无线传感器网络中一种能量有效的抗干扰路由算法

近年来,作为物联网重要支撑的无线传感器网络受WiFi等异构系统的干扰日益严重,传统路由协议在该干扰环境下的性能急剧下降。针对该问题,本文在引入动态簇的多信道策略的基础上,综合考虑信道切换代价、频谱受干扰程度、节点剩余能量、距离等因素提出了一种认知频谱干扰的能量有效的路由（CSIEE）算法。仿真结果表明,该路由与EEPA、AODV、AODV-EA路由相比,有效地节约了传感器节点能量,延长了网络生命周期。     

基于认知的无线传感器网络抗干扰路由算法

针对无线传感器网络受Wi—Fi等异构系统干扰日益严重的问题,在引入基于簇的动态多信道组网策略的基础上,综合考虑频谱受干扰程度、信道切换代价、节点剩余能量等因素,提出了一种认知频谱干扰的能量有效的路由（CSIEE）算法。仿真结果表明,该路由与EEPA,AODV,AODV—EA路由相比,有效地节约了传感器节点能量,延长了网络生命周期。     

基于节点特性的LR-WPAN网络能量优化路由算法

针对ZigBee网络混合路由算法的不足,考虑低速无线个域网(LR-WPAN)网络的能耗问题,提出了一种基于ZBR路由协议的改进算法(F-ZBR).本算法通过定义最小路由能量值和控制路由请求分组(RREQ)的传输方向、跳数以及在RREQ分组中加入能量标志位等措施,降低网络的整体能耗.仿真结果表明,F-ZBR算法的分组投递率、网络可用节点比率和网络剩余能量都较ZBR有明显提高,从而可以延缓ZigBee网络中大量数据传输造成的RN+节点能量过度损耗而导致的网络瘫痪等问题的发生,延长网络生命周期.     

一种具有能量感知的多路径Ad hoc路由算法

该文针对无线移动Ad hoc网络的动态变化拓扑逻辑,存在单向链路,节点能量有限等特点,提出了一种具有能量感知的多路径路由算法。该算法是一种反应式的基于路径池的多路径路由算法,数据和应答消息的路由根据路由池中路径的性能尺度,即跳数、可靠性和剩余能量以一定的概率分布随机选择。路径的可靠性和剩余能量在数据传输过程中动态更新。仿真结果表明该算法能有效地延长网络的生存时间。     

无线传感器网络路由中的能量预测及算法实现

基于无线传感器网络中路由协议高效合理利用能量的要求,提出一种基于剩余能量预测的地理位置路由(EPGR,energy prediction and geographical routing)算法。算法通过建立传感器网络节点运作模型,及相邻节点剩余能量预测机制,优化路由选择。仿真和分析表明,EPGR算法能够有效地优化数据传输路径,均衡传感器网络节点的能量消耗,延长网络寿命。     

基于能量均衡的便捷ZigBee路由改进算法

传统的ZigBee树路由算法的数据转发方式只能根据父子关系进行传输,其间将会消耗大量能量。为优化数据传输路径及数据传输过程中节点能量的均衡利用,文中提出一种改进型路由算法。充分利用邻居表,尽可能减少树路由跳数,同时考虑各节点能量的利用情况,使用能量值较高的节点进行数据传输。实验表明,改进的路由算法能够合理均衡能量,提高网络的整体寿命。     

基于跨层网络编码感知的无线传感器网络节能路由算法研究

编码感知路由可以发现路由中的网络编码机会,减少数据传输次数,提高网络吞吐量,是近年来路由算法研究的一个热点.当前编码感知路由存在编码条件失效、未考虑节点能量的问题,不适合直接应用于无线传感器网络.本文提出基于跨层网络编码感知的无线传感器网络节能路由算法CAER (Cross layer coding Aware Energy efficient Routing).提出并证明了修正后的网络编码条件,以解决编码条件失效问题.基于跨层思想,将网络编码感知机制与拓扑控制、覆盖控制结合,挖掘潜在编码机会.提出综合考虑节点编码机会、节点能量的跨层综合路由度量CCRM (Cross layer Coding aware Routing Metric).仿真结果表明,相比现有编码感知路由,CAER能够提高网络编码感知准确性,增加网络编码机会数量5%~15%,延长网络生存时间8%~12%.     

