一种SRIO网络负载均衡最短路径路由算法

在串行RapidIO传输过程中,路由选路算法是影响传输性能的重要因素之一。针对串行高速输入-输出(SRIO)网络深度优先搜索分配路径非最优问题,提出一种负载均衡最短路径路由算法。通过广度优先搜索对SRIO网络中的节点进行枚举并建立网络拓扑信息,以路由跳数定义路由的成本,根据改进Floyd-WarShall算法计算并保存交换节点间的K最短路径。给出预期负载的概念和链路上的路由路径数量来定义链路的负载,采用负载均衡算法从K最短路径中进行选路,建立SRIO网络最短路径约束的负载均衡路由。实验结果表明,与深度遍历路由算法、最小跳数算法相比,该算法在网络传输平均跳数、链路平均负载和链路负载均衡方面有更好的表现,能够有效提升SRIO路由网络的稳定性。     

基于改进AOMDV路由协议的WSNs拥塞控制和能耗均衡策略

无线传感器网络WSNs中数据流的突发、节点能量有限和多对一数据传输等特性导致其很容易发生网络拥塞和节点能量的非均衡消耗,而采用多路径方式进行数据传输,不仅可以缓解网络拥塞,而且也能达到网络能量均衡消耗的目的。AOMDV协议是一种面向Ad-Hoc网络的反应式多路由协议,首先提出了一种改进的AOMDV协议—I_AOMDV协议,在路由发现阶段不再使用发生拥塞和低能量的节点,而在路由维护阶段则仅使用HELLO信息交换邻居节点的"剩余能量"和"队列长度",同时在路径列表中添加了"拥塞恢复时间"和"能量剩余标志位",从而使I_AOMDV协议更适应于静态WSNs的数据传输。基于I_AOMDV协议,进一步提出了新的网络拥塞控制和能耗均衡策略,其中,拥塞控制策略采用新的拥塞检测方案,并为发生拥塞的最短路径设置了"拥塞恢复时间";而能耗均衡策略则通过为节点的每条路径设置"能量剩余标志位"来解决能量的非均衡消耗问题。仿真实验结果表明,基于I_AOMDV的拥塞控制和能耗均衡策略,可以减少路由协议的开销,有效降低数据丢包率和节点剩余能量的差异性。     

Load sensitive topology control: Towards minimum energy consumption in dense ad hoc sensor networks

Sensor networks are usually composed of tiny and resource constraint devices, which make energy conservation a vital concern of their design and deployment. Reducing energy consumption has been addressed through different aspects till now. Topology Control (TC) is a well-known approach which tries to determine transmission ranges of nodes to optimize their energy utilization while keeping some network properties like connectivity. However, in current TC schemes, the transmission range of each node is mostly accounted as the exclusive estimator for its energy consumption while ignoring the amount of data it sends or relays. In this paper, we deliberately reformulate the problem of topology control, regarding both network load and transmission range parameters. Our approach is particularly formulated for dense sensor networks with one or more base stations. The problem is considered in three different environmental conditions and then, proper mathematical relations are presented to find the optimum solutions. Finally, we show the advantages of our proposal through experiments.     

基于蚁群优化的WSN功率自适应路由算法

为节省节点能量开销,延长无线传感器网络(WSN)的生命周期,在研究蚁群优化算法的基础上,提出一种基于蚁群优化的功率自适应路由算法。在蚂蚁寻路时考虑节点的传输方向、剩余能量和节点间距离。寻找到一条最优路径后,根据相邻两节点间的距离调整节点的发射功率,避免功率过大造成能量浪费。仿真实验结果表明,在节点非均匀分布的情况下,该算法能够有效节省网络开销,延长网络生命周期。     

Dynamic load balancing in IP-over-WDM optical burst switching networks

In this paper, we consider the problem of dynamic load balancing in wavelength division multiplexing (WDM)-based optical burst switching (OBS) networks. We propose a load balancing scheme based on adaptive alternate routing aimed at reducing burst loss. The key idea of adaptive alternate routing is to reduce network congestion by adaptively distributing the load between two pre-determined link-disjoint alternative paths based on the measurement of the impact of traffic load on each of them. We develop two alternative-path selection schemes to select link-disjoint alternative paths to be used by adaptive alternate routing. The path selection schemes differ in the way the cost of a path is defined and in the assumption made about the knowledge of the traffic demands. Through extensive simulation experiments for different traffic scenarios, we show that the proposed dynamic load balancing algorithm outperforms the shortest path routing and static alternate routing algorithms.     

