基于剩余能量和睡眠控制的改进LEACH算法

无线传感器网络（WSN）路由协议研究的一个重要的目标是如何在有限的能源下降低整个网络的能耗,提高网络的生存时间。以分簇路由协议LEACH为研究基础,提出了一种改进算法。该算法改进了簇首选择规则,引入协调件协议算法,通过在成簇阶段降低剩余能量低的节点被选择成为簇首的概率,在稳定运行阶段使簇首节点尽可能多的保持睡眠状态,从而降低了网络能耗。仿真结果表明,与原LEACH算法相比,改进的算法能够明显地延长网络生存时间。     

A distributed battery recovery aware topology control algorithm for wireless sensor networks

Battery recovery effect is a phenomenon that the available capacity of a battery could increase if the battery can sleep for a certain period of time since its last discharging. Accordingly, the battery can work for a longer time when it takes some rests between consecutive discharging processes than when it works all the time. However, this effect has not been considered in the design of energy‐efficient topology control algorithms for wireless sensor networks. In this paper, we propose a distributed battery recovery effect aware connected dominating set constructing algorithm (BRE‐CDS) for wireless sensor networks. In BRE‐CDS, each network node periodically decides to join the connected dominating set or not. Nodes that have slept in the preceding round have priority to join the connected dominating set in the current round while nodes that have worked in the preceding round are encouraged to take sleep in the current round for battery recovery. Detailed algorithm design is presented. The computational complexity of BRE‐CDS is deduced to be O(D²), where D is node degree. Simulation results show that BRE‐CDS can significantly prolong the network lifetime as compared with existing work. Copyright © 2016 John Wiley & Sons, Ltd.     

一种基于冗余度的无线传感器网络节能策略

在无线传感器网络中,传感节点由于采用电池供电,因此寿命有限。如何有效节省传感器节点的能量,延长网络的使用寿命,一直是广泛研究的焦点。文章提出一种适用于高冗余度布置的无线传感器网络结构中,节省传感器节点能量消耗的方法-接续调度法。该方法通过协调点对小区域内节点的调度,使区域内节点依次分时段工作。通过这种接续调度,避免了节点间的冲突和串扰,达到延长整体网络寿命的效果。     

An Energy-Efficient Threshold-Based Clustering Protocol for Wireless Sensor Networks

Energy-constrained wireless sensor networks (WSNs) have been deployed widely for monitoring and surveillance purposes. Since sensor nodes (SNs) have significant power constraints (battery life), energy-efficient protocols must be employed to prolong the network lifetime. In this paper, we propose an energy-efficient protocol which provides a new way of creating distributed clusters. This protocol is a modified version of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. The experimental results show that our protocol that takes into account both the residual energy at each SN and the distance between the SNs outperforms LEACH protocol in terms of first node death time and average residual energy.     

基于传输距离和Sink移动的扩延网络寿命算法

在无线传感网络WSN(Wireless Sensor Network)中,传感节点通常以多跳方式向信宿Sink传输感测数据.由于邻近信宿Sink的传感节点需要承担数据转发的任务,比其他节点消耗更多的能量,缩短了网络寿命.为此,提出一种扩延网络寿命的新算法,记为NLTA(Network LifeTime Augmentation).NLTA算法采用了节点传输距离自适应调整和信宿Sink移动两个策略.节点依据能量情况,调整传输距离,减少能量消耗,然后根据路径容量值,调整Sink的位置,平衡网内的节点能量消耗,避免信宿Sink的周围节点能量过度消耗.仿真结果表明,提出的NLTA方案能够有效地提高网络寿命.     

Energy‐efficient multi‐level and distance‐aware clustering mechanism for WSNs

Most sensor networks are deployed at hostile environments to sense and gather specific information. As sensor nodes have battery constraints, therefore, the research community is trying to propose energy‐efficient solutions for wireless sensor networks (WSNs) to prolong the lifetime of the network. In this paper, we propose an energy‐efficient multi‐level and distance‐aware clustering (EEMDC) mechanism for WSNs. In this mechanism, the area of the network is divided into three logical layers, which depends upon the hop‐count‐based distance from the base station. The simulation outcomes show that EEMDC is more energy efficient than other existing conventional approaches. Copyright © 2013 John Wiley & Sons, Ltd.     