基于隐私保护的WSN路由算法

为了提高无线传感器网络(WSN)的隐私安全保护能力,针对当前的动态路由冲突重整隐私保护路由算法的链路开销过大和输出误码较高等问题,提出一种改进的基于隐私保护的WSN路由算法。首先构建WSN的路由链路信道模型,然后采用时隙调度方法进行隐私保护控制协议设计,结合WSN的能量量化均衡控制实现WSN路由算法优化设计。最后进行仿真测试,结果表明,该路由算法能提高WSN的隐私保护能力,网络输出码元的误码能得到有效抑制,提高数据传输的保真性。     

认知Ad-Hoc网络基于信道信息的路由算法

由于认知网络中信道具有动态时变特性,路由选择和信道分配成为认知Ad-Hoc网络亟待解决的问题。为此提出一种基于信道信息的改进路由算法,结合节点的信道共用度和最小条数作为路由度量,通过选取较稳定的节点,增强链路的稳定性。仿真结果表明,对于信道变化波动较大的环境,改进的路由算法具有很好的路径稳定性和链路修复能力。     

基于ACS的无线传感器网络区分服务路由算法

针对无线传感器网络中数据传输的不同要求,将QoS分为3类,根据无线链路的特点提供区分服务。利用博弈论分析了数据传输在延迟、可靠性与网络能量开销之间的关系,基于改进的蚁群优化算法ACS(ant colony system),设计了区分服务路由算法ADSGR(ant colony system based differentiated service and game-theory routing),依据不同QoS要求,选择适当的路由,提高网络的整体性能和资源利用率。实验结果表明,与现有算法相比,该算法在数据传输的延迟、可靠性和能量开销上具有更好的性能。     

An energy aware event-driven routing protocol for cognitive radio sensor networks

Cognitive radio sensor network (CRSN) is an intelligent and reasonable combination of cognitive radio technology and wireless sensor networks. It poses significant challenges to the design of topology maintenance techniques due to dynamic primary-user activities, which in turn decreases the data delivery performance of the network as well as it’s lifetime. This paper aims to provide a solution to the CRSN clustering and routing problem using an energy aware event-driven routing protocol (ERP) for CRSN. Upon detection of an event, the ERP determines eligible nodes for clustering according to local positions of CRSN nodes between the event and the sink and their residual energy levels. Cluster-heads are selected from the eligible nodes according to their residual energy values, available channels, neighbors and distance to the sink. In ERP, cluster formation is based on relative spectrum awareness such that channels with lower primary user appearance probability are selected as common data channels for clusters. For data routing, ERP employs hop-by-hop data forwarding approach through the CHs and primary/secondary gateways towards the sink. Through extensive simulations, we demonstrate that the proposed ERP provides with better network performances compared to those of the state-of-the-art protocols under a dynamic spectrum-aware data transmission environment.     

Survey on cluster-based routing protocols for cognitive radio sensor networks

Routing protocols could achieve efficient convergecast transmission of sensed data in cognitive radio sensor network (CRSN),and it is of vital importance for the whole network performance.In particular,cluster-based routing protocols could further lower routing selection complexity and improve scalability.Therefore,an overview of cluster-based routing protocols for CRSN was provided.Firstly,after a brief introduction to the concept and advantages of clustering in CRSN,the major factors concerning clustering algorithm design were pointed out.Secondly,the challenges faced by routing protocol design in CRSN and basic design principles were explored.Thirdly,the previous work of cluster-based routing protocols for CRSN was systematically analyzed and summarized.Finally,issues that require urgent solutions and future research directions were suggested.     

A Tabu search based routing algorithm for wireless sensor networks

In this paper, a Tabu search based routing algorithm is proposed to efficiently determine an optimal path from a source to a destination in wireless sensor networks (WSNs). There have been several methods proposed for routing algorithms in wireless sensor networks. In this paper, the Tabu search method is exploited for routing in WSNs from a new point of view. In this algorithm (TSRA), a new move and neighborhood search method is designed to integrate energy consumption and hop counts into routing choice. The proposed algorithm is compared with some of the ant colony optimization based routing algorithms, such as traditional ant colony algorithm, ant colony optimization-based location-aware routing for wireless sensor networks, and energy and path aware ant colony algorithm for routing of wireless sensor networks, in term of routing cost, energy consumption and network lifetime. Simulation results, for various random generated networks, demonstrate that the TSRA, obtains more balanced transmission among the node, reduces the energy consumption and cost of the routing, and extends the network lifetime.     

An Energy-Efficient Routing Algorithm Based on Relative Identification and Direction for Wireless Sensor Networks

In studies of wireless sensor networks (WSNs), routing protocols in network layer is an important topic. To date, many routing algorithms of WSNs have been developed such as relative direction-based sensor routing (RDSR). The WSNs in such algorithm are divided into many sectors for routing. RDSR could simply reduce the number of routes as compared to the convention routing algorithm, but it has routing loop problem. In this paper, a less complex, more efficient routing algorithm named as relative identification and direction-based sensor routing (RIDSR) algorithm is proposed. RIDSR makes sensor nodes establish more reliable and energy-efficient routing path for data transmission. This algorithm not only solves the routing loop problem within the RDSR algorithm but also facilitates the direct selection of a shorter distance for routing by the sensor node. Furthermore, it saves energy and extends the lifetime of the sensor nodes. We also propose a new energy-efficient algorithm named as enhanced relative identification and direction-based sensor routing (ERIDSR) algorithm. ERISDR combines triangle routing algorithm with RIDSR. Triangle routing algorithm exploits a simple triangle rule to determine a sensor node that can save more energy while relaying data between the transmitter and the receiver. This algorithm could effectively economize the use of energy in near-sensor nodes to further extend the lifetime of the sensor nodes. Simulation results show that ERIDSR get better performance than RDSR, and RIDSR algorithms. In addition, ERIDSR algorithm could save the total energy in near-sensor nodes more effectively.     

