Novel sensor scheduling and energy-efficient quantization for tracking target in wireless sensor networks

This paper focuses on sensor scheduling and information quantization issues for target tracking in wireless sensor networks (WSNs). To reduce the energy consumption of WSNs, it is essential and effective to select the next tasking sensor and quantize the WSNs data. In existing works, sensor scheduling’ goals include maximizing tracking accuracy and minimizing energy cost. In this paper, the integration of sensor scheduling and quantization technology is used to balance the tradeoff between tracking accuracy and energy consumption. The main characteristic of the proposed schemes includes a novel filtering process of scheduling scheme, and a compressed quantized algorithm for extended Kalman filter (EKF). To make the algorithms more efficient, the proposed platform employs a method of decreasing the threshold of sampling intervals to reduce the execution time of all operations. A real tracking system platform for testing the novel sensor scheduling and the quantization scheme is developed. Energy consumption and tracking accuracy of the platform under different schemes are compared finally.     

Understanding optimal data gathering in the energy and latency domains of a wireless sensor network

The problem of optimal data gathering in wireless sensor networks (WSNs) is addressed by means of optimization techniques. The goal of this work is to lay the foundations to develop algorithms and techniques that minimize the data gathering latency and at the same time balance the energy consumption among the nodes, so as to maximize the network lifetime. Following an incremental-complexity approach, several mathematical programming problems are proposed with focus on different network performance metrics. First, the static routing problem is formulated for large and dense WSNs. Optimal data-gathering trees are analyzed and the effects of several sensor capabilities and constraints are discussed, e.g., radio power constraints, energy consumption model, and data aggregation functionalities. Then, dynamic re-routing and scheduling are considered. An accurate network model is proposed that captures the tradeoff between the data gathering latency and the energy consumption, by modeling the interactions among the routing, medium access control and physical layers.For each problem, extensive simulation results are provided. The proposed models provide a deeper insight into the problem of timely and energy efficient data gathering. Useful guidelines for the design of efficient WSNs are derived and discussed.     

LABS: Latency aware broadcast scheduling in uncoordinated Duty-Cycled Wireless Sensor Networks

Broadcast is a fundamental operation in Wireless Sensor Networks (WSNs) and plays an important role in a communication protocol design. In duty-cycled scenarios, a sensor node can receive a message only in its active time slot, which makes it more difficult to design collision-free scheduling for broadcast operations. Recent studies in this area have focused on minimizing broadcast latency and guaranteeing that all nodes receive a broadcast message. This paper investigates the problem of Minimum Latency Broadcast Scheduling in Duty-Cycled (MLBSDC) WSNs. By using special geometric properties of independent sets of a broadcast tree, we reduce the number of transmissions, consequently reducing the possibility of collision. Allowing multiple transmissions in one working period, our proposed Latency Aware Broadcast Scheduling (LABS) scheme provides a latency-efficient broadcast schedule. Theoretical analysis proves that the scheme has the same approximation ratio and complexity as the previous best algorithm for the MLBSDC problem. Moreover, simulation shows that the new scheme achieves up to 34%, 37%, and 21% performance improvement over previous schemes, in terms of latency, number of transmissions, and energy consumption, respectively.     

Energy-saving PPM schemes for WSNs

Energy conservation is a critical problem in recently-emerging wireless sensor networks （WSNs）. Pulse position modulation （PPM）, as an exploring-worthy modulation format for energy efficiency, is tailored for WSNs into two schemes, mono-mode PPM and multi-mode PPM, in this paper. Resorting to an idealized system model and a practical system model, which combine the power consumptions in transmission and reception modules of nodes with the idealized and real- istic battery characteristics, the battery energy efficiencies of mono-mode PPM and multi-mode PPM are evaluated and compared. To minimize the battery energy consumption （BEC）, these schemes are further optimized in terms of constellation size M for a link in path-loss channels. Our analytical and numerical results show that considerable energy can be saved by multi-mode PPM; and the optimization performances of these schemes are noticeable at various communication distances though their optimization properties are different.     