Schedule unifying algorithm extending network lifetime in S-MAC-based wireless sensor networks

In S-MAC-based sensor networks, border nodes consume more energy since they follow multiple listen and sleep schedules. Therefore they switch into the listen state frequently and reduce the network lifetime. This paper proposes a simple but powerful algorithm, termed the Schedule Unifying Algorithm (SUA), to minimize energy consumption of border nodes by unifying multiple listen and sleep schedules into a single unified schedule. The simulation results show that SUA incorporated SMAC- based nodes consume less energy, thereby extending the network lifetime approximately 2 times more.     

Extending the Lifetime of Wireless Sensor Networks Through Adaptive Sleep

In recent years, the use of wireless sensor networks for industrial applications has rapidly increased. However, energy consumption still remains one of the main limitations of this technology. As communication typically accounts for the major power consumption, the activity of the transceiver should be minimized, in order to prolong the network lifetime. To this end, this paper proposes an Adaptive Staggered sLEEp Protocol (ASLEEP) for efficient power management in wireless sensor networks targeted to periodic data acquisition. This protocol dynamically adjusts the sleep schedules of nodes to match the network demands, even in time-varying operating conditions. In addition, it does not require any a priori knowledge of the network topology or traffic pattern. ASLEEP has been extensively studied with simulation. The results obtained show that, under stationary conditions, the protocol effectively reduces the energy consumption of sensor nodes (by dynamically adjusting their duty-cycle to current needs) thus increasing significantly the network lifetime. With respect to similar nonadaptive solutions, it also reduces the average message latency and may increase the delivery ratio. Under time-varying conditions, the protocol is able to adapt the duty-cycle of single nodes to the new operating conditions, while keeping a consistent sleep schedule among sensor nodes. The results presented here are also confirmed by an experimental evaluation in a real testbed.      

Energy‐Efficient Quorum‐Based MAC Protocol for Wireless Sensor Networks

The reliability of sensor networks is generally dependent on the battery power of the sensor nodes that it employs; hence it is crucial for the sensor nodes to efficiently use their battery resources. This research paper presents a method to increase the reliability of sensor nodes by constructing a connected dominating tree (CDT), which is a subnetwork of wireless sensor networks. It detects the minimum number of dominatees, dominators, forwarder sensor nodes, and aggregates, as well as transmitting data to the sink. A new medium access control (MAC) protocol, called Homogenous Quorum‐Based Medium Access Control (HQMAC), is also introduced, which is an adaptive, homogenous, asynchronous quorum‐based MAC protocol. In this protocol, certain sensor nodes belonging to a network will be allowed to tune their wake‐up and sleep intervals, based on their own traffic load. A new quorum system, named BiQuorum, is used by HQMAC to provide a low duty cycle, low network sensibility, and a high number of rendezvous points when compared with other quorum systems such as grid and dygrid. Both the theoretical results and the simulation results proved that the proposed HQMAC (when applied to a CDT) facilitates low transmission latency, high delivery ratio, and low energy consumption, thus extending the lifetime of the network it serves.     

无线传感器网络能量高效混合MAC算法

针对无线传感器网络MAC协议中存在的能耗问题,提出了能量高效的无线传感器网络混合MAC(EEH-MAC)算法,采用基于TDMA机制的时槽系数动态调整簇内节点的时槽大小来降低数据的传输时延;同时,对部分不需要数据传输的节点不分配时槽来减少能耗;按簇内节点剩余能量系数形成时槽分配顺序来减少状态转换的能耗;在簇头之间采用CSMA/CA机制的随机分配策略进行通信.仿真结果表明,EEH-MAC协议能有效减少能耗并延长网络生命周期.     

