转的混合能量高效分布式不等分簇算法（RUHEED）分别提高约18.1%和11.5%;在节点均匀分布模型下,所提算法的网络生命周期比基于分环的能量高效无线传感器网络分簇路由（RECR）协议提高约6.4%。所提算法有效均衡了不同分布模型下的能耗,有效延长了网络生命周期。     

WSN in cyber physical systems: Enhanced energy management routing approach using software agents

Recently, the cyber physical system has emerged as a promising direction to enrich the interactions between physical and virtual worlds. Meanwhile, a lot of research is dedicated to wireless sensor networks as an integral part of cyber physical systems. A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensors to monitor physical or environmental conditions. These autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. Shrinking size and increasing deployment density of wireless sensor nodes implies the smaller equipped battery size. This means emerging wireless sensor nodes must compete for efficient energy utilization to increase the WSN lifetime. The network lifetime is defined as the time duration until the first sensor node in a network fails due to battery depletion. One solution for enhancing the lifetime of WSN is to utilize mobile agents. In this paper, we propose an agent-based approach that performs data processing and data aggregation decisions locally i.e., at nodes rather than bringing data back to a central processor (sink). Our proposed approach increases the network lifetime by generating an optimal routing path for mobile agents to transverse the network. The proposed approach consists of two phases. In the first phase, Dijkstra’s algorithm is used to generate a complete graph to connect all source nodes in a WSN. In the second phase, a genetic algorithm is used to generate the best-approximated route for mobile agents in a radio harsh environment to route the sensory data to the base-station. To demonstrate the feasibility of our approach, a formal analysis and experimental results are presented.     

一种能耗均衡的WSN分布式拓扑博弈算法

无线传感器网络（wireless sensor network,WSN）中通常节点能量受限,节点间能耗不均衡会导致网络生命周期缩短.针对该问题,综合考虑节点的能量效率和能耗均衡,通过引入阿特金森指数设计了一种改进优化的综合效用函数;基于此,建立了一种能耗均衡的拓扑博弈模型,并证明了该拓扑博弈模型是序数势博弈且存在帕累托最优;提出了一种能耗均衡的WSN分布式拓扑博弈算法（DTCG）.通过仿真实验及对比分析表明,相较于其它基于博弈理论的拓扑控制算法,DTCG算法能在保证网络连通性和鲁棒性的前提下,降低节点发射功率,拥有更好的能量均衡性和能量效率,可以有效延长网络生命周期.     

基于Voronoi图的无线传感器网络覆盖空洞检测算法

针对无线传感器网络(WSN)中节点随机部署或部分节点能量耗尽带来的覆盖空洞(CH)问题,提出了一种基于Voronoi图的覆盖空洞检测算法。该算法利用节点的位置信息在覆盖区域范围内构建Voronoi图,通过计算每个Voronoi区域内的节点到该区域的顶点和边的距离来判断是否存在覆盖空洞,标识覆盖空洞的边界节点。仿真实验评估了不同节点分布密度、不同感知半径对空洞平均检测时间、平均能耗的影响,并与路径密度(PD)算法进行比较。实验结果表明所提算法在空洞平均检测时间和节点平均能耗两个方面均有10%左右的提升,对进一步延长网络生存期具有重要价值。     

基于萤火虫算法的无线传感器网络节点重部署策略

节点部署是无线传感器网络研究的重要问题之一.针对节点部署过程中的能量空洞问题,提出了一种基于萤火虫算法(FA)的节点重部署(NRBFA)策略.首先,在节点随机部署的传感器网络中,利用k-means算法进行分簇并引入冗余节点;然后,利用FA移动冗余节点,以分担簇头(CH)负载并均衡网络中节点的能耗;最后,再次利用FA寻找...     

无线传感器网络中节点非均匀分布的能量空洞问题

节点非均匀分布策略能缓解无线传感器网络中的能量空洞问题.文中从理论上探讨这种策略,证明在节点非均匀分布的圆形网络中,如果节点持续向Sink节点发送数据,能量空洞现象将无法避免,而当节点数目满足一定关系时,网络中能够实现次优能耗均衡.文中提出一种节点非均匀分布策略及相应的路由算法用于实现这种次优能耗均衡.模拟结果显示网络生存周期终止时,处于网络内部的节点几乎达到了能耗均衡.     

