Fusion function placement for Active Networks paradigm in wireless sensor networks

Active Networks paradigm integrated with distributed data fusion has the potential to significantly reduce energy dissipation in wireless sensor networks, where energy conservation is the most challenging issue. This work aims to minimize energy cost when distributed data fusion is deployed for the Active Networks computing paradigm. First we propose an optimal solution for mapping task graph of distributed data fusion application into network. Optimal solution uses an exhaustive search algorithm for finding the placements with minimized power consumption. However, optimal solution has high computational complexity—O(mn ^k ), where n denotes the number of network nodes, m is the number of fusion functions, and k is the maximum number of children a fusion function has in task graph and its children are also fusion functions. Then, an approximate solution with low complexity (O(mlog n + log² m)) is proposed called P2lace, which includes two phases, task graph partition and task graph placement. Finally, an extensive evaluation compares approximate solution with optimal solution. The results show that approximate solution is scalable with different task graph characteristics and network size and only causes slightly more transmission cost than optimal solution. And the algorithm without optimizing is shown to be applicable to the network, where the sink node does not have global information of entire network.     

交通路灯监控系统的无线传感网链状路由算法

在交通路灯监控系统中为节省网络节点能耗和降低数据传输时延,提出一种无线传感网链状路由算法（CRASMS）。该算法根据节点和监控区域的信息将监控区域分成若干个簇区域,在每一个簇区域中依次循环选择某个节点为簇头节点,通过簇头节点和传感节点的通信建立簇内星型网络,最终簇头节点接收传感节点数据,采用数据融合算法降低数据冗余,通过簇头节点间的多跳路由将数据传输到Sink节点并将用户端的指令传输到被控节点。仿真结果表明：CRASMS算法保持了PEGASIS算法在节点能耗方面和LEACH算法在传输时延方面的优点,克服了PEGASIS 算法在传输时延方面和LEACH算法在节点能耗方面的不足,将网络平均节点能耗和平均数据传输时延保持在较低水平。在一定的条件下,CRASMS算法比LEACH和PEGASIS算法更优。     

Asymptotic results for decentralized detection in power constrained wireless sensor networks

In this paper, we study a binary decentralized detection problem in which a set of sensor nodes provides partial information about the state of nature to a fusion center. Sensor nodes have access to conditionally independent and identically distributed observations, given the state of nature, and transmit their data over a wireless channel. Upon reception of the information, the fusion center attempts to accurately reconstruct the state of nature. Specifically, we extend existing asymptotic results about large sensor networks to the case where the network is subject to a joint power constraint, and where the communication channel from each sensor node to the fusion center is corrupted by additive noise. Large deviation theory is used to show that having identical sensor nodes, i.e., each node using the same transmission scheme, is asymptotically optimal. Furthermore, a performance metric by which sensor node candidates can be compared is established. We supplement the theory with examples to illustrate how the results derived in this paper apply to the design of practical sensing systems.     

A Tree-Based Data Collecting Network Structure for Wireless Sensor Networks

In a sensor network with a large number of densely populated sensor nodes, a single target of interest may be detected by multiple sensor nodes simultaneously. Data collected from the sensor nodes are usually highly correlated, and hence energy saving using in-network data fusion becomes possible. A traditional data fusion scheme starts with dividing the network into clusters, followed by electing a sensor node as cluster head in each cluster. A cluster head is responsible for collecting data from all its cluster members, performing data fusion on these data and transmitting the fused data to the base station. Assuming that a sensor node is only capable of handling a single node-to-node transmission at a time and each transmission takes T time-slots, a cluster head with n cluster members will take at least nT time-slots to collect data from all its cluster members. In this paper, a tree-based network structure and its formation algorithms are proposed. Simulation results show that the proposed network structure can greatly reduce the delay in data collection.     

Achieving energy‐neutral data transmission by adjusting transmission power for energy‐harvesting wireless sensor networks

Recently, benefiting from rapid development of energy harvesting technologies, the research trend of wireless sensor networks has shifted from the battery‐powered network to the one that can harvest energy from ambient environments. In such networks, a proper use of harvested energy poses plenty of challenges caused by numerous influence factors and complex application environments. Although numerous works have been based on the energy status of sensor nodes, no work refers to the issue of minimizing the overall data transmission cost by adjusting transmission power of nodes in energy‐harvesting wireless sensor networks. In this paper, we consider the optimization problem of deriving the energy‐neutral minimum cost paths between the source nodes and the sink node. By introducing the concept of energy‐neutral operation, we first propose a polynomial‐time optimal algorithm for finding the optimal path from a single source to the sink by adjusting the transmission powers. Based on the work earlier, another polynomial‐time algorithm is further proposed for finding the approximated optimal paths from multiple sources to the sink node. Also, we analyze the network capacity and present a near‐optimal algorithm based on the Ford–Fulkerson algorithm for approaching the maximum flow in the given network. We have validated our algorithms by various numerical results in terms of path capacity, least energy of nodes, energy ratio, and path cost. Simulation results show that the proposed algorithms achieve significant performance enhancements over existing schemes. Copyright © 2016 John Wiley & Sons, Ltd.     

