Balancing Energy Consumption to Maximize Network Lifetime in Data-Gathering Sensor Networks

Unbalanced energy consumption is an inherent problem in wireless sensor networks characterized by multihop routing and many-to-one traffic pattern, and this uneven energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed data-gathering sensor networks. We formulate the energy consumption balancing problem as an optimal transmitting data distribution problem by combining the ideas of corona-based network division and mixed-routing strategy together with data aggregation. We first propose a localized zone-based routing scheme that guarantees balanced energy consumption among nodes within each corona. We then design an offline centralized algorithm with time complexity O(n) (n is the number of coronas) to solve the transmitting data distribution problem aimed at balancing energy consumption among nodes in different coronas. The approach for computing the optimal number of coronas in terms of maximizing network lifetime is also presented. Based on the mathematical model, an energy-balanced data gathering (EBDG) protocol is designed and the solution for extending EBDG to large-scale data-gathering sensor networks is also presented. Simulation results demonstrate that EBDG significantly outperforms conventional multihop transmission schemes, direct transmission schemes, and cluster-head rotation schemes in terms of network lifetime.     

An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks

Wireless body sensor networks are expected to extend human-centered applications in large-scale sensing and detecting environments. Energy savings has become one of the most important features of the sensor nodes to prolong their lifetime in such networks. To provide reasonable energy consumption and to improve the network lifetime of wireless body sensor network systems, new and efficient energy-saving schemes must be developed. An energy-saving routing architecture with a uniform clustering algorithm is proposed in this paper to reduce the energy consumption in wireless body sensor networks. We adopted centralized and cluster-based techniques to create a cluster-tree routing structure for the sensor nodes. The main goal of this scheme is to reduce the data transmission distances of the sensor nodes by using the uniform cluster structure concepts. To make an ideal cluster distribution, the distances between the sensor nodes are calculated, and the residual energy of each sensor node is accounted for when selecting the appropriate cluster head nodes. On the basis of the uniform cluster location, the data transmission distances between the sensor nodes can be reduced by employing an adaptive multi-hop approach. The energy consumption is reduced, and the lifetime is extended for the sensor nodes by balancing the network load among the clusters. Simulation results show that the proposed scheme outperforms the previously known schemes in terms of the energy consumption and the network lifetime for the wireless body sensor networks.     

An Energy Efficient Clustering Scheme for Data Aggregation in Wireless Sensor Networks

In wireless sensor networks, a clustering scheme is helpful in reducing the energy consumption by aggregating data at intermediate sensors. This paper discusses the important issue of energy optimization in hierarchically-clustered wireless sensor networks to minimize the total energy consumption required to collect data. We propose a comprehensive energy consumption model for multi-tier clustered sensor networks, in which all the energy consumptions not only in the phase of data transmissions but also in the phase of cluster head rotations are taken into account. By using this new model, we are able to obtain the solutions of optimal tier number and the resulted optimal clustering scheme on how to group all the sensors into tiers by the suggested numerical method. This then enables us to propose an energy-efficiency optimized distributed multi-tier clustering algorithm for wireless sensor networks. This algorithm is theoretically analyzed in terms of time complexity. Simulation results are provided to show that, the theoretically calculated energy consumption by the new model matches very well with the simulation results, and the energy consumption is indeed minimized at the optimal number of tiers in the multi-tier clustered wireless sensor networks.     

无线传感器网络基于路径的非均匀分布策略

无线传感器网络中多对一的数据传输方式导致节点负载的不均衡性,靠近汇聚节点(Sink)的节点要比远离Sink的节点消耗更多的能量,如此容易引发能量空洞问题。针对该问题,从网络数据的传递路径出发,根据网络中节点承担的路径数量的不同,平衡各层节点的能耗,提出感知节点覆盖率一致、内层路由节点与其所有外层感知节点数目相同的的非均匀分布策略,并通过仿真实验证明了该方法的有效性。     

基于数据流和网络编码的无线传感器网络数据聚合算法

为了减少分簇的无线传感器网络(WSN)中数据包传输的数量,并使传感器网络的能量效率最大化,提出了一种节能的自适应数据聚合算法.在该算法中,源节点凭借其存储和计算能力,利用数据流技术减少数据包的传输量;当数据从源节点传输到簇头时,簇头根据控制信息选择一组节点作为编码节点,当数据相关性低于某阈值时,该组节点对数据包进行网络编码,若数据相关性高于某阈值,该组节点则会成为聚合节点进行数据聚合,网络编码和数据聚合可以减少簇头冗余流量,提高能量效率.实验结果显示,使用该算法后,数据包交付率有所提高,能量消耗显著减少.     

