Energy-aware scheduling for information fusion in wireless sensor network surveillance

Effective energy control while maintaining reliable monitoring performance becomes a key issue in wireless sensor networks (WSNs) based surveillance applications. While importance difference of surveillance zone, limited energy and dynamic network topology pose great challenges to surveillance performance. It is necessary to adjust sensor nodes' awakening frequency dynamically for information fusion. Thus an energy-aware scheduling with quality guarantee method named ESQG is proposed in this paper which considers sensor nodes' residual energy, different importance degrees of the surveillance zone and network topology comprehensively. It first uses a Voronoi diagram to determine the effective scope of each sensor node and then calculates node importance according to its residual energy and the importance degree of the effective scope. Then ESQG utilizes the importance of individual sensing scope and current forwarding costs to further compute node importance and awakening frequency for information fusion. In this way, ESQG can dynamically adapts each nodes awakening frequency to its dynamic network topology and importance degree of each individual sensing scope. The nodes are then turned on stochasticlly via the node awakening probability and node importance based information fusion is conducted for target detection. Besides, an adaptive process of perception factor C is proposed to match actual situation, and automatically change according to the detected data. Experiments results demonstrate that the proposed method ESQG can reduce the number of awakening nodes to a large extent while maintaining high reliability via information fusion.     

Connectivity and coverage maintenance in wireless sensor networks

One of the main design challenges for wireless sensor networks (WSNs) is to obtain long system lifetime without sacrificing system original performance such as communication connectivity and sensing coverage. A large number of sensor nodes are deployed in redundant fashion in dense sensor networks, which lead to higher energy consumption. We propose a distributed framework for energy efficient connectivity and coverage maintenance in WSNs. In our framework, each sensor makes self-scheduling to separately control the states of RF and sensing unit based on dynamic coordinated reconstruction mechanism. A novel energy-balanced distributed connected dominating set algorithm is presented to make connectivity maintenance; and also a distributed node sensing scheduling is brought forward to maintain the network coverage according to the surveillance requirements. We implemented our framework by C++ programming, and the simulation results show that our framework outperforms several related work by considerably improving the energy performance of sensor networks to effectively extend network lifetime.     

无线传感器网络能量均衡拓扑模型研究

针对BA模型仅考虑节点寿命对网络拓扑结构影响的现状,考虑到拓扑能量利用率不高会缩短网络生命周期,在分析网络平均剩余能量和通信半径对网络生命周期影响的基础上,提出一种无线传感器网络能量均衡拓扑模型.该模型在拓扑演化过程中,综合考虑节点剩余能量、通信半径和节点度,并引入剩余能量调节参数、通信半径调节参数和节点度调节参数,最终使剩余能量大的节点连接概率更高.理论分析和仿真实验结果表明,该模型不仅具有无标度网络的幂律特性,具有较好的稳定性,且能够均衡节点和网络能耗,延长网络的生命周期.     

一种能量有效的传感器监测网络成簇协议

提出了一种分布式能量有效的传感器监测网络成簇协议EECTS(energy-efficient clustering protocol for target surveillance).在该协议中,节点根据邻居节点的分布情况以及自己的剩余能量来竞争簇首.为了降低簇首的能量消耗,簇首间形成一个以基站为根的最小生成树,将监测到的数据通过多跳方式直接发送到生成树的上游节点.由于监测网络的首要任务是能够对移动目标进行不间断的监测,此协议还提出了一种簇内调度方法EECTS-1,可监测到网络中的大部分区域,并在此基础上提出了改进方法EECTS-2.这两种方法在目标进入网络时都能取得较高的持续监测度.随着节点密度的提高,EECTS协议在保证监测性能的前提下,使得传感器监测网络的寿命相应于节点数量呈线性增长.仿真结果表明,在监测性能相同的情况下,运行EECTS-1协议的网络寿命与HEED协议相同,比DEEG协议的网络寿命延长了约35%。EECTS-2协议比EECTS-1和HEED协议的网络寿命延长了约70%～80%.EECTS成簇协议可应用于军事目标监测等领域,工作时间长,监测结果具有很高的可靠性.     

基于小世界模型的WSN簇间拓扑优化方法

针对无线传感器网络节点因能量消耗、硬件故障、通信因素等导致的链路失效问题,提出一种基于复杂网络小世界模型Kleinberg的无线传感器网络簇间拓扑优化方法,该方法依据簇头节点的局部视图ViewList信息中的长链与短链构建WSN簇间拓扑.实验分析表明,利用该方法演化的无线传感器网络拓扑在节点失效概率为0.2时,网络寿命比DECDC提高25%,并具有良好的能量均衡性和较低的消耗代价.该方法构建的拓扑具有较好的容错性和较强的鲁棒性.     