A Learning Automata Based Area Coverage Algorithm for Wireless Sensor Networks

One way to reduce energy consumption in wireless sensor networks is to reduce the number of active nodes in the network. When sensors are redundantly deployed, a subset of sensors should be selected to actively monitor the field （referred to as a ＂cover＂）, whereas the rest of the sensors should be put to sleep to conserve their batteries. In this paper, a learning automata based algorithm for energy-efficient monitoring in wireless sensor networks （EEMLA） is proposed. Each node in EEMLA algorithm is equipped with a learning automaton which decides for the node to be active or not at any time during the operation of the network. Using feedback received from neighboring nodes, each node gradually learns its proper state during the operation of the network. Experimental results have shown that the proposed monitoring algorithm in comparison to other existing methods such as Tian and LUC can better prolong the network lifetime.     

传感器网络中基于域的分布式自动成簇算法研究

 在传感器网络中,分簇是其他应用的基础,本文结合传感器网络的节点特性和位置信息,提出一种基于域的分布式自动成簇算法DCAM(Distributed Clustering Auto Model),DCAM把传感器网络按域划分来构建簇,簇之间是相互连通并且可以覆盖网络中所有的传感节点,簇头节点与簇中的网关节点就构建成网络的连通核,当传送数据时,传感节点只需在连通核中寻径,因而能明显减少寻径时间复杂度并且具有更好的分布性;然后在DCAM的基础上提出了簇的自愈和更新算法, 更新和自愈算法可更大程度地延长整个网络的生命周期.     

Lifetime analysis of wireless sensor nodes in different smart grid environments

Wireless sensor networks (WSNs) can help the realization of low-cost power grid automation systems where multi-functional sensor nodes can be used to monitor the critical parameters of smart grid components. The WSN-based smart grid applications include but not limited to load control, power system monitoring and control, fault diagnostics, power fraud detection, demand response, and distribution automation. However, the design and implementation of WSNs are constrained by energy resources. Sensor nodes have limited battery energy supply and accordingly, power aware communication protocols have been developed in order to address the energy consumption and prolong their lifetime. In this paper, the lifetime of wireless sensor nodes has been analyzed under different smart grid radio propagation environments, such as 500 kV substation, main power control room, and underground network transformer vaults. In particular, the effects of smart grid channel characteristics and radio parameters, such as path loss, shadowing, frame length and distance, on a wireless sensor node lifetime have been evaluated. Overall, the main objective of this paper is to help network designers quantifying the impact of the smart grid propagation environment and sensor radio characteristics on node lifetime in harsh smart grid environments.     

Improving Low-Energy Adaptive Clustering Hierarchy Architectures with Sleep Mode for Wireless Sensor Networks

A wireless sensor network (WSN) is composed of sensor nodes whose energy is battery-powered. Therefore, the energy is limited. This paper aims to improve the energy efficiency of sensor nodes in order to extend the lifetime of WSNs. In this paper, we propose four new hierarchical clustering topology architectures: random cluster head and sub-cluster head (RCHSCH), random cluster head and max energy sub-cluster head (RCHMESCH), random cluster head and sub-cluster head with sleep mode (RCHSCHSM) and random cluster head and max energy sub-cluster head with sleep mode (RCHMESCHSM). Our proposed architectures involve three-layers and are based on low-energy adaptive clustering hierarchy (LEACH) architecture. Notably, RCHSCH can improve upon cluster head death within the LEACH architecture. In addition, we develop a sleep mode for sensor nodes based on correlations among sensor data within sub-clusters in RCHSCHSM. Thus, we can reduce the energy consumption of the sensor node and increase energy efficiency. From the simulation results, our proposed RCHSCH, RCHMESCH, RCHSCHSM and RCHMESCHSM architectures perform better than the LEACH architecture in terms of initial node death, the number of nodes alive and total residual energy. Furthermore, we find the performance of RCHMESCHSM architecture to be optimal in the set of all available architectures.     

