Sink节点移动的三维无线传感网数据收集算法研究

为克服三维静态无线传感网中的能量空穴问题和提高网络生存时间,考虑Sink节点移动,提出一种Sink节点移动的三维无线传感网数据收集算法(DCA-TWSN),在DCA-TWSN中,提出三维环境下的正方体网格划分方法,建立包括Sink 移动路径选择约束、数据流量约束、能耗约束、链路约束等约束条件的数据收集优化模型,采用最优化方法求解已知Sink节点移动路径的数据收集优化问题,采用修正的蚁群算法求解Sink节点的移动路径问题,获得最优方案。仿真结果表明:不管Sink节点的最大数据收集跳数和传感节点数量如何变化,DCA-TWSN都能寻找到较优的移动路径和数据传输方案,从而提高了网络生存时间和传感节点的平均数据传输率,降低了移动路径长度、平均节点能耗方差和丢包率,比RAND、GREED和EDG-3D更优。     

面向带状无线传感网低延迟可靠数据收集算法

带状无线传感网为长距离带状分布，现有的数据收集算法无法很好解决其数据收集延迟较大的问题。提出了一种主动定位移动Sink的数据收集算法DCFAN（Data Collection based on Forwarding of Agent Nodes），DCFAN构建移动Sink的同步代理节点以及存储同步代理节点的线节点序列，通过获取同步代理节点转发感知数据到Sink汇聚点。仿真结果表明，DCFAN算法能有效降低网络节点能耗以及数据收集延迟，同时提升数据收集率，适用于对数据收集延迟具有一定要求的带状无线传感网应用场景。     

数据收集单元和移动Sink辅助下的信息上传方法

为提升无线传感网数据收集能效,提出了一种基于移动Sink节点的数据上传策略。网络被划分为若干由三个数据收集单元构成的虚拟区域,并在各区域中根据节点剩余能量及其与区域中心的距离远近选出簇头。在数据收集过程中,Sink以固定的速度在遍历点间移动,而仅有簇头节点向其上传数据,从而有效降低了能耗。     

WSN数据收集中移动Sink的路径规划和簇头节点选取问题的综合研究

针对较大规模的无线传感器网络通过多跳传输进行数据收集而引起的能量空洞问题,提出了一种基于移动Sink的簇头节点数据收集算法(MSRDG),该算法基于图论原理,在满足时延性的条件下,综合考虑了普通节点到簇头节点路由和移动Sink遍历路经选取的问题,构建了一条通过的簇头节点尽可能多的移动轨迹。通过NS-2仿真软件对算法的性能进行评估,结果显示出该算法能减少数据的多跳传输,降低无线传感器网络节点的能量消耗,延长网络寿命。     

优化网络生存时间的Sink节点移动路径选择算法

为克服无线传感网的能量空穴问题,采用最优化方法,研究一种优化网络生存时间的Sink节点移动路径选择算法(MPSA)。在MPSA算法中,将单跳传输的无线传感网监测区域分成多个大小一致的网格,Sink节点可移动到任一网格中心,停留收集单跳最大通信范围内的传感节点数据。分析停留位置的全节点覆盖条件和所有传感节点的能耗,建立权衡网络生存时间和Sink节点移动路程的优化模型。提出一种改进的遗传算法,用于求解优化模型,即迭代执行染色体评估、选择、交叉、变异、最小覆盖处理、孤立节点处理等步骤,最终获得优化网络生存时间的Sink节点移动方案。仿真结果表明:MPSA算法能提高网络生存时间,将移动路程保持在较小范围。在提高网络生存时间方面,比RCC算法更优。     