Energy Efficient Energy Hole Repelling (EEEHR) Algorithm for Delay Tolerant Wireless Sensor Network

Reducing energy consumption and increasing network lifetime are the major concerns in Wireless Sensor Network (WSN). Increase in network lifetime reduces the frequency of recharging and replacing batteries of the sensor node. The key factors influencing energy consumption are distance and number of bits transmitted inside the network. The problem of energy hole and hotspot inside the network make neighbouring nodes unusable even if the node is efficient for data transmission. Energy Efficient Energy Hole Repelling (EEEHR) routing algorithm is developed to solve the problem. Smaller clusters are formed near the sink and clusters of larger size are made with nodes far from the sink. This methodology promotes equal sharing of load repelling energy hole and hotspot issues. The opportunity of being a Cluster Head (CH) is given to a node with high residual energy, very low intra cluster distance in case of nodes far away from the sink and very low CH to sink distance for the nodes one hop from the sink. The proposed algorithm is compared with LEACH, LEACH-C and SEP routing protocol to prove its novel working. The proposed EEEHR routing algorithm provides improved lifetime, throughput and less packet drop. The proposed algorithm also reduces energy hole and hotspot problem in the network.     

Online Multicasting for Network Capacity Maximization in Energy-Constrained Ad Hoc Networks

In this paper, we present new algorithms for online multicast routing in ad hoc networks where nodes are energy-constrained. The objective is to maximize the total amount of multicast message data routed successfully over the network without any knowledge of future multicast request arrivals and generation rates. Specifically, we first propose an online algorithm for the problem based on an exponential function of energy utilization at each node. The competitive ratio of the proposed algorithm is analyzed if admission control of multicast requests is permitted. We then provide another online algorithm for the problem, which is based on minimizing transmission energy consumption for each multicast request and guaranteeing that the local network lifetime is no less than gamma times of the optimum, where gamma is constant with 0 < gammaleq 1. We finally conduct extensive experiments by simulations to analyze the performance of the proposed algorithms, in terms of network capacity, network lifetime, and transmission energy consumption for each multicast request. The experimental results clearly indicate that, for online multicast routing in ad hoc wireless networks, the network capacity is proportional to the network lifetime if the transmission energy consumption for each multicast request is at the same time minimized. This is in contrast to the implication by Kar et al. that the network lifetime is proportional to the network capacity when they considered the online unicast routing by devising an algorithm based on the exponential function of energy utilization at each node.     

基于改进LEACH的多簇头分簇路由算法

为了降低无线传感器网络(WSN)的能耗,延长网络的生存周期,提出一种多簇头双工作模式的分簇路由算法.算法对低功耗自适应集簇分层(LEACH)协议作了以下改进:采用多簇头双工作模式来分担单簇头的负荷,以解决单簇头因能耗较大而过早消亡的问题;选举簇头时充分考虑节点位置和节点剩余能量,并应用粒子群优化(PSO)算法优化簇头的选举,以均衡网络内各节点的能耗;建立簇与簇之间的数据传输路由,以减少簇间通信的能耗.仿真结果表明,算法有效降低了网络的能耗,延长了网络的生存周期.     

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.     

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.     

Energy-Efficient Routing Algorithm Based on Unequal Clustering and Connected Graph in Wireless Sensor Networks

Clustering and multi-hop routing algorithms substantially prolong the lifetime of wireless sensor networks (WSNs). However, they also result in the energy hole and network partition problems. In order to balance the load between multiple cluster heads, save the energy consumption of the inter-cluster routing, in this paper, we propose an energy-efficient routing algorithm based on Unequal Clustering Theory and Connected Graph Theory for WSN. The new algorithm optimizes and innovates in two aspects: cluster head election and clusters routing. In cluster head election, we take into consideration the vote-based measure and the transmission power of sensor nodes when to sectionalize these nodes into different unequal clusters. Then we introduce the connected graph theory for inter-cluster data communication in clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads. Simulation results show that, this new algorithm balances the energy consumption among sensor nodes, relieves the influence of energy-hole problem, improve the link quality, achieves a substantial improvement on reliability and efficiency of data transmission, and significantly prolongs the network lifetime.