基于格拉布斯准则和改进粒子滤波算法的水下传感网目标跟踪

水下无线传感网络(UWSN)执行目标跟踪时,因为各个传感器节点测量值对目标状态估计的贡献不一样以及节点能量有限,所以探索一种好的节点融合权重方法和节点规划机制能够获得更好的跟踪性能。针对上述问题,该文提出一种基于Grubbs准则和互信息熵加权融合的分布式粒子滤波(PF)目标跟踪算法(GMIEW)。首先利用Grubbs准则对传感器节点所获得的信息进行分析检验,去除干扰信息和错误信息。其次,在粒子滤波的重要性权值计算的过程中,引入动态加权因子,采用传感器节点的测量值与目标状态之间的互信息熵,来反映传感器节点提供的目标信息量,从而获得各个节点相应的加权因子。最后,采用3维场景下的簇-树型网络拓扑结构,跟踪监测区域内的目标。实验结果显示,该算法可有效提高水下传感器网络测量数据对目标跟踪预测的准确度,降低跟踪误差。     

基于移动中继站的无线传感器网络设计

WSN（无线传感器网络）是由大量分布式的不同规格和功能的具有感知、计算和通信能力的微型传感器节点通过自组织的方式构成的一个小范围的无线网络。为了解决无线传感器的远距离通信中继问题,能够将网络信息通过中继顺利地传送到远程终端,设计了基于移动螃蟹的传感器网络。它以机器螃蟹作为中继,进行数据的本地化处理和融合,实现分布式数据采集和监控。本系统应用于大规模的无线网络,增加了设备状态数据采集与通信的距离,有效地增强了系统的健壮性。     

基于最优簇头数的无线传感器网络安全LEACH路由协议

提出一种基于最优簇头数的无线传感器网络安全LEACH路由协议,该协议模拟真实传感器网络情况建立了三维空间模型,通过理论分析和仿真实验方法得到LEACH协议的最优簇头数,使网络能耗达到最优。在能量优化的同时把增强安全性作为设计目标,根据LEACH协议的特点,采用预置共享密钥对的方法,在簇头选举和数据传输阶段采用在数据包尾部捎带加密信息的方法,实现数据加密,在只增加少量能量开销的情况下数据机密性得到了实现。仿真验证了新协议的有效性,在能量优化的同时提高了路由安全性,延长了网络生命期。     

An event-driven energy-efficient routing protocol for water quality sensor networks

Due to the limited resources of water quality sensor networks, how to design a routing protocol which can prolong the network life cycle is one of a research hotspots. In this paper, according to the event level and the node energy of the sensor networks, the nodes’ types are defined, which can help to determine the cluster node. Then, an event driven routing protocol (EDRP) is proposed, which considers the event information and the remaining energy of the whole network. Simulation results show that, compared with distributed energy-efficient clustering algorithm, EDRP can reduce the overall energy consumption of the network by 138–172%, based on different kinds of events. Besides, EDRP can effectively prolong the life cycle and greatly increase the amount of data transmission of the network.

     

A data transmission protocol for reliable and energy-efficient data transmission in a wireless sensor-actuator network

In a wireless sensor-actuator network, sensor nodes gather information on the physical world and can deliver messages with sensed values to only nearby nodes due to weak radio. Thus, messages sent by nodes might be lost due to not only collision but also noise. Messages are forwarded by sensor nodes to an actuator node. In the redundant data transmission (RT) protocol, a sensor node sends a message with not only its sensed value but also sensed values received from other sensor nodes. Even if a message with a sensed value v is lost, an actuator node can receive the value v from a message sent by another sensor node. In addition, we have to reduce the energy consumption of a sensor node. A sensor node mainly consumes the energy to send and receive messages. Even if an event occurs, only some number of sensor nodes sensing the event send the sensed values to reduce the total energy consumption. We discuss an energy-efficient data transmission protocol. We evaluate the RT protocol compared with the CSMA protocol in terms of how much sensing data a node can receive in presence of messages loss. We evaluate the RT protocol in terms of how many number of sensed values an actuator node can receive in presence of message loss. We show that about 72% of sensed values can be delivered to an actuator node even if 95% of messages are lost due to noise and collision.     