大规模输电线路状态监测传感器网络的周期性低功耗通信技术方案

为了实现输电线路监测的功耗低、寿命长、绿色发展的目的，提出大规模输电线路状态监测传感器网络周期性低功耗通信技术方案。依据网络中传感器网络组网特征以及节点运行状态转换特点，设置睡眠定时器，以周期性运行方式使传感器网络通信节点在初始化、睡眠、激活状态间转换，通信节点在输电线路状态监测数据无传递需求时进入睡眠状态，节省通信功耗；传感器网络汇聚（sink）节点利用梯度创建上行路由，通过源路由的方式创建下行路由，以跳数和剩余能量为依据进行上、下行路由数据分组传递，降低节点功耗，延长通信运行时间。实验显示，大规模输电线路状态监测传感器网络应用该技术方案后，通信功耗明显降低，运行时间明显延长，且不会影响监测传感器网络的数据传输性能，延长了监测传感器网络的使用寿命。     

一种基于无交集节点分组的无线传感器网络覆盖算法

无线传感器网络是一种无线自组织网络,它由大量能量有限的传感器节点组成.能量消耗和网络覆盖是无线传感器网络的两个核心问题,网络覆盖决定了无线传感器网络对物理世界的监测能力,能量消耗则决定了无线传感器网络的生存时间.本文研究了一种改进的基于无交集节点分组算法,针对随机选取节点实现无交集节点分组方式获得的分组个数少且节点通信...     

Prolonging the lifetime of wireless sensor networks by utilizing feedback control

A new algorithm aiming to prolong the lifetime of wireless sensor networks (WSNs) is proposed to balance energy depletion. Using a feedback control combined with a discrete nonlinear programming method to adjust the transmission radii of sensor nodes located in different locations, makes network load redistribution possible and balances energy consumption, further prolongs the lifetime of the entire network. A data distribution model which specific to WSNs with sensor nodes that can adjust transmission radii is proposed to analyze the load spread of the network. This model contributes to predicting and analyzing energy consumption balance effectively. Compared with two other algorithms, dynamic transmission range adjustment and SP, respectively, the experimental results show that the proposed algorithm can lengthen the lifetime of WSNs by up to 22.7 and 27.2 %.     

The Impact of Deployment Pattern and Routing Scheme on the Lifetime in Multi-Sink Wireless Sensor Network

Extensive use of sensor and actuator networks in many real-life applications introduced several new performance metrics at the node and network level. Since wireless sensor nodes have significant battery constraints, therefore, energy efficiency, as well as network lifetime, are among the most significant performance metrics to measure the effectiveness of given network architecture. This work investigates the performance of an event-based data delivery model using a multipath routing scheme for a wireless sensor network with multiple sink nodes. This routing algorithm follows a sink initiated route discovery process with the location information of the source nodes already known to the sink nodes. It also considers communication link costs before making decisions for packet forwarding. Carried out simulation compares the network performance of a wireless sensor network with a single sink, dual sink, and multi sink networking approaches. Based on a series of simulation experiments, the lifetime aware multipath routing approach is found appropriate for increasing the lifetime of sensor nodes significantly when compared to other similar routing schemes. However, energy-efficient packet forwarding is a major concern of this work; other network performance metrics like delay, average packet latency, and packet delivery ratio are also taken into the account.

     

Optimizing sensor networks in the energy-latency-density design space

In wireless sensor networks, energy efficiency is crucial to achieving satisfactory network lifetime. To reduce the energy consumption significantly, a node should turn off its radio most of the time, except when it has to participate in data forwarding. We propose a new technique, called sparse topology and energy management (STEM), which efficiently wakes up nodes from a deep sleep state without the need for an ultra low-power radio. The designer can trade the energy efficiency of this sleep state for the latency associated with waking up the node. In addition, we integrate STEM with approaches that also leverage excess network density. We show that our hybrid wakeup scheme results in energy savings of over two orders of magnitude compared to sensor networks without topology management. Furthermore, the network designer is offered full flexibility in exploiting the energy-latency-density design space by selecting the appropriate parameter settings of our protocol.     

Maximizing Lifetime of Target Coverage in Wireless Sensor Networks Using Learning Automata

In wireless sensor networks, when each target is covered by multiple sensors, we can schedule sensor nodes to monitor deployed targets in order to improve lifetime of network. In this paper, we propose an efficient scheduling method based on learning automata, in which each node is equipped with a learning automaton, which helps the node to select its proper state (active or sleep), at any given time. To study the performance of the proposed method, computer simulations are conducted. Results of these simulations show that the proposed scheduling method can better prolong the lifetime of the network in comparison to similar existing methods.