基于CPK和能量的安全路由算法

无线传感网是由大量传感器节点组成的网络,具有无线通信、自组织、无中心的组网特性。针对无线传感器网络面临的众多安全问题,从组合公钥和节点能量入手,对LEACH进行改进,提出了一种基于CPK和能量的安全有效路由算法。通过仿真实验,改进的路由协议比LEACH具有更长的寿命,而且在安全性方面也进一步加强了。     

无线传感器网络能量均衡路由博弈算法

针对无线传感器网络节点能耗不均匀,容易形成网络分区的问题,提出了一种基于博弈论的无线传感网络路由选择策略,建立传感器节点之间以剩余能量为效用的博弈模型,求解并确定节点剩余能量最优的路由。仿真结果表明,所提出的路由选择策略可以有效地最大化节点的剩余能量,同时当该模型处于纳什均衡解时,每条路径的能耗处于均衡状态,有效地利用了传感器节点的能量资源,避免了网络能量的空洞,延长了网络的生命周期。     

无线传感网络移动分簇路由策略

无线传感网络(WSN)路由协议中,分簇路由具有拓扑管理方便、能量高效和数据融合简单等优点,成为当前重点研究的路由技术。通过研究各种环境下的移动传感器网络,有效地降低能耗则是研究移动无线传感器网络的重要目的之一。针对无线传感网络中移动性问题,基于LEACH协议,利用移动传感器网络中节点距离、速度和剩余能量等因素提出了能量高效的移动分簇路由算法。实验结果表明此算法能够较好地支持节点移动,从而降低网络能耗,延长网络生存时间。     

基于改进蚁群算法的无线传感器网络路由

为了降低节点能量消耗,延长网络生存的时间,提出了一种改进蚁群算法的无线传感器网络路由机制。首先将无线传感器网络服务质量分为3类,然后利用蚁群算法可以自适应网络状况动态性的优势,构建传感器节点转移函数和信息素更新规则,自适应构建数据路由,最后采用仿真模拟实验对算法性能进行检验。实验结果表明,相对于与现有无线传感器路由算法,本文通过引入蚁群优化机理挖掘传感器节点之间的关联性,数据传输延迟、可靠性和能量开销上具有更好的性能,使整个网络性能保持最优。     

基于博弈理论的无线传感器网络分布式节能路由算法

为了有效解决无线传感器网络路由节能问题,该文提出适合无线传感器网络的节能路由算法。在引入博弈理论概念建立网络模型的基础上,通过对于以往传感器网络簇首选择方法的研究,设计了一种基于博弈论的,兼顾节点剩余能量及簇首分布的节能路由DEER(DistributedEnergy-EconomicalRouting),大大节省了分布式决策网络协议的能量损耗。仿真证明了该方法在无线传感器网络中,能够有效地平衡网络负载,节省节点能量,延长网络寿命。     

基于改进蚁群算法的传感路由低负载方法

无线多媒体传感网络采用无线信号完成通信,会受到网络带宽的限制,实时传递能量较低,限制多媒体数据的传输。提出一种基于改进蚁群算法的无线多媒体传感网络的路由结构优化方法,根据改进蚁群算法,设计无线多媒体传感网络路由模块的硬件构造,改进无线多媒体传感网络路由优化过程,通过改进基本蚁群算法中的转移概率模型,对蚁群移动概率进行完善,确保负载的均衡,实现路由结构优化设计。实验结果说明,所提方法对无线多媒体网络中的路由结构进行改进后,均衡了网络能量消耗,使得无线传感网络节点的平均剩余能量更多,提高无线多媒体传感网络的运转周期。     

基于扇形分簇的无线传感器网络路由算法

无线传感网络中低功耗自适应聚类分簇(LEACH)路由算法等概率选取簇首节点,容易导致整个网络节点能量损耗出现极端化,减少网络生存时间。为此,提出一种针对簇首节点选取和分簇的改进LEACH算法。该算法把整个网络区域分为四个扇形区域,在每个区域内独立进行分簇路由;然后基站根据节点剩余能量和与基站的距离进行簇首节点选择,节点根据簇首节点和基站接收信号强度选择路由方式,以均衡网络能量消耗。仿真结果表明,改进LEACH算法的网络寿命是原有LEACH算法的150%,数据吞吐量提升了3倍。     