一种支持多分辨率查询的数据存储策略

减少空闲侦听是延长无线传感网络生命周期的有效途径。文章分析了无线传感网络在数据处理和数据传输时的能耗问题,提出了一种支持多分辨率查询的数据存储策略。该策略是将指定区域内所有无线传感节点的工作时槽以一种蛇形排列方式进行分配,使各节点周期性地进入睡眠或侦听状态。在任意时刻,有且仅有两个传感节点处于工作状态,既保证了系统的可靠性,又降低了系统的开销。仿真实验表明,该方法减少了空闲侦听,降低了传感器的能耗,有效延长了网络的生命周期。     

Joint design of clustering and in-cluster data route for heterogeneous wireless sensor networks

A heterogeneous wireless sensor network comprises a number of inexpensive energy constrained wireless sensor nodes which collect data from the sensing environment and transmit them toward the improved cluster head in a coordinated way. Employing clustering techniques in such networks can achieve balanced energy consumption of member nodes and prolong the network lifetimes. In classical clustering techniques, clustering and in-cluster data routes are usually separated into independent operations. Although separate considerations of these two issues simplify the system design, it is often the non-optimal lifetime expectancy for wireless sensor networks. This paper proposes an integral framework that integrates these two correlated items in an interactive entirety. For that, we develop the clustering problems using nonlinear programming. Evolution process of clustering is provided in simulations. Results show that our joint-design proposal reaches the near optimal match between member nodes and cluster heads.     

一种异构传感器网络下的节能分簇路由算法

无线传感器网络存在着严重的能量约束,传统同构的传感网络路由协议和算法不适合异构网络,因此,设计异构传感网络下的节能路由算法具有现实意义。研究两种不同类型传感器节点构成的,具有不同的初始能量和不同感知数据能力的异构网络中基于簇头预测的节能分簇路由算法ECAH。根据簇内节点的剩余能量、能量消耗速率和跟上一轮簇头的距离预测出下一轮簇头,有效地减少了控制报文数量,降低了系统开销,节约了能量。仿真结果显示,在异构的网络中采用ECAH路由算法比LEACH算法网络生存时间大约提高了23%。     

基于均匀分簇的无线传感器网络寿命最大化理论分析

无线传感器网络路由协议的一个重要目标是均衡节点能量消耗并延长网络寿命.基于均匀分簇的无线传感器网络模型,对网络寿命最大化进行了理论分析.在此基础上,提出了一种改进的数据传输方式,有效地均衡了节点的能量消耗,并显著地延长了网络寿命.模拟实验表明,在网络半径一定时,通过合理地选取最优的簇半径,可以最大化网络寿命.改进数据传输方式后的最大网络寿命比改进前的提高了13%.最后,结合该领域当前研究现状,指出了基于分簇路由协议的最大网络寿命未来的研究重点.     

一种高效节能的无线传感器网络数据聚合协议

在无线传感器网络的应用中,常常利用大量传感器监视若干个离散目标。针对这类目标监视网络,本文提出了一种分布式高效节能的数据聚合协议EETO。EETO将覆盖目标相关 的节点组成一个簇,簇成员都是簇头的K跳覆盖邻居,相关数据在簇头能得到及时、完全的聚合,大大减少了数据传送量。详细的模拟实验结果表明,EETO有效地减少了能量消耗,显著增强了网络的覆盖寿命。     

线形异构传感器的网络生命周期

无线传感器网络的能耗决定了网络的生命周期,如何有效部署传感器节点来延长网络的生命周期是一个重要的研究课题。针对由高级节点和普通节点组成的线形异构传感器网络,给出了最大化网络生命周期模型。通过分析节点的能量消耗,求解出了两种节点的分配比例,得出了最大化网络生命周期的节点部署方案。     

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.     