Data aggregation and routing in Wireless Sensor Networks: Optimal and heuristic algorithms

A fundamental challenge in the design of Wireless Sensor Networks (WSNs) is to maximize their lifetimes especially when they have a limited and non-replenishable energy supply. To extend the network lifetime, power management and energy-efficient communication techniques at all layers become necessary. In this paper, we present solutions for the data gathering and routing problem with in-network aggregation in WSNs. Our objective is to maximize the network lifetime by utilizing data aggregation and in-network processing techniques. We particularly focus on the joint problem of optimal data routing with data aggregation en route such that the above mentioned objective is achieved. We present Grid-based Routing and Aggregator Selection Scheme (GRASS), a scheme for WSNs that can achieve low energy dissipation and low latency without sacrificing quality. GRASS embodies optimal (exact) as well as heuristic approaches to find the minimum number of aggregation points while routing data to the Base-Station (BS) such that the network lifetime is maximized. Our results show that, when compared to other schemes, GRASS improves system lifetime with acceptable levels of latency in data aggregation and without sacrificing data quality.     

Balanced energy allocation scheme for a solar-powered sensor system and its effects on network-wide performance

Solar power can extend the lifetime of wireless sensor networks (WSNs), but it is a very variable energy source. In many applications for WSNs, however, it is often preferred to operate at a constant quality level rather than to change application behavior frequently. Therefore, a solar-powered node is required adaptation to a highly varying energy supply. Reconciling a varying supply with a fixed demand requires a good prediction of that supply, so that demand can be regulated accordingly. We describe two energy allocation schemes, based on time-slots, which aim at optimum use of the periodically harvested solar energy, while minimizing the variability in energy allocation. The simpler scheme is designed for resource-constrained sensors; and a more accurate approach is designed for sensors with a larger energy budget. Each of these schemes uses a probabilistic model based on previous observation of harvested solar energy. This model takes account of long-term trends as well as temporary fluctuations of right levels. Finally, this node-level energy optimization naturally leads to the improvement of the network-wide performance such as latency and throughput. The experimental results on our testbeds and simulations show it clearly.     

一种基于转发优先及流量分级的无线传感器网络退避算法

基于无线传感器网络的特点,提出了一种新的基于转发优先和流量分级的退避算法,该算法根据节点自身可获取的网络信息将网络流量判定为不同的级别,并依此改变退避窗口的大小;该算法还赋予转发节点一定的信道竞争优势,使得当前的通信业务可以优先地进行下去。通过理论分析和仿真实验,证实该算法能够有效地降低节点冲突率和额外的能量开销,减少传输延时,提高系统吞吐量,从而提高无线传感器网络的性能。     

A1: An energy efficient topology control algorithm for connected area coverage in wireless sensor networks

Energy consumption in Wireless Sensor Networks (WSNs) is of paramount importance, which is demonstrated by the large number of algorithms, techniques, and protocols that have been developed to save energy, and thereby extend the lifetime of the network. However, in the context of WSNs routing and dissemination, Connected Dominating Set (CDS) principle has emerged as the most popular method for energy-efficient topology control (TC) in WSNs. In a CDS-based topology control technique, a virtual backbone is formed, which allows communication between any arbitrary pair of nodes in the network. In this paper, we present a CDS based topology control algorithm, A1, which forms an energy efficient virtual backbone. In our simulations, we compare the performance of A1 with three prominent CDS-based algorithms namely energy-efficient CDS (EECDS), CDS Rule K and A3. The results demonstrate that A1 performs better in terms of message overhead and other selected metrics. Moreover, the A1 not only achieves better connectivity under topology maintenance but also provides better sensing coverage when compared with other algorithms.     

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.     

An energy-efficient,transport-controlled MAC protocol for wireless sensor networks

In wireless sensor networks (WSNs), one major cause of wasted energy is that the wireless network interface is always on to accept possible traffic. Many medium access control (MAC) protocols therefore adopted a periodic listen-and-sleep scheme to save energy, at sacrifice of end-to-end latency and throughput. Another cause is packet dropping due to network congestion, necessitating a lightweight transport protocol for WSNs. In this paper, we suggest a transport-controlled MAC protocol (TC-MAC) that combines the transport protocol into the MAC protocol with the aims of achieving high performance as well as energy efficiency in multi-hop forwarding. Although TC-MAC also works through a periodic listen-and-sleep scheme, it lowers end-to-end latency by reserving data forwarding schedules across multi-hop nodes during the listen period and by forwarding data during the sleep period, all while increasing throughput by piggybacking the subsequent data forwarding schedule on current data transmissions and forwarding data consecutively. In addition, TC-MAC gives a fairness-aware lightweight transport control mechanism based on benefits of using the MAC-layer information. The results show that TC-MAC performs as well as an 802.11-like MAC in end-to-end latency and throughput, and is more efficient than S-MAC in energy consumption, with the additional advantage of supporting fairness-aware congestion control.     