Network Lifetime Maximization for Estimation in Multihop Wireless Sensor Networks

We consider the distributed estimation by a network consisting of a fusion center and a set of sensor nodes, where the goal is to maximize the network lifetime, defined as the estimation task cycles accomplished before the network becomes nonfunctional. In energy-limited wireless sensor networks, both local quantization and multihop transmission are essential to save transmission energy and thus prolong the network lifetime. The network lifetime optimization problem includes three components: i) optimizing source coding at each sensor node, ii) optimizing source throughput of each sensor node, and iii) optimizing multihop routing path. Fortunately, source coding optimization can be decoupled from source throughput and multihop routing path optimization, and is solved by introducing a concept of equivalent 1-bit MSE function. Based on the optimal source coding, the source throughput and multihop routing path optimization is formulated as a linear programming (LP) problem, which suggests a new notion of character-based routing. The proposed algorithm is optimal and the simulation results show that a significant gain is achieved by the proposed algorithm compared with heuristic methods.     

低能耗节点位置未知无线传感器网络控制方案

介绍了一种低能耗节点位置未知的网络控制方案,根据不同的网络运行轮数设定网络节点的通信半径,使网络具有良好的能量有效性.网络中基站经过构建阶段的启动过程、节点信息收集过程和节点信息上报过程,获得了整个网络节点的相对位置分布,然后整合节点-节点信息支路,得到具有回路链接的簇首节点集,其他节点根据自己邻居信息选择簇首节点,实现网络近似最小能耗拓扑的构建.通过仿真与同类典型算法LEACH-C、MCLB进行比较,结果显示该方案应用于网络运行时具有更长的网络生命周期、更少的信息总数和更低的网络构建代价.     

基于效用的无线传感器网络能量分配优化策略

该文对传感器网络在能量受限条件下的数据传输进行建模,提出了一种基于效用最大化的网络优化模型。该模型刻画了传感器网络节点之间在能量消耗方面的耦合关系。该文通过引入松弛变量和采用对偶分解技术,获得传感器网络能量控制的分布式算法。实验表明,该算法对所有的节点能收敛到速率和能量之间的帕累托(Pareto)最优平衡。     

基于连通支配集的无线传感网Top-k查询最优支撑树研究

构建底层逻辑树能有效降低集中式top-k查询带来的巨大通信开销,针对现有逻辑树都以固定汇聚节点为根节点,导致其附近节点能耗太大、过早死亡的问题,本文在无固定汇聚节点的网络背景下,基于连通支配集,提出一种能耗均衡的top-k查询最优支撑树构建方法,综合节点能量、度数以及与邻节点通信开销,选取能量代价小的作为支配节点负责查询中间数据处理,在每次查询中,节点基于地理位置ID轮流作为根节点,有效均衡节点的能耗.仿真实验表明,与其他逻辑拓扑树相比,基于最优支撑树的top-k查询具有相近的查询时间,但其平均每轮查询能耗更小,多次查询后各节点能耗达到均衡,有效延长了网络生命周期.     

Distributed Transmission Power Control for Network Programming in Wireless Sensor Networks

In wireless sensor networks, the necessity of network programming becomes more and more important due to the inaccessibility of the sensor nodes. Because the network programming produces a large amount of data, it consumes a great deal of energy and causes the network to suffer from much interference. Many conventional studies regarding the network programming attempted to reduce the energy consumption and the interference effect. However, they overlook transmission power effect on the energy-efficiency and the interference problem. In this paper, we present a novel network programming protocol that controls the transmission power at each sender node in a distributed manner. The protocol deals not only with the energy consumption of individual sensor node but also the network load distribution. Moreover, it reduces the interference effect on the network by decreasing the average transmission power of the sensor nodes. We verify that our protocol extends the lifetime of the sensor network and decreases the packet losses through simulation results.     

