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.     

点能量密度平衡的无线传感器网络基站移动策略

数据收集是无线传感器网络的一个基本功能。由于部署在基站周围的传感器节点承担着网络内大部分的负载,因此导致能量迅速耗尽,现有的基站移动策略可以通过基站的移动实现网络内传感器节点的负载平衡以延长网络寿命。但是现有负载平衡的基站移动策略只能在传感器节点被均匀布撒的情况下才能有效地延长网络寿命,其他情况下不能达到延长网络寿命的效果。因此本文定义了点能量概念用以表示传感器网络对感知区域每个点的感知能量,并给出了有效的点能量密度计算方法。通过点能量密度消耗分析,提出了一种点能量密度平衡的基站移动策略(energy-density-balance base stationmovement,简称EDB-BSM)。通过理论分析和仿真试验验证,相对于固定基站模式和基站随机移动模式,该移动策略能够在各种传感器节点分布情况下有效的延长网络寿命,并具有良好可扩展性。     

无线传感器网络中非均匀的节点布置

在无线传感器网络中,传感器节点将收集到的数据传输到簇头,经簇头聚合后数据包以多跳方式发送到基站。靠近基站的节点,因转发的数据较多而提早死亡,出现所谓的能量空洞问题。为此,对无线传感器网络中节点的能耗情况进行了研究,提出了一种非均匀的节点布置算法,得出了一个布置传感器节点的密度函数,在靠近基站的区域内布置较多的节点。仿真实验表明,非均匀的节点布置算法能有效延长网络的生命周期。     

Exact and approximate balanced data gathering in energy-constrained sensor networks

We consider the problem of gathering data from a wireless multi-hop network of energy-constrained sensor nodes to a common base station. Specifically, we aim to balance the total amount of data received from the sensor network during its lifetime against a requirement of sufficient coverage for all the sensor locations surveyed. Our main contribution lies in formulating this balanced data gathering task, studying the effects of balancing, and proposing an approximation algorithm for the problem. Based on an LP network flow formulation, we present experimental results on both optimal and approximate data routing designs, in open transmission ranges and with impenetrable obstacles between the nodes.     

EADEEG:能量感知的无线传感器网络数据收集协议

提出了一种基于簇结构的无线传感器网络数据收集协议EADEEG(an energy-aware data gathering protocol for wireless sensor networks).EADEEG通过最小化网络通信开销以及良好的能量负载平衡方法,可以有效地延长网络寿命.与以前的相关研究相比,EADEEG采用了一种全新的簇头竞争参数,能够更好地解决节点能量异构问题.此外,EADEEG也采用了一种简单而有效的簇内节点调度算法,通过控制活动节点的密度,可以在不增加额外控制开销的条件下关闭冗余节点并保证覆盖要求,因此可以进一步延长网络寿命.模拟实验证明,在节点初始能量同构和异构两种情况下,EADEEG协议都能够满足用户对覆盖率的要求,并在网络寿命上大幅度优于LEACH(low energy adaptive clustering hierarchy),PEGASIS(power-efficient gathering in sensor information systems)和DEEG(distributed energy-efficient data gathering and aggregation protocol)协议.     

Bio-inspired data transmission scheme to multiple sinks for the long-term operation of wireless sensor networks

Wireless sensor networks have a wide range of applications, such as natural environmental monitoring, object tracking, and environmental control in residential spaces or plants. In wireless sensor networks, many sensor nodes with limited resources are placed in an observation area and used to gather information about environments. Therefore, a data gathering scheme (or a routing algorithm) for saving and balancing the energy consumption of each sensor node is needed to prolong the lifetime of wireless sensor networks. This article proposes a new bio-inspired data transmission scheme for the long-term operation of wireless sensor networks. By using the proposed scheme, autonomous load-balancing data transmission to multiple sinks can be actualized. We evaluate the proposed scheme using computer simulations to verify its effectiveness, and also discuss its development potential.     

基于随机几何的网络拓扑密度控制模型研究

为同时保证无线传感器网数据的可靠传输,降低密集传感器网络中冗余的传输链路产生的节点之间的干扰对网络传输的影响,需要对网络的拓扑密度进行控制。本文基于节点的真实信道传输特性以及网络中节点的分布特征设计了基于随机几何的传感器网络拓扑密度控制模型,利用随机几何中的hard-core理论对拓扑密度控制后的节点稀释过程进行建模。最后,用蒙特卡洛仿真验证了网络中节点密度控制的结果。结果表明采用了拓扑控制后,网络中的干扰能耗更小。     

在有洞的无线传感器网络中移动基站轨迹的研究

数据收集是无线传感器网络的一个基本功能,由于部署在基站周围的传感器节点承担着网络内大部分的负载,因此导致能量迅速耗尽.但是现有的负载平衡的基站移动策略只能在传感器节点被均匀布撒的情况下才能有效地延长网络寿命.本文针对在含有洞的无线传感器网络区域中,提出了基站移动的4种轨迹,基站沿着边界之间的中轴线进行移动,把中轴线上的节点作为汇聚节点,可以降低包的丢失率.实验仿真结果表明,该算法不仅能平衡节点负载,提高包的接收率,也降低了网络能耗,延长了网络寿命.     