IRPL: An energy efficient routing protocol for wireless sensor networks

This study aims to overcome the disadvantages of the original RPL (IPv6 Routing Protocol for Low power and Lossy networks) routing protocol (RPL including problems with energy consumption and energy load balance). We developed a relatively balanced RPL – the improved protocol (IRPL). This protocol is based on an efficient clustering algorithm and an effective topology control model of the loop domain communication route. The clustering algorithm can be used to calculate the optimal number of cluster heads by assumption of the network model. Combined with the clustering probability model and the node competition mechanism, the cluster head node in the wireless sensor network was used to complete the clustering process. In the topology control model, the wireless sensor network was divided into concentric rings with equal areas. Nodes determined the best network route, depending on different levels of ring domain and the optimal forwarding communication area defined in this study. Simulation results indicate that the IRPL routing protocol can reduce overall network energy consumption, balance network energy consumption, and prolong network lifetime.     

Energy-efficient mobile target detection in Wireless Sensor Networks with random node deployment and partial coverage

This paper addresses the problem of engineering energy-efficient target detection applications, using unattended Wireless Sensor Networks (WSNs) with random node deployment and partial coverage, for long-lasting surveillance of areas of interest. As battery energy depletion is a crucial issue, an effective approach consists in switching on and off, according to proper duty cycles, sensing and communication modules of wireless sensor nodes. Making these modules work in an intermittent fashion has an impact on (i) the latency of notification transmission (depending on the communication duty cycle), (ii) the probability of missed target detection (depending on the number of deployed nodes, the sensing duty cycle, and the number of incoming targets), and (iii) the delay in detecting an incoming target. In order to optimize the system parameters to reach given performance objectives, we first derive an analytical framework which allows us to evaluate the probability of missed target detection (in the presence of either single or multiple incoming targets), the notification transmission latency, the detection delay, and the network lifetime. Then, we show how this “toolbox” can be used to optimally configure system parameters under realistic performance constraints.     

Lifetime extension for surveillance wireless sensor networks with intelligent redeployment

For wireless sensor networks (WSNs), uneven energy consumption is a major problem. A direct consequence of this is the energy hole problem, formation of sensing voids within the network field due to battery depleted sensors in the corresponding region. Hole formations are inherent in the network topology, yet it is possible to develop strategies to delay the hole formations to later stages of the network operation and essentially extend the network lifetime without sensing quality loss. In this work, we initially propose and analyze an approach that can be used to mitigate the hole problem. The approach is presented in detail and the effects on the sustained surveillance quality are presented. The results are based on simulations with different network configurations with realistic sensor models, MAC and routing protocols. By using the proposed approach, sustaining a sensing quality above a given threshold and more than doubling the network lifetime are possible. The results clearly indicate the suitability of the approach for especially demanding WSNs such as the ones used for border surveillance tasks.     

SNs中面向定位应用的参考点覆盖性能研究*

由于传感器节点具有传感与通信两个功能,基于传感器网络的定位参考点选择不能仅仅考虑定位性能或网络通信性能,根据不同的传感半径与通信半径选择不同的设置方案成为一个亟待解决的问题。为此,对比分析了三种常见的规则网络拓扑结构的性能,提出了一种参考点设置方法。实验结果表明只有依据通信半径与传感半径的关系设置参考点才能够达到较优的覆盖效果。     

A tree-based topology construction algorithm with probability distribution and competition in the same layer for wireless sensor network

Topology construction is an efficient strategy to save energy and extend lifetime in wireless sensor networks. In this paper, a theorem of probability distribution about the number of nodes in each layer is proposed and discussed with theoretical verification. Then a tree-based topology construction algorithm with probability distribution and competition in the same layer (PCLT) is proposed for reducing communication packets and energy consumption. PCLT calculates the weighted value of nodes through broadcasting messages and selects the best parent node using competition method in the same layer. Furthermore, the secondary waken strategy is given to make a decision of which node needs to be waken up in terms of its probability distribution. The effectiveness of the PCLT algorithm is verified by the simulation results. Compared with EECDS, A3 and EBCDS algorithms, it has competitive edges in number of backbone nodes, energy consumption, and number of messages as well as the network lifetime.     