无线传感器网络中一种基于移动Sink的数据收集算法

针对移动无线传感器网络设计一种不依赖于节点地理位置的基于移动汇聚节点(Sink)的数据收集算法(Mobile Sink-based Data Gathering,MSDG)。该算法解决了无线传感器网络中多跳路由通信时出现能量空洞的"热点"问题。Sink沿途以最近的固定节点作为根节点动态构建路由树。簇内移动节点感知的数据经簇头进行数据融合计算,然后将融合后的数据沿路由树反向逐跳转发给Sink。仿真结果表明,MSDG在节点的平均能耗和网络生存时间等方面的性能远超过LEACH、ACE-L等数据收集协议。     

基于虚拟栅格的传感网能量空洞缓解方法

为延长无线传感网的生命期,提出了一种能量空洞缓解方法。网络被划分为若干虚拟栅格,以便于多跳传输。树形结构的数据上传路径则由各个簇头和移动Sink构成。此外,为缓解能量空洞的出现,Sink的移动轨迹被设计为可控的,从而有效均衡了能耗。仿真结果表明,该方法在多跳传感网络的节能方面表现较为良好。     

容忍延迟传感器网络中基于分簇的移动Sink动态路由算法

在无线传感器网络中使用移动Sink能有效延长网络寿命。提出一种在容忍延迟传感器网络中基于分簇的移动Sink动态路由算法MSDR（Mobile Sink Dynamic Routing）,移动Sink根据簇头位置构建遍历所有簇头的Hamilton回路,并沿着该路径收集数据。进一步提出基于标记的数据缓存机制,有效解决算法中每一轮之间的数据存储问题。仿真实验结果表明,MSDR算法使网络具有较长的生命周期,能有效平衡网络能耗。     

稀疏水下传感网中AUV数据移动收集技术研究

由于水下传感器节点的水声通信距离有限、价格昂贵,水下传感器网络中一般采用稀疏方式部署,因此很难保证整体网络的连通性及数据采集效率。自主水下航行器AUV（Autonomous Underwater Vehicle）作为天然的移动数据采集平台,可以弥补固定Sink节点数据采集方式的缺陷。提出了一种基于移动AUV的水下传感网移动数据收集机制。以AUV覆盖区域内的传感器节点作为临时Sink节点,其他传感器节点以临时Sink节点为根节点,采用最小生成树MST（Minimum Spanning Tree）方法将传感数据传输到这些临时Sink节点,然后通过临时Sink节点将汇聚数据传输给AUV。随着AUV的自主移动轨迹,水下传感网的传感数据都能简单高效地被收集起来。仿真结果验证了该方法在保证网络能耗的前提下提高了数据采集效率。     

一种无线传感网的Sink节点移动路径规划算法研究

为寻找传感节点均匀分布时Sink节点的最优移动路径和最大网络生存时间,提出一种无线传感网的Sink节点移动路径规划算法(MPOA).在MPOA算法中,将Sink节点的数据收集范围分解成多个圆环,将监测区域分解成多个网格.根据Sink节点的停留位置和多跳通信方式,采用数学公式表示每一个网格的单位节点能耗,从而获得Sink节点移动的网络生存时间优化模型.采用修正的混合粒子群算法求解该优化模型,获得网络生存时间、Sink节点的停留位置和移动路径的最优方案.仿真结果表明:MPOA算法可寻找到Sink节点的最优移动路径,从而平衡网络能耗,提高网络生存时间.在一定的条件下,MPOA算法比Circle,Rect和Rand算法更优.     

WSN数据收集中移动sink的路径规划和蔟头节点选取问题的综合研究

针对较大规模的无线传感器网络通过多跳传输进行数据收集而引起的能量空洞问题,本文提出了一种基于移动sink的簇头节点数据收集算法（MSRDG）,该算法基于图论原理,在满足时延性的条件下,综合考虑了普通节点到簇头节点路由和移动sink遍历路经选取的问题,构建了一条通过的簇头节点尽可能多的移动轨迹。通过NS-2仿真软件对算法的性能进行评估,结果显示出该算法能减少数据的多跳传输,降低无线传感器网络节点的能量消耗,延长网络寿命。     