基于非线性电池模型的WSNs节能技术研究

在无线传感器网络（WSNs）节能技术研究中,如何最大化节点电池能量效率从而延长整个网络寿命是一个关键问题。采用非线性电池模型,使用在低数据传输速率场合中较为节能的FSK调制技术,通过理论分析和参数优化方法,以电池能耗最小为目标,建立电池能耗模型,优化调制指数,使得电池能耗最低。仿真结果表明：该模型能够更加准确地评估节点能耗和寿命。在给定传输距离下,存在一个最优调制指数,使得电池能耗最低。最后给出了不同传输距离对应的最优调制指数。     

无线传感网络任务分配的能效性控制策略

无线传感网络包含大量密集分布传感节点,各节点测量产生大量数据给传输、存储、管理和分析带来困难,无线传感网络能源不可更换性限制了网络寿命.本文提出基于熵理论和欧式距离的网络能耗评价指标,采用对等(peer-to-peer,简称P2P)计算方法,利用基于蚁群智能的能效性优化任务分配控制策略,针对中心节点工作状态、传输能耗和网络寿命实现动态实时任务控制分配,完成多中心节点并行计算,提高网络工作效率,节约能耗.实验表明基于蚁群智能的能效性任务分配控制策略能实时有效地缩短无线传感网络计算时间,减少网络能耗,提高网络寿命.     

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.     

An energy-efficient data gathering method based on compressive sensing for pervasive sensor networks

This paper proposes an energy-efficient data gathering method called CN-MSTP (Combining Minimum Spanning Tree with Interest Nodes) for pervasive wireless sensor networks, basing on Compressive sensing (CS) and data aggregation. The proposed CN-MSTP protocol selects different nodes at random as projection nodes, and sets each projection node as a root to construct a minimum spanning tree by combining with interest nodes. Projection node aggregates sensor reading from sensor nodes using compressive sensing. We extend our method by letting the sink node participate in the process of building a minimum tree and introduce eCN-MSTP. We compare our methods with the other methods. Simulation results indicate that our two methods outperform the other methods in overall energy consumption saving and load balance and hence prolong the lifetime of the network.     

自适应异构传感网节能优化拓扑控制研究

针对传统的节能优化算法没有充分考虑节点间的通信距离和节点失效后重新分簇等问题,为了延长网络的生存期,提出一种自适应优化异构无线传感器网络拓扑结构控制算法.提出的算法首先基于传输数据跳数和相邻传感器之间通信距离,依据相似三角形几何原理,结合具体应用场景对传感器节点的分簇、成簇等操作进行自适应优化控制.仿真实验表明:改进的...     

A two-hop clustered image transmission scheme for maximizing network lifetime in wireless multimedia sensor networks

In traditional wireless sensor networks, normal sensor nodes which measure scalar physical phenomena like temperature, pressure and humidity usually compress the data before sending them out to minimize the communication energy consumption. However, this strategy may not be suitable for image transmission in wireless multimedia sensor networks. In the traditional clustering structure, when the camera-equipped node or the cluster head compresses the images, an energy hole will appear. This is a key factor that affects the lifetime of the network. To avoid the energy hole problem, a two-hop clustered image transmission scheme is proposed in this paper. In the proposed scheme, many redirectors are used to compress and forward the images for the purpose of reducing energy consumption of the camera-equipped node and the cluster head. With adaptive adjustment of the transmission radius in the camera cluster and tasks allocation based on the residual energy of the normal sensor nodes by the camera-equipped node, the energy consumption of the nodes in the network is balanced. The experimental results show that the proposed scheme can prolong the network lifetime dramatically in the case of the sensor nodes deployed densely.     

实现能量均衡消耗的传感器网络节点摆放策略

在传感器网络技术应用的民用领域中,采集信息的传感器节点位置固定,并且有些距离汇聚节点太远,需要加入中继节点转发数据。一些中继节点由于承担了过多的数据量而过早耗尽能量,影响了网络的生存周期。该文针对该种情况,提出了一种实现各节点能量均衡消耗的中继节点多级摆放策略,研究了如何通过调整中继节点的摆放位置和转发数据量,使传感器节点和中继节点在每一轮的数据传输中消耗相同的能量。基于该策略,还研究了中继节点数目与网络生存周期之间的关系,为延长网络生命周期和减小中继节点数目的折中提供了一种参考。     

无线传感网优化生存时间的分布式功率控制

为延长无线传感网的生存时间,提出优化生存时间的分布式功率控制算法(DPCOL).该算法分析节点发送功率变化下的链路流量平衡约束,链路最大传输速率约束,节点能耗约束等条件,建立最大化生存时间的网络模型.采用分布式功率迭代和次梯度算法求解该模型.节点获知与各邻居节点通信所需要的最低发送功率集,随机选择发送功率集中的功率作为...