Increasing network lifetime by balancing node energy consumption in heterogeneous sensor networks

Sensor nodes are powered by battery and have severe energy constraints. The typical many‐to‐one traffic pattern causes uneven energy consumption among sensor nodes, that is, sensor nodes near the base station or a cluster head have much heavier traffic burden and run out of power much faster than other nodes. The uneven node energy dissipation dramatically reduces sensor network lifetime. In a previous work, we presented the chessboard clustering scheme to increase network lifetime by balancing node energy consumption. To achieve good performance and scalability, we propose to form a heterogeneous sensor network by deploying a few powerful high‐end sensors in addition to a large number of low‐end sensors. In this paper, we design an efficient routing protocol based on the chessboard clustering scheme, and we compute the minimum node density for satisfying a given lifetime constraint. Simulation experiments show that the chessboard clustering‐based routing protocol balances node energy consumption very well and dramatically increases network lifetime, and it performs much better than two other clustering‐based schemes. Copyright © 2006 John Wiley & Sons, Ltd.     

Clustering routing protocol based on improved PSO algorithm in WSN

Aiming at the problem that the location distribution of cluster head nodes filtered by wireless sensor network clustering routing protocol was unbalanced and the data transmission path of forwarding nodes was unreasonable,which would increase the energy consumption of nodes and shorten the network life cycle,a clustering routing protocol based on improved particle swarm optimization algorithm was proposed.In the process of cluster head election,a new fitness function was established by defining the energy factor and position equalization factor of the node,the better candidate cluster head node was evaluated and selected,the position update speed of the candidate cluster head nodes was adjusted by the optimized update learning factor,the local search and speeded up the convergence of the global search was expanded.According to the distance between the forwarding node and the base station,the single-hop or multi-hop transmission mode was adopted,and a multi-hop method was designed based on the minimum spanning tree to select an optimal multi-hop path for the data transmission of the forwarding node.Simulation results show that the clustering routing protocol based on improved particle swarm optimization algorithm can elect cluster head nodes and forwarding nodes with more balanced energy and location,which shortened the communication distance of the network.The energy consumption of nodes is lower and more balanced,effectively extending the network life cycle.     

A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks

In wireless sensor network, a large number of sensor nodes are distributed to cover a certain area. Sensor node is little in size with restricted processing power, memory, and limited battery life. Because of restricted battery power, wireless sensor network needs to broaden the system lifetime by reducing the energy consumption. A clustering‐based protocols adapt the use of energy by giving a balance to all nodes to become a cluster head. In this paper, we concentrate on a recent hierarchical routing protocols, which are depending on LEACH protocol to enhance its performance and increase the lifetime of wireless sensor network. So our enhanced protocol called Node Ranked–LEACH is proposed. Our proposed protocol improves the total network lifetime based on node rank algorithm. Node rank algorithm depends on both path cost and number of links between nodes to select the cluster head of each cluster. This enhancement reflects the real weight of specific node to success and can be represented as a cluster head. The proposed algorithm overcomes the random process selection, which leads to unexpected fail for some cluster heads in other LEACH versions, and it gives a good performance in the network lifetime and energy consumption comparing with previous version of LEACH protocols.     

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.     

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.     

Energy-efficient neighbor discovery protocol for mobile wireless sensor networks

Low energy consumption is a critical design requirement for most wireless sensor network (WSN) applications. Due to minimal transmission power levels, time-varying environmental factors and mobility of nodes, network neighborhood changes frequently. In these conditions, the most critical issue for energy is to minimize the transactions and time consumed for neighbor discovery operations. In this paper, we present an energy-efficient neighbor discovery protocol targeted at synchronized low duty-cycle medium access control (MAC) schemes such as IEEE 802.15.4 and S-MAC. The protocol effectively reduces the need for costly network scans by proactively distributing node schedule information in MAC protocol beacons and by using this information for establishing new communication links. Energy consumption is further reduced by optimizing the beacon transmission rate. The protocol is validated by performance analysis and experimental measurements with physical WSN prototypes. Experimental results show that the protocol can reduce node energy consumption up to 80% at 1–3 m/s node mobility.     

基于节点移动和协作转发的异构传感器网络路由协议

在异构传感器网络中,超级节点有着重要的意义.针对异构传感器网络中超级节点能量消耗过快的问题,提出了一种新的分簇路由协议（MCC）.通过在建簇阶段采用簇首移动控制策略来使簇内负载更加均衡;在簇间数据传输时引入了节点协作转发机制,提高了分簇协议的数据传输性能.通过NS2仿真验证,结果表明,MCC协议不仅降低了簇首能耗,而且使网络能耗更加均匀,延长了网络寿命.     