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。     

基于分簇机制的移动无线传感器网络数据采集协议*

为了均衡无线传感器网络的能量消耗,提出了一种基于分簇机制的移动无线传感器网络数据采集协议。该协议中,整个网络使用网格均匀分簇,节点根据加权能量—邻居规则选出分布在簇中间区域的簇头,簇头负责收集簇内兴趣事件并进行数据融合,移动sink依次运动到簇的中心点位置收集簇内兴趣事件。仿真结果表明,该协议有效地均衡了网络的能量消耗,延长了网络的生存时间。     

数据收集传感器网络的负载平衡网络构建方法

传感器网络所具有的集中式数据收集、多跳数据传输、多对一流量模式这3种特征会造成漏斗效应的出现,这会导致严重的包碰撞、网络拥塞、包丢失,甚至拥塞崩溃,还会导致能量消耗的热点的出现,使某些节点甚至整个网络过早死亡.负载平衡技术能够有效缓解漏斗效应的产生.针对静态数据收集传感器网络,基于供求网络的思想,提出了一种分布式算法,将传感器节点组织成交易平衡网络,用于平衡传感器节点的负载.利用这种方法组织而成的网络结构不是一棵负载平衡树,而是一个负载平衡网络.实验结果验证了这种方法的有效性.     

无线传感器网络中移动协助的数据收集策略

利用移动数据收集器(mobile data collector,简称MDC)进行传感器网络中感知数据的收集,可以有效地减少传感器将数据发送到静止基站的传输跳数,节约网络的能量,延长网络寿命.此外,MDC通过循环收集传感器数据或承担数据转发的功能,避免节点间由于多跳传输引起的能量空洞(energy hole)以及节点失效造成的传输链路中断等问题.MDC的移动性也为无线传感器网络的研究带来新的挑战.研究基于移动协助数据收集的无线传感器网络结构,分类总结了近年来提出的一些典型的基于MDC的算法和协议,着重讨论了MDC在网络能量、延迟、路由和传输等方面带来的性能变化.最后,进行了各种算法的比较性总结,针对传感器网络中MDC的研究提出了亟待解决的问题,并展望了其未来的发展方向.     

无线传感器网络疑误数据节点自动诊断方法

为了提高无线传感器网络疑误数据检测能力,提出基于轮换调度的无线传感器网络疑误数据节点自动诊断方法.通过采用分块区域特征匹配的方法,得到无线传感器网络疑误数据传输的梯度模型,采用资源优化分配方案,进行数据传输信道的均衡调度,得到节点部署分布模型.通过传感信息跟踪采样方法,得到采样信息分布,建立无线传感器网络疑误数据信息特...     

Data Gathering in Wireless Sensor Networks Via Regular Low Density Parity Check Matrix

A great challenge faced by wireless sensor networks (WSNs) is to reduce energy consumption of sensor nodes. Fortunately, the data gathering via random sensing can save energy of sensor nodes. Nevertheless, its randomness and density usually result in difficult implementations, high computation complexity and large storage spaces in practical settings. So the deterministic sparse sensing matrices are desired in some situations. However, it is difficult to guarantee the performance of deterministic sensing matrix by the acknowledged metrics. In this paper, we construct a class of deterministic sparse sensing matrices with statistical versions of restricted isometry property (StRIP) via regular low density parity check (RLDPC) matrices. The key idea of our construction is to achieve small mutual coherence of the matrices by confining the column weights of RLDPC matrices such that StRIP is satisfied. Besides, we prove that the constructed sensing matrices have the same scale of measurement numbers as the dense measurements. We also propose a data gathering method based on RLDPC matrix. Experimental results verify that the constructed sensing matrices have better reconstruction performance, compared to the Gaussian, Bernoulli, and CSLDPC matrices. And we also verify that the data gathering via RLDPC matrix can reduce energy consumption of WSNs.      