WSN中基于最大最小化的优化路由算法

无线传感器网络(WSN)由能量受限的节点组成,需要设计路由算法优化节点的能耗。文章以最大化网络生存时间为目标,基于最大最小化模型提出了优化路由算法,定义了数据发送矩阵,设计了转发节点选择机制,以避免路由回路;基于节点收发数据的能耗及剩余能量,设计了求解优化路由的数学规划模型,优化了传感器节点的数据发送路径和发送量,均衡了节点的能量消耗。仿真结果表明,该算法能有效地均衡节点的能耗,延长网络生存时间。     

无线传感器网络中一种基于标记的能量平衡路由

为实现数据的高效传输和网络生命期的最大化,提出了一种基于标记的能量平衡（LBEB）路由。该路由先向网络中嵌入多棵独立最短路径树,以构建一个虚拟树型标记系统,然后基于此标记系统设计针对不同数据类型的转发策略：紧急数据使用贪婪策略转发以保障其时延要求;而平常数据则综合考虑邻居节点的负载和剩余能量情况使用平衡策略转发以缓解拥塞并均衡节点能耗。2种策略相辅相成,共同完成预期目标。仿真结果表明：LBEB能以适量开销获得较好的路由性能,并且能在满足数据时延要求的同时均衡网络能耗从而使网络生命期最大化。     

Network coding based reliable disjoint and braided multipath routing for sensor networks

This paper presents network coding based reliable disjoint and braided multipath routing (NC-RMR ) for sensor networks, which forms multipath by hop-by-hop method and only maintains local path information of each node without establishing end-to-end paths. Neighbors of each local node are divided into groups according to their hops to sink nodes to improve the network load balancing. For further performance improvement of NC-RMR with disjoint multipath model, local nodes select their own backup nodes in neighbor nodes to form additional logical paths, which implement a braided multipath model. Security advantages of NC-RMR with multipath and network coding mechanisms are analyzed. Analytical and simulation results prove that braided multipath routing model has better performance over disjoint model, and NC-RMR protocol can reduce the required number of transmission paths, ensure load balance of sensor network system, reduce the energy consumption of nodes.     

基于工业无线网络性能评价的规划路径算法

针对路由节点查找消息路径的局限性,提出了一种网关设备规划消息路径的算法。该算法结合工业无线网络通信数据的规律性,在考虑时延、能耗、可靠传输和负载均衡方面的性能综合评价之后,找出一种路径组合,避免消息拥塞和干扰,提高通信性能。然后,设计了仿真实验来对比规划路径与AODV查找路径两种情况下的通信性能。实验结果证明,规划的消息路径下的通信性能更好。     

云环境下利用用户到数据中心建模的高效节能路由算法

针对云计算用户、服务、供应商和数据中心的密度不断增长导致传输数据、网络流量和基础设施的大量能耗问题,提出针对云数据的高效节能路由算法。其目的是在用户和数据中心之间定位出最低能量消耗路线,同时确保用户需求。首先,对用户到数据中心的连通性进行建模,分析了网络拓扑结构;然后为了用户意图最简化和能量最小化,通过遍历节点最小数的基线最短路径算法进行评估,将用户任务通过最节能路径发送到数据中心,从而最小化能量损耗和服务响应时间(SRT)。实验的网络拓扑结构使用互联网服务提供商(ISP)的分支设计。实验结果表明提出的算法具有更短的路由路径长度和更低的路由能耗。此外,最短路径方法只有在成功发送或接收之后才能确定最节能的路由。     

量子密钥分发网络端端密钥协商最优路径选择算法

针对量子密钥分发(QKD)网络端端密钥协商路径选择问题,设计了一种基于改进Dijkstra算法的端端密钥协商最优路径选择算法。首先,基于有效路径策略,剔除网络中的失效链路;然后,基于最短路径策略,通过改进Dijkstra算法,得到密钥消耗最少的多条最短路径;最后,基于最优路径策略,从多条最短路径中选择一条网络服务效率最高的最优路径。分析结果表明,该算法很好地解决了最优路径不唯一、最优路径非最短、最优路径非最优等问题,可以降低QKD网络端端密钥协商时密钥消耗量,提高网络服务效率。     