无线传感器网络分簇路由节能研究

在大规模传感和环境监测中,节约能源延长传感器节点生命已成为无线传感器网络最重要的研究课题之一。提供合理的能源消耗和改善无线网络生命周期的传感器网络系统,必须设计一种新的有效的节能方案和节能路由体系。方案采用一种聚类算法减少无线传感器网络的能量消耗,创建一种cluster-tree分簇路由结构的传感器网络。该方案主要目标是做一个理想的分簇分配,减少传感器节点之间的数据传输距离,降低传感器节点能源消耗,延长寿命。实验结果表明,该方案有效地降低了能源消耗从而延长无线传感器网络生命。     

Energy-aware node placement,topology control and MAC scheduling for wireless sensor networks

In the WSNs, the nodes closer to the sink node have heavier traffic load for packet forwarding because they do not only collect data within their sensing range but also relay data for nodes further away. The unbalanced power consumption among sensor nodes may cause network partition. This paper proposes efficient node placement, topology control, and MAC scheduling protocols to prolong the sensor network lifetime, balance the power consumption of sensor nodes, and avoid collision. Firstly, a virtual tree topology is constructed based on Grid-based WSNs. Then two node-placement techniques, namely Distance-based and Density-based deployment schemes, are proposed to balance the power consumption of sensor nodes. Finally, a collision-free MAC scheduling protocol is proposed to prevent the packet transmissions from collision. In addition, extension of the proposed protocols are made from a Grid-based WSN to a randomly deployed WSN, enabling the developed energy-balanced schemes to be generally applied to randomly deployed WSNs. Simulation results reveal that the developed protocols can efficiently balance each sensor node’s power consumption and prolong the network lifetime in both Grid-based and randomly deployed WSNs.     

面向异构WSNs的基于能量感知的簇路由算法

有效地使用传感节点的能量,进而延长网络寿命成为设计无线传感网路由协议的一项挑战性的工作.为了延长网络,现存的多数簇路由是面向同构网络.为此,提出分布式能量感知的异构WSNs非均匀分簇路由DEAC(Distributed Energy Aware unequal Clustering)算法.DEAC算法是以EADUC(Energy Aware Distributed Unequal Clustering)为基础,并进行优化.与EADUC不同,DEAC算法从簇头竞选机制、簇间多跳通信中的下一跳转发节点的选择策略以及自适应的节点通信半径的设置三方面进行优化.在簇头竞选机制中,采用退避算法,利用节点的剩余能量以及邻居节点的平均能量设置延时时间;在选择下一跳转发节点时,建立节点的关于能量的度量函数,选择具有最大剩余能量的节点作为下一跳;而在设置节点通信半径时,考虑了距离、剩余能量以及邻居节点数信息.仿真结果表明,与EADUC协议相比,提出的DEAC算法能够有效地延缓第1个节点失效的时间,减少了能耗,扩延网络寿命.     

无线传感器节点实时能耗监测

无线传感器网络设计的关键技术环节之一是低功耗。首先要准确地检测到运行时各模块的能量消耗,然后才能够进行控制优化。然而,应用上的需求千差万别,导致硬件平台的多样性。本文选取无线传感器网络领域节点能量消耗检测作为研究方向,提出了一种便携的无线传感器节点能耗数据采集装置,能够实时采集节点的电压、电流信息。针对当前研究集中于仿真模拟,这种装置可用于实际环境的能量消耗检测,检测精度高。在MicaZ节点上的实验结果表明,该系统能以较高精度监测节点的能量效率。实际测量发现,传感器网络中传感器能耗也属能量消耗的一部分,且消耗量不可忽视,为今后的研究改进提供了新的参考。     