Design of fault tolerant wireless sensor networks satisfying survivability and lifetime requirements

Sensor networks are deployed to accomplish certain specific missions over a period of time. It is essential that the network continues to operate, even if some of its nodes fail. It is also important that the network is able to support the mission for a minimum specified period of time. Hence, the design of a sensor network should not only provide some guarantees that all data from the sensor nodes are gathered at the base station, even in the presence of some faults, but should also allow the network to remain functional for a specified duration. This paper considers a two-tier, hierarchical sensor network architecture, where some relay nodes, provisioned with higher power and other capabilities, are used as cluster heads. Given a distribution of sensor nodes in a sensor network, finding the locations to place a minimum number of relay nodes such that, each sensor node is covered by at least one relay node, is known to be a computationally difficult problem. In addition, for successful and reliable data communication, the relay nodes network needs to be connected, as well as resilient to node failures. In this paper, a novel integrated Integer Linear Program (ILP) formulation is proposed, which, unlike existing techniques, not only finds a suitable placement strategy for the relay nodes, but also assigns the sensor nodes to the clusters and determines a load-balanced routing scheme. Therefore, in addition to the desired levels of fault tolerance for both the sensor nodes and the relay nodes, the proposed approach also meets specified performance guarantees with respect to network lifetime by limiting the maximum energy consumption of the relay nodes.     

无线传感器网络最大生命期通信模型研究*

提出一种新的无线传感器网络最大生命期通信模型,研究了无线传感器网络中多源多链路多基站的最大生命期问题.为均衡数据流量分布,源节点产生的数据可以通过多条链路转发到多个基站.针对无线传感器网络能量和带宽受限等多约束条件,建立以网络最大生命期为最优目标和以降低节点处的数据量为次优目标的线性规划模型,依靠现有的分布式算法解决该模型.通过仿真实验验证了通信模型在多基站环境中的性能,并表明所提出的模型能够有效地延长网络生命期.     

Maximizing network lifetime in wireless sensor networks with regular topologies

Limited energy supply (battery-powered) is a crucial problem in wireless sensor networks (WSNs). Sensor node placement schemes and routing protocols are mostly proposed to address this problem. In this paper, we first present how to place sensor nodes by use of a minimal number of them to maximize the coverage area when the communication radius of the sensor node is different from the sensing radius, which results in the application of regular topology to WSNs deployment. With nodes placed at an equal distance and equipped with an equal power supply, the problem of unbalanced energy consumption in 2-D regular topologies becomes more severe and much more difficult to tackle than that in 1-D chains, though the latter is known as an already quite hard problem. We address this problem and propose an adaptive data collection scheme by employing different communication radii for nodes in different locations to balance the energy consumption in WSNs. In order to achieve the ultimate goal of maximizing network lifetime in grid-based WSNs, we give a mathematical formulation, which shows the problem of maximizing network lifetime is a nonlinear programming problem and NP-hard even in the 1-D case. We discuss several heuristic solutions and show that the halving shift data collection scheme is the best solution among them. We also generalize the maximizing network lifetime problem to the randomly-deployed WSNs, which shows the significance of our mathematical formulation for this crucial problem in WSNs.     

Sleep–wake up scheduling with probabilistic coverage model in sensor networks1

Energy optimisation is one of the important issues in the research of wireless sensor networks (WSNs). In the application of monitoring, a large number of sensors are scattered uniformly to cover a collection of points of interest (PoIs) distributed randomly in the monitored area. Since the energy of battery-powered sensor is limited in WSNs, sensors are scheduled to wake up in a large-scale sensor network application. In this paper, we consider how to reduce the energy consumption and prolong the lifetime of WSNs through wake-up scheduling with probabilistic sensing model in the large-scale application of monitoring. To extend the lifetime of sensor network, we need to balance the energy consumption of sensors so that there will not be too much redundant energy in some sensors before the WSN terminates. The detection probability and false alarm probability are taken into consideration to achieve a better performance and reveal the real sensing process which is characterised in the probabilistic sensing model. Data fusion is also introduced to utilise information of sensors so that a PoI in the monitored area may be covered by multiple sensors collaboratively, which will decrease the number of sensors that cover the monitored region. Based on the probabilistic model and data fusion, minimum weight probabilistic coverage problem is formulated in this paper. We also propose a greedy method and modified genetic algorithm based on the greedy method to address the problem. Simulation experiments are conducted to demonstrate the advantages of our proposed algorithms over existing work.     