Energy-efficient multipath routing in wireless sensor network considering wireless interference

Due to the energy and resource constraints of a wireless sensor node in a wireless sensor network (WSN), design of energy-efficient multipath routing protocols is a crucial concern for WSN applications. To provide high-quality monitoring information, many WSN applications require high-rate data transmission. Multipath routing protocols are often used to increase the network transmission rate and throughput. Although large-scale WSN can be supported by high bandwidth backbone network, the WSN remains the bottleneck due to resource constraints of wireless sensors and the effects of wireless interference. In this paper, we propose a multipath energy-efficient routing protocol for WSN that considers wireless interference. In the proposed routing protocol, nodes in the interference zone of the discovered path are marked and not allowed to take part in the subsequent routing process. In this way, the quality of wireless communication is improved because the effects of wireless interference can be reduced as much as possible. The network load is distributed on multiple paths instead of concentrating on only one path, and node energy cost is more balanced for the entire wireless network. The routing protocol is simulated in NS2 software. Simulation result shows that the proposed routing protocol achieves lower energy cost and longer network lifetime than that in the literature.     

WSN中基于改进樽海鞘群算法的分簇路由协议

针对无线传感器网络能耗不均衡、网络生存期短的问题,提出了一种基于改进樽海鞘群算法的分簇路由协议;所提协议分别从分簇阶段和稳定传输阶段进行优化;分簇阶段,首先对樽海鞘群算法进行改进,引入了精英反向学习策略和动态学习机制,克服了基本樽海鞘群算法局部勘探和全局开发能力不平衡的问题;其次考虑节点的剩余能量和地理位置设计高效的适应度函数,以选出最优簇首,平衡簇间负载;稳定传输阶段,设计了基于最小生成树的簇间路由算法,为簇首构建最优传输路径,在缓解簇首负载的同时提高网络能量利用率;簇内通信阶段,引入轮询控制机制帮助节点构建传输调度,提高时隙利用率;对所提协议进行仿真实验,并与几种前沿协议进行对比;对比结果表明,所提出的基于改进樽海鞘群算法的分簇路由协议能够有效地改善网络性能,从而延长传感网对于目标区域的监测时间,并提高基站接受到的数据包总量。     

一种带有可控阈值参数的分簇路由优化算法

针对传感网中大量冗余数据导致通信频繁中断的问题,提出一种带有可控阈值参数的分簇路由优化算法。引入蚁群算法中的适应度函数和启发式函数,使得下一跳簇首节点的选择更具针对性,实现网络路由树的建立与事件域节点的分布式成簇。利用可控阈值参数和变异系数对网络路由所选最短路径进行优化,保证节点能量消耗较低的同时全网延时最小,并通过全局信息素的更新策略抑制长链路的产生,以均衡全网能量并延长网络生存周期。实验结果表明,该算法与DMOA和MTTA算法在抑制网络能量消耗和延长网络生存周期方面进行对比,其性能指标平均提升了13.72%和12.06%。     

Joint coverage and link utilization for fast IP local protection

To mitigate the impact of failures, many IP Fast Local Recovery (IPFLR) schemes have been proposed to reroute traffic in the events of failures. However, the existing IPFLR schemes either aimed to find the alternate backup routes to protect failures, or focused on balancing the traffic load routed on the backup routes. Furthermore, in Internet, flows are often managed by shortest path routing, and therefore purely determining the backup routing paths is not sufficient in protecting the error-prone networks. In this paper, we propose a Simulated Annealing based Load balancing and Protection (SALP) scheme to determine link weights for balancing link utilization in the non-failure state and simultaneously construct backup routing tables for protecting any single link failure in IP networks. In our proposed scheme, the two most significant issues, (1) load balancing and (2) coverage, are jointly considered to recover the network operation from single link failures. In the proposed scheme, upon a failure, only the nodes adjacent to a failure are activated to divert affected traffic to backup paths without disturbing regular traffic. Numerical results delineate that the proposed scheme achieves high coverage rate and load balancing at the expense of slightly increasing the entries of backup routing table.     