An efficient trajectory design for mobile sink in a wireless sensor network

Mobile sink trajectory plays a pivotal role for network coverage, data collection and data dissemination in wireless sensor networks. Considering this, we propose a novel approach for mobile sink trajectory in wireless sensor networks. Our proposed approach is based on Hilbert Space Filling Curve, however, the proposed approach is different from the previous work in a sense that the curve order changes according to node density. In this paper, we investigate the mobile sink trajectory based on Hilbert Curve Order which depends upon the size of the network. Second, we calculate the Hilbert Curve Order based on node density to re-dimension the mobile sink trajectory. Finally, we perform extensive simulations to evaluate the effectiveness of proposed approach in terms of network coverage and scalability. Simulation results confirm that our proposed approach outperforms with size based Hilbert Curve in terms of network coverage, packet delivery ratio and average energy consumption.     

Termite-hill: Performance optimized swarm intelligence based routing algorithm for wireless sensor networks

A wireless sensor network (WSN) is a large collection of sensor nodes with limited power supply, constrained memory capacity, processing capability, and available bandwidth. The main problem in event gathering in wireless sensor networks is the formation of energy-holes or hot spots near the sink. Due to the restricted communication range and high network density, events forwarding in sensor networks is very challenging, and require multi-hop data forwarding. Improving network lifetime and network reliability are the main factors to consider in the research associated with WSN. In static wireless sensor networks, sensors nodes close to the sink node run out of energy much faster than nodes in other parts of the monitored area. The nodes near the sink are more likely to use up their energy because they have to forward all the traffic generated by the nodes farther away to the sink. The uneven energy consumption results in network partitioning and limit the network lifetime. To this end, we propose an on-demand and multipath routing algorithm that utilizes the behavior of real termites on hill building termed Termite-hill which support sink mobility. The main objective of our proposed algorithm is to efficiently relay all the traffic destined for the sink, and also balance the network energy. The performance of our proposed algorithm was tested on static, dynamic and mobile sink scenarios with varying speed, and compared with other state-of-the-art routing algorithms in WSN. The results of our extensive experiments on Routing Modeling Application Simulation Environment (RMASE) demonstrated that our proposed routing algorithm was able to balance the network traffic load, and prolong the network lifetime.     

An improved ant colony optimization-based approach with mobile sink for wireless sensor networks

Traditional wireless sensor networks (WSNs) with one static sink node suffer from the well-known hot spot problem, that of sensor nodes near the static sink bear more traffic load than outlying nodes. Thus, the overall network lifetime is reduced due to the fact some nodes deplete their energy reserves much faster compared to the rest. Recently, adopting sink mobility has been considered as a good strategy to overcome the hot spot problem. Mobile sink(s) physically move within the network and communicate with selected nodes, such as cluster heads (CHs), to perform direct data collection through short-range communications that requires no routing. Finding an optimal mobility trajectory for the mobile sink is critical in order to achieve energy efficiency. Taking hints from nature, the ant colony optimization (ACO) algorithm has been seen as a good solution to finding an optimal traversal path. Whereas the traditional ACO algorithm will guide ants to take a small step to the next node using current information, over time they will deviate from the target. Likewise, a mobile sink may communicate with selected node for a relatively long time making the traditional ACO algorithm delays not suitable for high real-time WSNs applications. In this paper, we propose an improved ACO algorithm approach for WSNs that use mobile sinks by considering CH distances. In this research, the network is divided into several clusters and each cluster has one CH. While the distance between CHs is considered under the traditional ACO algorithm, the mobile sink node finds an optimal mobility trajectory to communicate with CHs under our improved ACO algorithm. Simulation results show that the proposed algorithm can significantly improve wireless sensor network performance compared to other routing algorithms.     