基于分布式聚类的有向传感器网络移动目标跟踪算法研究

针对有向传感器网络DSN（Directional Sensor Networks）中,传感器节点部署数量对目标跟踪精度、网络寿命和能效问题的影响方面,提出了一个分布式聚类算法,该算法在优化活跃传感器和节点的直接通信过程中,由分布式集群来负责协调成员间的节点,通过传输给Sink的定位信息及从多个节点聚集的传感数据来准确定位目标的位置。基于该理论的目标跟踪机制,提高了目标跟踪精度、增加了网络寿命和网络剩余能量。并进行了仿真验证,结果表明该方法能实现更高的跟踪性能。     

Virtual field strategy for collaborative signal and information processing in wireless heterogeneous sensor networks

A novel collaborative signal and information processing (CSIP) method, which is based on virtual fields excited by sensor nodes, is proposed for wireless heterogeneous sensor networks. These virtual fields influence states and operations in sensor nodes located in their regions of influence (ROIs) and thus collaboration is implemented through interactions between surrounding virtual fields and sensor nodes. Described by a group of radial basis functions (RBFs), virtual fields have different magnitudes and ROIs due to different initial energy, communication ranges, sensing ranges and information processing capabilities in heterogeneous sensor nodes. Dynamic mobile agent itinerary decision and adaptive node active probability updating are studied with virtual field strategies in a heterogeneous sensor network using mobile-agent-based computing paradigm. Simulation results demonstrate that this approach can reduce energy consumption in sensor nodes. Information gain efficiency and network lifetime are also increased.     

Energy-aware self-organisation algorithms with heterogeneous connectivity in wireless sensor networks

Heterogeneity of node energy is a common phenomenon in wireless sensor networks. In such node energy heterogeneous sensor network, how to balance the energy consumption is the key problem on extending the lifetime of the sensor network system. An energy-efficient self-organisation algorithm with heterogeneous connectivity based on energy-awareness is proposed. Each sensor node in the network adjusts its own transmission radius based on the local energy information during the constructing and operating phase. Thus heterogeneous network topology, in which the nodes can choose different transmission radius, is formed. In contrast to the homogeneous network model, in which the node carries the same radius, simulation and analysis are conducted to explore the topology characteristics and robustness with different node energy distribution. The degree distribution shows the scale-free property in the heterogeneous model. The proposed network model enjoys higher efficiency of transmitting data, less clustering, higher robustness under node random failures and longer network lifetime than those in the homogeneous ones.     

基于数据预处理的无线气象传感网数据重构模型

针对无线气象传感网内由于节点数量大、感知数据冗余度高而导致节点通信耗能过高的问题,提出了数据联合稀疏预处理模型,利用监测区域气象要素预报值和各簇头要素值计算出一个全网公共分量并对网内数据进行预处理。将分布式压缩感知应用于簇型传感网中,对各节点感知数据进行压缩观测,在汇聚节点进行数据重构,从根本上降低节点通信量,均衡负载;同时设计了一个基于公共分量异常数据稀疏方法。仿真实验中,相对于单独使用压缩感知,数据联合稀疏预处理模型能够有效利用数据时空相关性提高数据稀疏度,压缩性能提高了25%,重构性能提高46%;同时,异常数据处理方案能够以96%的高概率恢复异常数据。因此,该数据预处理模型能够提高数据重构效率,有效降低网内数据通信量,延长网络寿命。     

概率模型下的一种优化覆盖算法

覆盖率不仅是评价无线传感器网络体系性能的重要标准之一,也是无线传感器网络所研究的一项重点课题.为此,提出了一种概率模型下优化覆盖算法.该算法通过对概率覆盖模型的计算,给出了传感器节点覆盖的期望值和公差的求解过程以及对所关注目标节点进行首次覆盖后的期望值证明过程.在网络能量方面则通过节点状态调度策略对通信路径进行优化,证明节点能量衰减过程中,拟合函数极限存在的意义,实现了传感器节点能量的有效匹配,抑制了传感器节点能量的消耗,证明了优化后整个监测区域传感器节点覆盖函数之间的关系.仿真实验结果表明,该算法不仅提高了覆盖和网络服务质量,而且有效地抑制了网络能量开销,延长了网络生存周期.     

基于相关性感知的无线视频传感器网络路由协议

无线视频传感器网络（ WVSNs）节点的能量十分有限,为了降低传感器节点的能耗,延长网络生存时间,提出了一种基于相关性感知的视频传感器网络通信协议。首先对当前经典无线视频传感器网络路由协议的不足进行分析;然后从簇首节点的选择、簇的形成、节点感知方向的调整、簇内通信以及簇间通信等几个方面进行改进和优化;最后在Matlab 2012平台进行了仿真对比测试。仿真结果表明：该协议不仅能够延长无线视频传感器网络生命周期,而且提高了监测区域覆盖率。