用于移动汇聚节点的自适应数据采集策略

移动汇聚节点用于无线传感网络信息采集,可以提高网络能效性,延长网络生命期。研究了四轴飞行器携带 移动汇聚节点,该节点可采集地面无线传感网数据。通过分析汇聚节点空中移动特性,探讨了低功耗无线数据采集 时,移动轨迹、速率和高度与移动汇聚节点能够发送的数据量的之间的理论约束条件。在满足约束条件前提下,提出 基于数据量局部最优化策略,用以控制移动汇聚节点移动路径。在仿真环境中,详尽分析了这种数据采集策略下逗留 时间与移动轨迹、速度和高度等之间的关系,为这类应用莫定了理论基础。     

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。     

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。     

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...     

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.     

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.     

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。     

EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks

In recent years, there has been a growing interest in wireless sensor networks. One of the major issues in wireless sensor network is developing an energy-efficient clustering protocol. Hierarchical clustering algorithms are very important in increasing the network’s life time. Each clustering algorithm is composed of two phases, the setup phase and steady state phase. The hot point in these algorithms is the cluster head selection. In this paper, we study the impact of heterogeneity of nodes in terms of their energy in wireless sensor networks that are hierarchically clustered. We assume that a percentage of the population of sensor nodes is equipped with the additional energy resources. We also assume that the sensor nodes are randomly distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. Homogeneous clustering protocols assume that all the sensor nodes are equipped with the same amount of energy and as a result, they cannot take the advantage of the presence of node heterogeneity. Adapting this approach, we introduce an energy efficient heterogeneous clustered scheme for wireless sensor networks based on weighted election probabilities of each node to become a cluster head according to the residual energy in each node. Finally, the simulation results demonstrate that our proposed heterogeneous clustering approach is more effective in prolonging the network lifetime compared with LEACH.     

基于可预测移动汇聚节点的无线传感网分簇算法研究

在汇聚节点移动可预测情况下,提出一种无线传感网分簇算法。该算法将subsink节点引入到HEED分簇算法中,以较快感知移动路径变化,快速形成分簇拓扑;采用sink节点注册机制,实现汇聚节点移动过程中的信息交互。实例分析表明,该算法能快速形成合理网络拓扑,延长无线传感网的生存期。     

A smart node architecture for adding mobility to wireless sensor networks

Adding a few mobile nodes into the conventional wireless sensor networks can greatly improve the sensing and control capabilities of the networks and can help researchers solve many challenges such as network deployment and repair. This paper presents an enhanced node architecture for adding controlled mobility to wireless sensor networks. The structural model, the power model and the networking model of the proposed mobile node have been built respectively for better node control. And it provides a novel robotic platform for experimental research in hybrid sensor networks or other distributed measurement and control systems. A testbed has finally been created for validating the basic functions of the proposed mobile sensor node. The results of a coverage experiment show that the mobile node can provide additional support for network coverage and can ensure that the sensor network will work properly in undesirable environments.     

A honeycomb structure based data gathering scheme with a mobile sink for wireless sensor networks

With the widespread use of wireless sensor networks, more and more applications require energy efficient and low packet loss rate data collection methods. Recently, the concept of ‘mobile’ is introduced in various mechanisms to meet the needs of this kind. In this paper, a honeycomb structure based data gathering scheme, HSDG, is proposed for wireless sensor networks with a mobile sink. By partitioning the network into a honeycomb structure and giving each partition a direction value, every sensor node can obtain the latest location of the mobile sink dynamically with a small amount of broadcasting overhead. HSDG uncouples the moving strategy of mobile sink from the data forwarding mechanism, and three subscheme HSDG_RM, HSDG_DGM, and HSDG_EGM are proposed. Our schemes are investigated from average energy consumption, maintenance cost, packet loss rate and the number of packets collected. Compared with BTDG and ALURP, HSDG_DGM is the most energy efficient with a low packet loss rate.     

基于轨迹受限的移动Sink低能耗数据收集协议

无线传感器网络数据收集的能耗问题一直以来都是研究的热点。本文主要研究基于移动Sink轨迹受限的数据收集协议。首先针对轨迹受限的无线传感网络提出一种通用的系统模 型,将该问题形式化为最大化降低全网总路径长度轨迹设计问题 (Maximizing total length reduction for constrained trajectory, MTRC),并证明了MTRC为NP-Hard问题;然后设计一种轨迹约束低能耗贪心算法 (Trajectory constrain of low energy consumption, TCLEC),通过 TSP近似算法设计最大化降低有效长度的Sink移动轨迹。理论分析和仿真实验结果表明,TCLEC在网络拓扑数据收集树的初始化以及优化方面是高效的,并且相对于同类基于移动Sink的无线传感网络分层数据收集方法,其能耗降低了7%左右。     

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.     