Maximum lifetime routing in wireless sensor networks

A routing problem in static wireless ad hoc networks is considered as it arises in a rapidly deployed, sensor based, monitoring system known as the wireless sensor network. Information obtained by the monitoring nodes needs to be routed to a set of designated gateway nodes. In these networks, every node is capable of sensing, data processing, and communication, and operates on its limited amount of battery energy consumed mostly in transmission and reception at its radio transceiver. If we assume that the transmitter power level can be adjusted to use the minimum energy required to reach the intended next hop receiver then the energy consumption rate per unit information transmission depends on the choice of the next hop node, i.e., the routing decision. We formulate the routing problem as a linear programming problem, where the objective is to maximize the network lifetime, which is equivalent to the time until the network partition due to battery outage. Two different models are considered for the information-generation processes. One assumes constant rates and the other assumes an arbitrary process. A shortest cost path routing algorithm is proposed which uses link costs that reflect both the communication energy consumption rates and the residual energy levels at the two end nodes. The algorithm is amenable to distributed implementation. Simulation results with both information-generation process models show that the proposed algorithm can achieve network lifetime that is very close to the optimal network lifetime obtained by solving the linear programming problem.     

多簇无线传感网的优化生存时间近邻功率控制算法

针对非均匀分布的无线传感网的生存时间问题,提出多簇无线传感网的优化生存时间近邻功率控制(NPCAOL_MC)算法。该算法采用K-means算法确定网络的簇个数和对应每个簇的节点,利用近邻算法评估每个簇的节点密度,确定簇的最优通信距离。结合Friss自由空间模型计算当前簇的最优发送功率。Sink节点广播通知其他节点,如果是同一簇内的节点相互通信,则采用簇最优功率发送数据,否则采用默认最大发送功率发送数据。仿真结果表明,利用NPCAOL_MC算法可以分析整个网络节点的位置信息,采用簇最优发送功率发送数据,从而提高生存时间,并使能耗经济有效。在密度分布不均的无线传感网中,NPCAOL_MC比采用固定发送功率的Ratio_w算法更优。     

Distributed object tracking using moving trajectories in wireless sensor networks

Most recent research on object tracking sensor networks has focused on collecting all data from the sensor network into the sink, which delivers the predicted locations to the corresponding nodes in order to accurately predict object movement. The communication cost of this centralized scenario is higher than that of a distributed method. Centralized data collection affects the freshness of the data and increases latency in movement trajectory prediction. In addition, due to the large amount of packets being sent and received, sensor node energy is quickly exhausted. Although this data collection method might result in higher accuracy for prediction, the sensor network lifetime is not reduced. In this paper, a distributed object tracking method is proposed using the network structure of convex polygons, called faces. The nodes in the faces cooperate to find the trajectories of an object and then these trajectories are used to predict the objects’ movement. The proposed method, based on trajectory tree construction, can reduce both the storage space of collected trajectories and the time spent on trajectory prediction analysis. Simulations show that the proposed method can reduce the energy consumption of the nodes and make prediction of nodes moving direction accurately than the existing approaches.     

Multi-factor and Distributed Clustering Routing Protocol in Wireless Sensor Networks

One of important issues in wireless sensor networks is how to effectively use the limited node energy to prolong the lifetime of the networks. Clustering is a promising approach in wireless sensor networks, which can increase the network lifetime and scalability. However, in existing clustering algorithms, too heavy burden of cluster heads may lead to rapid death of the sensor nodes. The location of function nodes and the number of the neighbor nodes are also not carefully considered during clustering. In this paper, a multi-factor and distributed clustering routing protocol MFDCRP based on communication nodes is proposed by combining cluster-based routing protocol and multi-hop transmission. Communication nodes are introduced to relay the multi-hop transmission and elect cluster heads in order to ease the overload of cluster heads. The protocol optimizes the election of cluster nodes by combining various factors such as the residual energy of nodes, the distance between cluster heads and the base station, and the number of the neighbor nodes. The local optimal path construction algorithm for multi-hop transmission is also improved. Simulation results show that MFDCRP can effectively save the energy of sensor nodes, balance the network energy distribution, and greatly prolong the network lifetime, compared with the existing protocols.     

Energy-Efficient Scheduling for Wireless Sensor Networks

We consider the problem of minimizing the energy needed for data fusion in a sensor network by varying the transmission times assigned to different sensor nodes. The optimal scheduling protocol is derived, based on which we develop a low-complexity inverse-log scheduling (ILS) algorithm that achieves near-optimal energy efficiency. To eliminate the communication overhead required by centralized scheduling protocols, we further derive a distributed inverse-log protocol that is applicable to networks with a large number of nodes. Focusing on large-scale networks with high total data rates, we analyze the energy consumption of the ILS. Our analysis reveals how its energy gain over traditional time-division multiple access depends on the channel and the data-length variations among different nodes.