基于遗传算法的无线传感器网络自适应数据融合路由算法

针对移动代理以能量有效的方式收集相关性数据的问题,该文提出了一种新的基于遗传算法的自适应数据融合路由算法。算法选择移动代理路由时,根据数据传输和融合能量开销及节能增益,对移动代理迁移到每个传感器节点是否进行数据融合做自适应选择,以在信息收集过程中提高网络能量效率。仿真结果表明自适应数据融合路由算法的能量效率优于完全数据融合路由算法和最邻近启发式算法。     

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。     

一种WSN中分簇路由算法的改进

在无线传感器网络中,基于分簇的路由协议对提高网络的寿命有着重要作用,LEACH是一种应用比较广泛的层次路由协议。本文提出一种新的基于最优分簇的无线传感器网络分簇路由（LEACH-O）算法,在簇的形成过程考虑到节点的集中程度和节点的剩余能量,从而减少传感器节点的能量消耗,优化资源利用率。仿真实表明,与传统的LEACH算法相比,该算法配传感器节点间数据传输提供了高效路由,从而延长网络的生命周期。     

An Energy-Efficient Routing Protocol for Event-Driven Dense Wireless Sensor Networks

The routing energy efficiency of a wireless sensor network is a crucial issue for the network lifetime. In this article, we propose MICRO (MInimum Cost Routing with Optimized data fusion), an energy-efficient routing protocol for event-driven dense wireless sensor networks. The proposed routing protocol is an improvement over the formerly proposed LEACH and PEGASIS protocol, which is designed to be implemented mainly with node computations rather than mainly with node communications. Moreover, in the routing computation the proposed scheme exploits a new cost function for energy balancing among sensor nodes, and uses an iterative scheme with optimized data fusions to compute the minimum-cost route for each event-detecting sensor node. Compared to the PEGASIS routing protocol, MICRO substantially improves the energy-efficiency of each route, by optimizing the trade-off between minimization of the total energy consumption of each route and the balancing of the energy state of each sensor node. It is demonstrated that the proposed protocol is able to outperform the LEACH and the PEGASIS protocols with respect to network lifetime by 100–300% and 10–100%, respectively.     

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.     

Variable Bit Rate Flow Routing in Wireless Sensor Networks

Since energy constraint is a fundamental issue for wireless sensor networks, network lifetime performance has become a key performance metric for such networks. In this paper, we consider a two-tier wireless sensor network and focus on the flow routing problem for the upper tier aggregation and forwarding nodes (AFNs). Specifically, we are interested in how to perform flow routing among the nodes when the bit rate from each source node is time-varying. We present an algorithm that can be used to construct a flow routing solution with the following properties: (1) If the average rate from each source node is known a priori, then flow routing solution obtained via such algorithm is optimal and offers provably maximum network lifetime performance; (2) If the average rate of each source node is unknown but is within a fraction (epsiv) of an estimated rate value, then network lifetime by the proposed flow routing solution is within 2epsiv/1-epsiv from the optimum. These results fill in an important gap in theoretical foundation for flow routing in energy-constrained sensor networks.     

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.     

Optimal base station selection for anycast routing in wireless sensor networks

Energy constraints have a significant impact on the design and operation of wireless sensor networks. This paper investigates the base station (BS) selection (or anycast) problem in wireless sensor networks. A wireless sensor network having multiple BSs (data sink nodes) is considered. Each source node must send all its locally generated data to only one of the BSs. To maximize network lifetime, it is essential to optimally match each source node to a particular BS and find an optimal routing solution. A polynomial time heuristic is proposed for optimal BS selection and anycast via a sequential fixing procedure. Through extensive simulation results, it is shown that this algorithm has excellent performance behavior and provides a near-optimal solution.     