REMUDA: 一个实用地无线传感网络拓扑控制和数据转发机制

In wireless sensor networks, topology control plays an important role for data forwarding efficiency in the data gathering applications. In this paper, we present a novel topology control and data forwarding mechanism called REMUDA, which is designed for a practical indoor parking lot management system. REMUDA forms a tree-based hierarchical network topology which brings as many nodes as possible to be leaf nodes and constructs a virtual cluster structure. Meanwhile, it takes the reliability, stability and path length into account in the tree construction process. Through an experiment in a network of 30 real sensor nodes, we evaluate the performance of REMUDA and compare it with LEPS which is also a practical routing protocol in TinyOS. Experiment results show that REMUDA can achieve better performance than LEPS.     

基于ZigBee的无线传感器网络设计与实现

无线传感器网络是由部署在监测区域内大量的廉价微型传感器结点组成,具有传感器节点密度高,网络拓扑变化频繁,以及节点的功率、计算能力和数据存储能力有限等特点。该文介绍了ZigBee网络与GSM/GPRS网络相结合实现远程监测的无线传感器网络的软件与硬件总体设计方法。     

基于混合计算模型的分布式传感器网络数据收集

首先分析了传感器网络中两种计算模型的特点;然后针对装甲集群状态监控的实际需求,提出了基于无线传感器网络的装备状态监控系统的基本结构.分析了用于前端数据收集和传输的两层传感器网络的不同特点,结合client/server和移动agent模型的优点,提出基于混合计算模型的分布式传感器网络数据收集机制,在相对独立的车载监测网络中基于client/server模型建立数据收集机制,在车载监测网络之间基于移动agent模型建立数据收集机制.     

A Framework for Using Unmanned Aerial Vehicles for Data Collection in Linear Wireless Sensor Networks

The wireless sensor network (WSN) technology have been evolving very quickly in recent years. Sensors are constantly increasing in sensing, processing, storage, and communication capabilities. In many WSNs that are used in environmental, commercial and military applications, the sensors are lined linearly due to the linear nature of the structure or area that is being monitored making a special class of these networks; We defined these in a previous paper as Linear Sensor Networks (LSNs), and provided a classification of the different types of LSNs. A pure multihop approach to route the data all the way along the linear network (e.g. oil, gas and water pipeline monitoring, border monitoring, road-side monitoring, etc.), which can extend for hundreds or even thousands of kilometers can be very costly from an energy dissipation point of view. In order to significantly reduce the energy consumption used in data transmission and extend the network lifetime, we present a framework for monitoring linear infrastructures using LSNs where data collection and transmission is done using Unmanned Aerial Vehicles (UAVs). The system defines four types of nodes, which include: sensor nodes (SNs), relay nodes (RNs), UAVs, and sinks. The SNs use a classic WSN multihop routing approach to transmit their data to the nearest RN, which acts as a cluster head for its surrounding SNs. Then, a UAV moves back and forth along the linear network and transport the data that is collected by the RNs to the sinks located at both ends of the LSN. We name this network architecture a UAV-based LSNs (ULSNs). This approach leads to considerable savings in node energy consumption, due to a significant reduction of the transmission ranges of the SN and RN nodes and the use of a one-hop transmission to communicate the data from the RNs to the UAV. Furthermore, the strategy provides for reduced interference between the RNs that can be caused by hidden terminal and collision problems, that would be expected if a pure multihop approach is used at the RN level. In addition, three different UAV movement approaches are presented, simulated, and analyzed in order to measure system performance under various network conditions.     

基于SDMA应用的移动Sink节点的设计与实现

静态无线传感器网络(所有节点均为静止)不可避免地存在能量空洞(energy hole)、冗余覆盖(overlap)和热点(hot spot)等问题.在无线传感器网络中引入节点的移动性来解决上述问题.移动节点可以完成数据收集和转发等功能,有效地减少静态节点数据传输的跳数,节约静态节点的能量,延长网络的寿命.实现了一个基于ARM7内核的移动汇点DataTruck,具有容量大、速度快等特点.在此基础上引入SDMA(space-division multiple access)技术,在移动汇点上加入智能天线,使得该节点能同时接收同一频率上多个静态节点传输的数据.实验表明基于SDMA技术的移动汇点能高效地收集数据,并减少数据延时.     

A virtual infrastructure for large-scale wireless sensor networks

The primary goal of a wireless sensor network is to collect useful information from the network. Most wireless sensor networks are assumed that the number of nodes are very large and they should operate with confined resources. Consequently it is important to take a scalable and energy-efficient architecture.In this paper, we present Railroad, a data collection and topology management architecture for large-scale wireless sensor networks. It proactively exploits a virtual infrastructure called Rail, which acts as a rendezvous area of the event data and queries. By using Rail, Railroad achieves scalability and energy efficiency under dynamic conditions with multiple mobile observers and targets. We evaluate the communication cost and the hot area message complexity of Railroad and compare them with previous approaches. We evaluate communication cost of Railroad by both an analytic model and simulations.