能量有效和延迟敏感的无线传感器网络数据收集协议

利用移动Sink进行数据收集是无线传感器网络数据收集的一个趋势。本文提出一种能量有效、延迟敏感的移动数据收集协议（Energy—efficient and Delay—Sensitive Data Gathering Protocol for Wireless Sensor Networks,简称EEDS）。EEDS中,移动Sink在网络中穿行,从代理节点收集传感器节点监测到的数据。为了减少数据收集的延迟,采用类TSP（Traveling Salesman Problem）的解决方法,确保移动Sink在各个代理节点中收集数据时,始终选择一条最短路径在网络中行走。模拟仿真表明,提出的数据收集协议在延长网络生命周期以及减少数据收集延迟方面都有显著的优势。     

Particle swarm optimization based clustering algorithm with mobile sink for WSNs

Wireless sensor networks with fixed sink node often suffer from hot spots problem since sensor nodes close to the sink usually have more traffic burden to forward during transmission process. Utilizing mobile sink has been shown as an effective technique to enhance the network performance such as energy efficiency, network lifetime, and latency, etc. In this paper, we propose a particle swarm optimization based clustering algorithm with mobile sink for wireless sensor network. In this algorithm, the virtual clustering technique is performed during routing process which makes use of the particle swarm optimization algorithm. The residual energy and position of the nodes are the primary parameters to select cluster head. The control strategy for mobile sink to collect data from cluster head is well designed. Extensive simulation results show that the energy consumption is much reduced, the network lifetime is prolonged, and the transmission delay is reduced in our proposed routing algorithm than some other popular routing algorithms.     

无线传感器网络中基于数据融合的移动代理曲线动态路由算法研究

和传统的C/S模型相比,移动代理模型在数据融合方面更适合无线传感器网络.在基于移动代理的数据融合算法中,移动代理访问传感节点的顺序以及总数对算法的效率、网络寿命等有着重大影响.为此提出了一种基于数据融合的移动代理曲线动态路由算法设计方案.通过构造特定数据结构的数据报文和数据表,给出了目标节点基本信息收集算法获取目标节点到处理节点的最优路径;将移动代理路由归结为一个优化问题,由静态路由算法求出移动代理迁移的静态最优路由节点序列,进而获得了移动代理基于曲线的动态路由算法.理论分析和模拟实验表明,随着传感器网络规模的增大和传感数据量的增加,和其它算法相比,该算法有更小的网络耗能和延时.     

Sink轨迹固定传感器网络的高效数据采集机制

在sink移动轨迹固定的传感器网络中,由于sink点有限的通信时间和节点的随机分布,使得很难兼顾数据采集量的提高和整体能耗的降低.为了解决该问题,提出了一种最大数据量最短路径(maximum amount shortest path,简称MASP)数据采集方法.MASP对网络中成员节点与sub-sink节点之间的匹配关系进行集中式优化.采用0-1线性规划方法对MASP问题进行形式化描述,提出了一种基于二维染色体编码的遗传算法进行求解,并给出了相应的数据通信协议设计.另外,MASP可以扩展支持低密度网络和多sink点网络.基于OMNET++的仿真结果表明,MASP在能耗利用率方面要远远优于最短路径树方法(shortest path tree,简称SPT)及固定sink数据采集方法.     

密集型传感器网络中移动sink的路径选择机制

针对密集型无线传感器网络,以最大化网络寿命为优化目标,将网络转换成相应的网络流图,利用网络最大流问题估算sink采用不同路径下的网络寿命并以此为标准进行路径选择,提出了一种基于网络流理论的高效sink路径选择机制。仿真结果表明,本方案同采用固定路径采集及类似解决方案相比,能有效均匀网络能耗,延长网络寿命,取得了较好的网络性能。     

面向动态传感器网络的数据汇集算法

传感器网络中移动终端广泛存在,针对无线传感器网络移动Sink场景,提出一种移动Sink代理机制和网络质量评估策略.根据网络质量决定Sink的移动路径,并在此基础上,从能量均衡的角度提出一种基于角度的数据汇集算法ADC-MS(Angle-based Data Collection algorithm for Mobile...