无线传感网络中基于蚁群的路由算法

In the wireless sensor networks, high efficient data routing for the limited energy resource networks is an important issue. By introducing Ant-colony algorithm, this paper proposes the wireless sensor network routing algorithm based on LEACH. During the construction of sensor network clusters, to avoid the node premature death because of the energy consumption, only the nodes whose residual energy is higher than the average energy can be chosen as the cluster heads. The method of repeated division is used to divide the clusters in sensor networks so that the numbers of the nodes in each cluster are balanced. The basic thought of ant-colony algorithm is adopted to realize the data routing between the cluster heads and sink nodes, and the maintenance of routing. The analysis and simulation showed that the proposed routing protocol not only can reduce the energy consumption, balance the energy consumption between nodes, but also prolong the network lifetime.     

Online Data Gathering for Maximizing Network Lifetime in Sensor Networks

Energy-constrained sensor networks have been deployed widely for monitoring and surveillance purposes. Data gathering in such networks is often a prevalent operation. Since sensors have significant power constraints (battery life), energy efficient methods must be employed for data gathering to prolong network lifetime. We consider an online data gathering problem in sensor networks, which is stated as follows: assume that there is a sequence of data gathering queries, which arrive one by one. To respond to each query as it arrives, the system builds a routing tree for it. Within the tree, the volume of the data transmitted by each internal node depends on not only the volume of sensed data by the node itself, but also the volume of data received from its children. The objective is to maximize the network lifetime without any knowledge of future query arrivals and generation rates. In other words, the objective is to maximize the number of data gathering queries answered until the first node in the network fails. For the problem of concern, in this paper, we first present a generic cost model of energy consumption for data gathering queries if a routing tree is used for the query evaluation. We then show the problem to be NP-complete and propose several heuristic algorithms for it. We finally conduct experiments by simulation to evaluate the performance of the proposed algorithms in terms of network lifetime delivered. The experimental results show that, among the proposed algorithms, one algorithm that takes into account both the residual energy and the volume of data at each sensor node significantly outperforms the others     

An ant colony optimization based routing algorithm for extending network lifetime in wireless sensor networks

Reducing the energy consumption of network nodes is one of the most important problems for routing in wireless sensor networks because of the battery limitation in each sensor. This paper presents a new ant colony optimization based routing algorithm that uses special parameters in its competency function for reducing energy consumption of network nodes. In this new proposed algorithm called life time aware routing algorithm for wireless sensor networks (LTAWSN), a new pheromone update operator was designed to integrate energy consumption and hops into routing choice. Finally, with the results of the multiple simulations we were able to show that LTAWSN, in comparison with the previous ant colony based routing algorithm, energy aware ant colony routing algorithms for the routing of wireless sensor networks, ant colony optimization-based location-aware routing algorithm for wireless sensor networks and traditional ant colony algorithm, increase the efficiency of the system, obtains more balanced transmission among the nodes and reduce the energy consumption of the routing and extends the network lifetime.     

Energy Efficiency Routing with Node Compromised Resistance in Wireless Sensor Networks

For the energy limited wireless sensor networks, the critical problem is how to achieve the energy efficiency. Many attackers can consume the limited network energy, by the method of capturing some legal nodes then control them to start DoS and flooding attack, which is difficult to be detected by only the classic cryptography based techniques with common routing protocols in wireless sensor networks (WSNs). We argue that under the condition of attacking, existing routing schemes are low energy-efficient and vulnerable to inside attack due to their deterministic nature. To avoid the energy consumption caused by the inside attack initiated by the malicious nodes, this paper proposes a novel energy efficiency routing with node compromised resistance (EENC) based on Ant Colony Optimization. Under our design, each node computes the trust value of its 1-hop neighbors based on their multiple behavior attributes evaluation and builds a trust management by the trust value. By this way, sensor nodes act as router to achieve dynamic and adaptive routing, where the node can select much energy efficiency and faithful forwarding node from its neighbors according to their remaining energy and trust values in the next process of data collection. Simulation results indicate that the established routing can bypass most compromised nodes in the transmission path and EENC has high performance in energy efficiency, which can prolong the network lifetime.