An efficient cluster-based communication protocol for wireless sensor networks

A wireless sensor network is a network of large numbers of sensor nodes, where each sensor node is a tiny device that is equipped with a processing, sensing subsystem and a communication subsystem. The critical issue in wireless sensor networks is how to gather sensed data in an energy-efficient way, so that the network lifetime can be extended. The design of protocols for such wireless sensor networks has to be energy-aware in order to extend the lifetime of the network because it is difficult to recharge sensor node batteries. We propose a protocol to form clusters, select cluster heads, select cluster senders and determine appropriate routings in order to reduce overall energy consumption and enhance the network lifetime. Our clustering protocol is called an Efficient Cluster-Based Communication Protocol (ECOMP) for Wireless Sensor Networks. In ECOMP, each sensor node consumes a small amount of transmitting energy in order to reach the neighbour sensor node in the bidirectional ring, and the cluster heads do not need to receive any sensed data from member nodes. The simulation results show that ECOMP significantly minimises energy consumption of sensor nodes and extends the network lifetime, compared with existing clustering protocol.     

Research on WSN lifetime optimization game algorithm combined power and channel

Due to the problem of shortening the network lifetime which was caused by the big energy consumption for wireless sensor network (WSN) whose energy and computing power was limit,a lifetime optimization game algorithm combined power control and channel allocation (LOAPC) was proposed.The influence of node power and residual energy on the node interference was explored to construct an interference affection measurement model.Then,expected transmission times was introduced to establish a novel node lifetime model.Finally,LOAPC aimed at reducing interference and prolonging lifetime,and the node power was limited by an optional power set which ensured the network connectivity and economized energy consumption,so as to prolong the network lifetime effectively.At the same time,the simulation results show that the algorithm has the characteristics of low interference,low energy consumption and effectively prolonging the lifetime of the network.     

物联网感知层多路径传输策略研究

多路径数据传输是无线传感器网络亟需解决的一个关键问题.本文针对节点故障、链路失效和外界干扰影响网络稳定性和可靠性,提出一种基于混合蛙跳算法的无线传感器网络多路径传输策略.首先我们详细介绍了蛙跳算法及其原理,之后我们将其应用到无线传感器网络多路径传输策略之中,接着运用混合蛙跳算法对传感网络节点其进行更新、划分、重组以便选择出最优节点建立传输最优路径,提高网络的稳定性和可靠性.通过算法仿真与结果对比提出的算法与AODV、粒子群PSO算法相比,在网络能耗、传输时延、丢包率、连通率和可靠度等方面都具有较好的性能.其中网络能耗比AODV、PSO算法降低了62.5％和35.8％.     

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。     

Development of Energy Efficient Image/Video Sensor Networks

Image/Video Sensor Networks are emerging applications for sensor network technologies. The relatively high energy consuming image capturing process and the large size of the data collected by image/video sensors presents new challenges for the sensor network in terms of energy consumption and network capacity. We propose to address these issues through the use of a high density network deployment. A high density network allows network nodes to conserve power by reducing their transmission power and simultaneously increases the potential for spatially concurrent transmissions within the network, resulting in improved network throughput. Furthermore, with the use of additional relay nodes, we allow a communication density that differs from the sensing density. A higher communication density has the potential to further increase the spatially concurrent transmission. Moreover, this reduces the relay burden of the sensor node, thus conserving sensor energy. In this work, we show analytically how a high density network design effectively improves energy consumption and network capacity. Furthermore, we discuss the constraints placed on a high density sensor network deployment due to application latency requirements, sensor coverage requirements, connectivity requirements, and node costs.     

基于改进SSA优化WSN分簇协议

无线传感器网络(Wireless Sensor Networks,WSN)的路由协议是无线传感器网络领域中的一个研究热点.针对LEACH协议的不足,提出一种基于自适应t分布改进麻雀搜索算法(Improved Sparrow Search Algorithm,ISSA)的改进LEACH协议(LEACH?ISSA),以解决...     

The slow start power controlled MAC protocol for mobile ad hoc networks and its performance analysis

We propose and evaluate the performance of a new MAC-layer protocol for mobile ad hoc networks, called the Slow Start Power Controlled (abbreviated SSPC) protocol. SSPC improves on IEEE 802.11 by using power control for the RTS/CTS and DATA frame transmissions, so as to reduce energy consumption and increase network throughput and lifetime. In our scheme the transmission power used for the RTS frames is not constant, but follows a slow start principle. The CTS frames, which are sent at maximum transmission power, prevent the neighbouring nodes from transmitting their DATA frames at power levels higher than a computed threshold, while allowing them to transmit at power levels less than that threshold. Reduced energy consumption is achieved by adjusting the node transmission power to the minimum required value for reliable reception at the receiving node, while increase in network throughput is achieved by allowing more transmissions to take place simultaneously. The slow start principle used for calculating the appropriate DATA frames transmission power and the possibility of more simultaneous collision-free transmissions differentiate the SSPC protocol from the other MAC solutions proposed for IEEE 802.11. Simulation results indicate that the SSPC protocol achieves a significant reduction in power consumption, average packet delay and frequency of RTS frame collisions, and a significant increase in network throughput and received-to-sent packets ratio compared to IEEE 802.11 protocol.     