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。     

数据传输时延和跳数受限的Sink节点移动路径选择算法

考虑实际无线传感网系统中数据传输时延和跳数受限情况,且为降低算法的时间复杂度,提出一种移动无线传感网的Sink节点移动路径选择算法（MPSA）。在MPSA算法中,Sink节点采用分布式最短路径树算法收集k+1跳通信范围内传感节点的相关信息和感知数据,采用虚拟力理论计算边界、障碍物和空洞区域的虚拟斥力、第k+1跳未覆盖传感节点的虚拟引力和所有虚拟力的合力,根据停留次数、合力大小和方向等信息计算当前网格中心的停留时间和下一个停留网格中心。仿真结果表明：MPSA算法根据传感节点的位置、剩余能量等信息,寻找到一条较优的移动路径,从而提高Sink节点的数据收集量和节点覆盖率,降低传感节点的感知数据丢弃量。总之,在数据传输时延和跳数受限下,MPSA算法比RAND算法、GMRE算法和EASR算法更优。     

移动Sink的传感器网络路径优化策略

在无线传感器网络（WSNs）中引入移动 Sink 可以避免网络拥塞和能量空洞并降低网络能耗,但由于移动速度的限制导致时延较大。针对这一问题,提出了时延约束下的移动 Sink 路径优化策略,根据时延和网络能耗之间的关系设计了可调节的节点权重,通过模拟退火遗传算法得到最优节点权重,并依据此权重通过迭代得到汇聚节点和最佳移动路径。仿真结果表明：该策略能保证在满足时延约束的前提下降低网络能耗,且收敛速度快。     

基于活动区域的移动无线传感器网络路由协议

为了解决移动无线传感器网络中能量效率问题,提出了一种基于活动区域的移动无线传感器网络（WSN）路由协议。本方法使用源和sink节点相对位置来形成路由的活动区域,网络中的移动节点使用睡眠唤醒模式来节约能源。移动向量信息（如当前位置、方向和速度）以及节点的剩余能量,用于选择能够提供最大连接保留时间的邻居,移动向量信息也被用来唤醒活动区域中的移动节点。实验表明,与其他路由协议进行比较,该方法在分组传输过程中具有更高的可靠性。     

基于不均匀环带模型能量有效的无线传感器网络节点放置方法

采用相同无线发射半径的无线传感器网络,距离sink较近的节点由于承担大量数据包的转发任务,易过早死亡.根据节点距离sink的位置,结合网络流量特征,提出基于不均匀环带模型的节点放置策略和无线通信半径的确定方法.仿真结果表明,在相同的系统参数条件下,不均匀环带模型既可降低所有节点的总能耗,又可降低最内环节点能耗,有效延长网络生命周期.     

Efficient data-forwarding method in delay-tolerant P2P networking for IoT services

These days Internet of Things (IoT), which consists of smart objects such as sensor nodes is the most important technology for providing intelligent services. In the IoT ecosystem, wireless sensor networks deliver collected information from IoT devices to a server via sink nodes, and IoT services are provided by peer-to-peer (P2P) networking between the server and the IoT devices. Particularly, IoT applications with wide service area requires the mobile sink nodes to cover the service area. To employ mobile sink nodes, the network adopts delay-tolerant capability by which delay-tolerant nodes try to transmit data when they connect to the mobile sink node in the application service field. However, if the connection status between a IoT device and a mobile sink node is not good, the efficiency of data forwarding will be decreased. In addition, retransmission in bad connection cause high energy consumption for data transmission. Therefore, data forwarding in the delay-tolerant based services needs to take the connection status into account. The proposed method predicts the connection status using naïve Bayesian classifier and determines whether the delay tolerant node transmits data to the mobile sink node or not. Furthermore, the efficiency of the proposed method was validated through extensive computer simulations.     

一种移动无线视频传感器节点的覆盖算法

在现有的无线传感器网络覆盖算法的研究中,缺乏对移动节点路径规划的研究,而针对具有视频传感器节点的网络仍使用普通传感器圆形覆盖区域的测量方法来计算覆盖面积,并不完全符合实际情况.基于这两方面的原因,本文提出了一种适用于无线视频传感器节点的最大覆盖算法,并提出一种对于视频传感器节点覆盖面积的计量方法.该算法能够使节点在保证网络连通性的前提下,达到最大的有效监测范围.此外,本文建立了相应的仿真实验模型,对该算法的有效性和覆盖面积进行了实验与分析.结果表明,本算法的节点监测面积大约为使用随机运动算法的节点监测面积的1.5倍左右,并可以保证网络的连通性.