基于能耗量化传导的WSN路由探测算法

为了降低无线传感器网络(WSN)路由节点的能量损耗,提高网络的寿命周期,需要进行路由节点的优化分布设计。传统方法采用CSMA/CA有限竞争的信道分配模型进行WSN的路由探测算法设计,实现能量均衡,在节点规模较大和干扰较强时,节能的能耗开销较大。提出一种基于能耗量化传导的WSN路由探测算法,首先建立WSN的分簇能耗调度模型,以能量控制开销、丢包率、传输时延等为约束参量指标进行路由探测的控制目标函数的构建,然后采用路由冲突协调机制进行能耗量化分配,结合WSN传输信道的能量传导均衡模型实现WSN路由的优化探测和WSN节点的优化部署。仿真结果表明,采用该方法进行WSN路由探测设计时网络的能效较高,传输时延和误码率等参量指标的表现优于传统方法。     

Cost Minimization of Wireless Sensor Networks with Unlimited-lifetime Energy for Monitoring Oil Pipelines

Cyber-physical-system (CPS) has been widely used in both civil and military applications. Wireless sensor network (WSN) as the part and parcel of CPS faces energy problem because sensors are battery powered, which results in limited lifetime of the network. To address this energy problem, we take advantage of energy harvesting device (EHD) and study how to indefinitely prolong oil pipeline monitoring network lifetime by reasonable selecting EHD. Firstly, we propose a general strategy worst case-energy balance strategy (WC-EBS), which defines worst case energy consumption (WCEC) as the maximum energy sensor node could expend for oil pipeline monitoring WSN. When the energy collected by EHD is equal or greater than WCEC, network can have an unlimited lifetime. However, energy harvesting rate is proportional to the price of EHD, WC-EBS will cause high network cost. To reduce network cost, we present two optimization strategies, optimization workloadenergy balance strategy (OW-EBS) and optimization first nodeenergy balance strategy (OF-EBS). The main idea of OW-EBS is to cut down WCEC by reducing critical node transmission workload; OF-EBS confirms critical node by optimizing each sensor node transmission range, then we get the optimal energy harvesting rate in OF-EBS. The experimental results demonstrate that OF-EBS can indefinitely extend network lifetime with lower cost than WC-EBS and OW-EBS, and energy harvesting rate P in each strategy satisfies POF-EBS ≤ POW-EBS ≤ PWC-EBS.      

Lifetime elongation for wireless sensor network using queue-based approaches

A wireless sensor network (WSN) is envisioned as a cluster of tiny power-constrained devices with functions of sensing and communications. Sensors closer to a sink node have a larger forwarding traffic burden and consume more energy than nodes further away from the sink. The whole lifetime of WSN is deteriorated because of such an uneven node power consumption patterns, leading to what is known as an energy hole problem (EHP). From open literatures, most research works have focused on how to optimally increase the probability of sleeping states using various wake-up strategies. In this article, we propose a novel power-saving scheme to alleviate the EHP based on the N-policy M/M/1 queuing theory. With little or no extra management cost, the proposed queue-based power-saving technique can be applied to prolong the lifetime of the WSN economically and effectively. A mathematical analysis on the optimal control parameter has been made in detail. Focusing on many-to-one WSN, numerical and network simulation results validate that the proposed approach indeed provides a feasibly cost-effective approach for lifetime elongation of WSN.     

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。     

一种新的无线传感器网络非均匀分簇双簇头算法 ——PUDCH算法

能量利用效率问题一直是限制WSN广泛应用的瓶颈,能源容量对各个网络节点产生至关重要的影响.针对WSN中"能量空洞问题"以及由于簇头任务过重所导致的能量消耗过快,同时也为了提高WSN的能量利用效率,提出了一种无线传感器网络非均匀分簇双簇头算法——PUDCH.该算法先综合考虑节点综合信息(如节点剩余能量、节点到基站的距离),根据节点综合信息通过不同的时间竞争机制来选举簇头,将整个网络划分为不均匀的分簇;在规模大些的簇内,为了减轻簇头的负担再选取副簇头.最后簇头再构造基于最小生成树的最优传输路径.一系列的仿真表明PUDCH路由算法在WSN节约平衡节点能量消耗方面表现优良.     

基于博弈论能耗均衡的WSN非均匀分簇路由协议

在无线传感器网络(WSN)的分簇路由算法中,节点间能耗不均容易引发 “能量空洞”现象,影响整个网络的性能。针对这个问题,提出了一种基于博弈论能耗均衡的非均匀分簇路由(GBUC)算法。该算法在分簇阶段,采用非均匀分簇结构,簇的半径由簇头到汇聚节点的距离和剩余能量共同决定,通过调节簇头在簇内通信的能耗和转发数据的能耗来达到能耗的均衡;在簇间通信阶段,通过建立一个以节点剩余能量和链路可靠度为效益函数的博弈模型,利用其纳什均衡的解来寻找联合能耗均衡、链路可靠性的最优传输路径,从而提高网络性能。仿真结果表明:与能量高效的非均匀分簇(EEUC)算法和非均匀分簇节能路由(UCEER)算法相比,GBUC算法在均衡节点能耗、延长网络生命周期等性能方面有显著的提高。