无线传感器网络不依赖位置信息的能耗均衡拓扑控制

针对无线传感器网络(WSN)稠密部署的特点,首先提出一种不依赖位置信息的拓扑构建(LTC)算法用于构造连通支配树型结构的虚拟骨干网。在此基础上,深入分析骨干节点的能量消耗以及数据传输时延,引入密度控制与数据传输率控制因子以均衡虚拟骨干网能耗,提出了不依赖位置信息的能耗均衡拓扑控制(LETC)算法。LETC算法依据各个区域不同的数据传输量,调整该区域虚拟骨干节点的布置密度,同时增加低能耗节点的传输速率以减少网络时延。理论分析与仿真表明,经过优化的LETC算法相比LTC能够更有效地均衡能耗,延长网络寿命241%,减少时延28.1%。     

J-Sim下WSNs仿真框架的扩展设计与实现

随着无线传感器网络(WSNs)的应用,如何延长网络生命周期,对路由协议的研究提出了挑战。为了更好地研究能量高效利用的WSNs路由协议,建立对WSNs能耗支持较好的仿真平台具有十分重要的现实意义。针对J-Sim下WSNs框架对能耗仿真支持不好的问题,在现有的WSNs框架基础上提出了一种支持能耗仿真的WSNs仿真框架并在该框架上扩展实现LEACH协议。实验结果表明改进后的WSNs框架可以真实地仿真WSNs,获取有价值的仿真结果。     

基于DSP的障碍物环境的簇状传感网络路由算法

分簇是延长无线传感网络寿命的有效技术之一,然而现有的簇状传感网络的路由技术没有考虑障碍物环境.为此,提出了面向障碍物的簇状传感网络的Dijkstra最短路径路由DSPR(Dijkstra shortestpath-based routing)算法.DSPR算法首先利用能量有效的同质簇EHC(energy-efficient homogeneous clus-tering)技术周期地选举簇头CH(cluster head).每周期定义一帧,每帧利用EHC技术选举簇头CH.簇头CHs构成数据传输的主干路径,并利用Dijkstra最短路径DSP(Dijkstra shortest path)算法选择最优路径,当遭遇障碍物时,将障碍物的顶点作为中间终点,再运行DSP,从而缩短数据传输路径.仿真结果表明,提出的DSPR有效减少传输路径和能量消耗,并提高了数据传输效率.     

基于WSNs的部分覆盖应用的节点唤醒机制

无线传感网络WSNs(Wireless Sensor Networks)已广泛应用于各类领域.然而,由于能量有限,提高传感节点能效是一项挑战工作.休眠调度策略是保存能量、延长网络寿命的有效策略.此外,多数WSNs应用并不要求100％的覆盖.为此,提出面向部分覆盖应用的节点唤醒机制,且标记为PCLA.PCLA机制引用学习自动机去合理地唤醒节点,而其他节点休眠,进而延长网络寿命.首先,唤醒部分节点构成主干网,然后,再利用这些节点的邻居去满足网络覆盖要求.实验数据表明,与同类机制相比,提出的PCLA机制能够有效地满足部分覆盖要求,并且在活动节点数和网络寿命方面也具有较好的性能.     

单节点的无线传感器网络数据传输优化策略

为了提高无线传感器网络（WSNs）节点能量的利用率,延长WSNs的生存时间,提出了一种单节点的WSNs数据传输优化策略.首先对WSNs结构进行分析,并建立单个传感器节点数据传输优化的数学模型;然后采用惩罚函数法对数据传输过程中的传感器节点能耗进行优化;最后在Matlab 2012平台对其进行仿真分析.结果表明：该方法可以根据环境能量的变化对传感器节点能耗进行自适应优化,提高了节点的累积数据传输总量,可以较好适应环境能量不确定性.     

基于协作传输的大范围WSNs能耗均衡分簇算法

由于大范围无线传感器网络（WSNs）节点的数量巨大,网络的能量消耗极不均,提出一种基于协作传输的分簇算法—EBBMCC—LS算法。该算法在保证网络均匀分簇的前提下,能保证网络中簇头节点的均匀分布,在簇间通信时加入协作传输策略,传感器节点之间通过协作传输构成虚拟多天线系统,改善系统性能,解决了大范围WSNs中的能耗不均现象。实验验证：该算法能够均衡大范围WSNs中的能耗,延长网络寿命,可促进大范围WSNs应用的推广。