Distributed routing in packet-switching networks by counterpropagation network

Routing is a problem of considerable importance in a packet-switching network, because it allows both optimization of the transmission speeds available and minimization of the time required to deliver information. In classical centralized routing algorithms, each packet reaches its destination along the shortest path, although some network bandwidth is lost through overheads. By contrast, distributed routing algorithms usually limit the overloading of transmission links, but they cannot guarantee optimization of the paths between source and destination nodes on account of the mainly local vision they have of the problem. The aim of the authors is to reconcile the two advantages of classical routing strategies mentioned above through the use of neural networks. The approach proposed here is one in which the routing strategy guarantees the delivery of information along almost optimal paths, but distributes calculation to the various switching nodes. The article assesses the performance of this approach in terms of both routing paths and efficiency in bandwidth use, through comparison with classical approaches.     

能量高效的无线传感器网络路由协议

针对目前无线传感器网络分簇路由协议存在的节点能耗不均衡的问题,提出一种基于分簇思想的能量高效的多跳路由协议(EEMR)。该协议首先基于节点临近度将网络划分成簇,采用簇首自适应轮转模式优化簇内节点通信的能量消耗,以高剩余能量短路径向心角的适应度路由算法均衡簇间通信负载和能量消耗,有效避免多跳路由中出现的能量消耗不均衡问题。仿真结果表明,EEMR协议能有效均衡网络内节点的能量消耗,显著延长无线传感器网络的生命期并提高网络能量利用率。     

Transient chaotic neural network-based disjoint multipath routing for mobile ad-hoc networks

Due to mobility of wireless hosts, routing in mobile ad-hoc networks (MANETs) is a challenging task. Multipath routing is employed to provide reliable communication, load balancing, and improving quality of service of MANETs. Multiple paths are selected to be node-disjoint or link-disjoint to improve transmission reliability. However, selecting an optimal disjoint multipath set is an NP-complete problem. Neural networks are powerful tools for a wide variety of combinatorial optimization problems. In this study, a transient chaotic neural network (TCNN) is presented as multipath routing algorithm in MANETs. Each node in the network can be equipped with a neural network, and all the network nodes can be trained and used to obtain optimal or sub-optimal high reliable disjoint paths. This algorithm can find both node-disjoint and link-disjoint paths with no extra overhead. The simulation results show that the proposed method can find the high reliable disjoint path set in MANETs. In this paper, the performance of the proposed algorithm is compared to the shortest path algorithm, disjoint path set selection protocol algorithm, and Hopfield neural network (HNN)-based model. Experimental results show that the disjoint path set reliability of the proposed algorithm is up to 4.5 times more than the shortest path reliability. Also, the proposed algorithm has better performance in both reliability and the number of paths and shows up to 56% improvement in path set reliability and up to 20% improvement in the number of paths in the path set. The proposed TCNN-based algorithm also selects more reliable paths as compared to HNN-based algorithm in less number of iterations.     

基于蚁群的无线传感器网络能量均衡非均匀分簇路由算法

无线传感器网络(WSN)路由中,节点未充分考虑路径剩余能量及链路状况进行的路由会造成网络中部分节点网络寿命减少,严重影响网络的生存时间。为此,将蚁群优化算法与非均匀分簇路由算法相结合,提出一种基于蚁群优化算法的无线传感器非均匀分簇路由算法。该算法首先利用考虑节点能量的优化非均匀分簇方法对节点进行分簇,然后以需要传输数据的节点为源节点,汇聚节点为目标节点,利用蚁群优化算法进行多路径搜索,搜索过程充分考虑了路径传输能耗、路径最小剩余能量、传输距离和跳数、所选链路的时延和带宽等因素,最后选出满足条件的多条最优路径,完成源目的节点间的信息传输。实验表明,该算法充分考虑路径传输能耗和路径最小剩余能量、传输跳数及传输距离,能有效延长无线传感器网络的生存期。     

基于免疫连通模型的多路径传输选择算法

为解决无线传感器网络（WSN）中节点部署不均匀造成的节点能量消耗大、数据传输可靠性低的问题，提出了一种基于免疫连通模型的多路径传输选择算法。当数据传输发生故障时，免疫机制被用来选择路径的适应度函数，从而达到优化传输路径和减少节点能耗的目的。实验从网络寿命、端到端传输延迟、覆盖率、传输可靠性、载荷分布等指标对算法进行评价。实验结果显示，所提算法可更好地平衡负载，延长网络的生命周期，以及保证数据传输的可靠性。所提算法可以应用于对能量效率、可扩展性、延长网络寿命和降低网络开销有较高要求的传感器网络设计。