Distributed Cooperative Control Algorithm for Topology Control and Channel Allocation in Multi-radio Multi-channel Wireless Sensor Network: From a Game Perspective

With the development of wireless communication technology, the spectrum resource is becoming more and more scarce, which results in the increase of network co-interference and then incurs the increase of data retransmission probability. Hence, the single channel based algorithms are facing a myriad of challenges. Moreover, reducing the energy consumption and prolonging the network lifetime is the key issue for wireless sensor network. In order to alleviate the interference while reducing and balancing the energy consumption, we tend to design a multi-radio multi-channel algorithm that joint the topology control and channel allocation. Firstly, we study the interactions between topology control and channel allocation, which lay the basis for the further reduction of transmission power and interference. We take account of the radio power, node residual energy and node interference to construct a cooperative control game model of topology and channel allocation. This game model has proven to guarantee the existence of Nash equilibrium. And then based on this game model, a distributed Cooperative Control Algorithm of Topology and Channel allocation (CCATC) is developed, which can converge to Nash Equilibrium and preserve the network connectivity. Furthermore, the simulation results demonstrate that CCATC can not only greatly reduce the interference but also prolong the network lifetime by balancing the energy consumption of nodes. The reduction of interference comes with the improvement of network throughput. Besides, CCATC has many other attractive features such as the higher channel utilization, the better robustness, the fairer channel allocation and the less end-to-end delay.     

基于无线传感器网络的K均值算法研究

传统无线传感网一般由大量密集的传感器节点构成,存在节点计算能力、能源和带宽都非常有限的缺点,为了有效节能、延长网络寿命,介绍了基于聚类的K均值算法.该算法通过生成的簇头节点散播到网络的各个区域中,减少了每个区域内通信的能耗和可能会出现的一般节点过早死亡的情况,从而避免了网络对该区城提早失去监控.实验证明,该算法对各节点...     

基于改进蚁群算法的高能效WSN协作传输策略*

针对传统传感器网络分簇不均匀,数据传输能耗相对较高的问题,提出了I-CoopACO(Cooperative transmission scheme based improved Ant Colony Optimal algorithm)算法.该算法在协作LEACH (Low Energy Adaptive Clustering Hierar-chy)的技术基础上,改进了成簇过程,使得分簇规模更加均匀;在稳定传输阶段,利用节点剩余能量和传输功耗构建启发因子,通过改进的蚁群算法搜索下一跳中继节点获得最优节点,使得传输功耗更低,能耗更均衡.仿真结果表明,在随机分布的感知网络中,I-CoopACO算法减少了传输能耗,均衡了网络负载,延长了网络工作寿命,比协作LEACH算法延长了64.93％的工作寿命.     

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。     

节点密集型传感器网络中路由算法的研究

传感器网络的路由协议越来越引起人们的关注。针对节点高密度部署并且存在部分移动节点的网络环境,当前常用的各类路由算法都不能有效地降低能耗。论文提出了改进型GAF算法,将网络划分成若干个单元格,不同移动速度的节点以不同的权重竞选簇头,竞选失败者将进入休眠状态,以此来降低网络总能耗。通过分析和仿真,验证了该算法在节能方面的优势。     

A demand-based slot assignment algorithm for energy-aware reliable data transmission in wireless sensor networks

This paper proposes a new demand-based slot assignment (DSA) algorithm that allocates time slots based on the bandwidth demand of each node in a tree topology. DSA is basically different from SDA, DAS, or WIRES that assigns one large slot for each sensor node, but is similar to the frame-slot pair assignment (FSA) algorithm used in TreeMAC in that it assigns multiple small size slots for sensor nodes per each data collection round. DSA tackles the shortcomings of FSA in terms of the capability of packet aggregation and filtering, the balance of energy consumption, and bandwidth utilization. In general, nodes at lower tree depths process more packets and consume more energy than ones at higher tree depths, and thus the imbalanced energy consumption shortens network lifetime. The proposed algorithm allocates a sequence of receiving slots and then a sequence of sending slots to each node. This approach not only reduces the power consumption of nodes at lower depths significantly by allowing efficient data aggregation and filtering, but also it improves bandwidth utilization by removing wasted slots. In addition, the RTS and CTS messages are used within a slot for ensuring the reliability of data transmission and updating sync time between a child and its parent. Simulation results show that DSA far outperforms FSA in energy consumption and bandwidth utilization.