功率控制下基于能耗最小的Ad hoc网络路由选择算法

在节点MAC层发射功率可控情况下，提出了一种基于路径能量消耗最小的路由路径选择算法。该算法根据链路的能量消耗情况来进行路由路径选择，达到节约网络能量的目的。仿真表明．该算法可以动态调整网络路由路径，从而使所选路径的能量消耗达到最小。     

基于灰色关联的ZigBee网络混合路由算法研究

ZigBee网络混合路由算法(ZigBee Routing,ZBR)中将源目的节点之间的最小跳数作为唯一的路由度量因素。但随着节点能量消耗以及节点的频繁移动,ZBR算法的这一特性会造成网络间歇性连接,从而导致网络性能下降。本文提出一种选择最优分组转发路径的ZigBee网络混合路由算法—GRA-ZBR算法。GRA-ZBR算法在目的节点选择路径时引入灰色关联算法,综合考虑节点剩余能量、链路质量、节点剩余队列长度、以及路径长度等因素。仿真结果表明：GRA-ZBR算法可以有效提高网络分组投递率,降低平均端到端时延。     

基于灰色关联的ZigBee网络混合路由算法

ZigBee网络混合路由算法(ZigBee Routing,ZBR)中将源节点和目的节点之间的最小跳数作为唯一的路由度量因素.但随着节点能量消耗以及节点的频繁移动,ZBR算法的这一特性会造成网络间歇性连接,从而导致网络性能下降.提出一种选择最优分组转发路径的ZigBee网络混合路由算法(Grey Relational Algorithm based ZBR,GRA-ZBR).GRA-ZBR算法在目的节点选择路径时引入灰色关联算法,综合考虑节点剩余能量、链路质量、节点剩余队列长度以及路径长度等因素.仿真结果表明,GRA-ZBR算法可以有效提高网络分组投递率,降低平均端到端时延.     

认知无线网络中基于主用户行为的联合路由和信道分配算法

针对认知无线网络中主用户行为将导致频谱瞬时变化而影响路由稳定性的问题,提出了一种基于主用户行为的路由和信道联合分配算法。该算法通过采用呼叫模型对主用户行为建模,并根据动态源路由协议的路由寻找机制,在目的节点等待多个路由请求分组后选择受主用户行为影响最小的路由,然后沿着所选定路径的反方向传送路由回复分组并完成信道分配。理论分析证明了算法中的链路平均持续时间期望与主用户活动概率成反比且具有与网络节点数成正比的计算复杂度。仿真结果表明,该算法具有比Gymkhana路由方案更高的分组投递率和更低的平均分组时延。     

基于城市道路实时信息的VANET动态路由协议

文章提出动态路由算法DRDC(基于城市道路实时信息的VANET动态路由算法),该路由算法利用实时车流信息来动态创建基于道路的路径,并采用动态路由更新策略和基于下一跳速度矢量选择最优路径来降低端到端时延。仿真结果表明,与现有的VANET路由算法相比,该算法能有效改善分组的传输效率,降低端到端的传输时延。     

Ad Hoc网络中一种随机化分布式QoS路由算法

针对无线移动Ad Hoc网络(Mobile Ad Hoc Network,MANET),采用一种基于随机化分布式QoS路由算法RBAD(Random-Based Distributed QoS Routing Algorithm),该算法依据信道条件和业务量优化分组在多条路径上的路由,及寻找路由和存储路由表的代价,通过对结点排序,达到实现网络平均时延和平均消息复杂度最小的目标。仿真结果表明该算法能够以较小的路由消息开销获得较高的路由成功率,此外,算法具有可扩展性,可以应用于较大规模的Ad Hoc网络。     

考虑排队时延的系统保护通信网络路由选择算法

目前满足系统保护通信网络的路由算法是在综合时延和可靠性的要求下,计算一条快速且可靠传输的路径,而没有考虑到当电网发生故障或网络中通信量过大时,通信网络中许多节点的排队时延会极大地增加,忽略排队时延对路径传输总时延的影响会导致路径的错误选择,从而影响系统保护的实时性。针对此问题,提出了一种考虑排队时延的路由选择算法,用于计算信息传输总时延最小的最优路径,以提高系统保护通信的实时性。实验结果表明,通过本文提出的路由选择算法计算得到的路径在满足系统保护可靠性要求的基础上信息传输总时延最小。     

基于双层递归神经网络的路由优化算法

研究分组交换网的路由选择及流量分配问题,以网络的平均时延为优化目标函数。为使问题的解能实时、可靠地完成,将一种用于最短路径计算的双层递归神经网络应用于路由选择的流量导数法中。仿真结果表明,该算法在收敛的可靠性和计算的实时性方面有所提高。     

一种SDN架构下业务属性相关的多径路由算法

面对当前网络中流量的增长、业务种类的增多,SDN中多数的路由算法只支持一种QoS参数,没有兼顾对系统调度服务公平性的考虑,然而多参数限制的QoS 明显是NP 难问题,该问题用普通的路由算法难以解决,引进蚁群算法,在蚁群算法的基础上,将链路的时延、分组丢失率引入蚁群算法中,作为算法选择路径的依据,提出一种新的路由算法。该算法在对不同业务属性的数据流分类的基础上,根据网络的实时状况,为不同业务属性的数据流选择合适的路径,对网络中的数据流进行多路径传输。仿真实验表明,该算法能有效地降低数据流的时延、分组丢失率。     

基于蚁群优化的移动P2P网络路由选择算法

因为移动P2P网络具有动态性而且移动节点能量受限,提升移动P2P数据传输效率至关重要.利用蚁群优化算法,将蚂蚁的信息素与节点的能量和通信带宽结合起来,在蚁群选择路径时,减少其寻优路径上的信息素浓度,根据概率路由表中信息素的浓度对路由选择策略进行调整,避免网络拥塞和个别节点能量消耗过快,提出了一种移动P2P网络的多路径路由选择算法.实验结果表明,与EDSR路由协议相比,提出的算法能够降低节点的分组丢失率和端到端的平均时延,提高了网络的生存周期.     

A new traffic allocation algorithm in Ad hoc networks

~~A new traffic allocation algorithm in Ad hoc networks1. Su Kai-rong, ZHENG Wu,XIAO Shu-cheng, et al. Research on technology of mobile Ad hoc network access. Joural of Chongqing University of Posts and Telecommunications: Natural Science. 2005, 17(5): 61…     

Shortest route mobility assisted packet delivery with soft maximum delay guarantees in mobile ad hoc networks

In delay tolerant Mobile Ad hoc Networks (MANETs) node mobility can be exploited in order to reduce the source–destination path lengths in the expense of higher packet delivery delays. This paper addresses the problem of minimizing the average source–destination path length under a maximum delay constraint for packet delivery which is desirable to certain applications. Imposing packet delivery deadlines results in a certain percentage of multi-hop packet transmissions and poses the practical problem of selecting the optimum moment for the transmission. We propose an Optimal Stopping Rule algorithm for solving this problem and show how this algorithm can be extended in the case that a source–destination route is not always available by relaxing the hard delay constraint to a soft (probabilistic) constraint. The performance of this algorithm is compared to the ideal case of scheduling with perfect knowledge of the future and the trade-off between higher allowable delay and lower average path length is illustrated through several Matlab and ns-2 simulation results. As an application of path length minimization we explain how this can lead to energy consumption minimization in a MANET with light traffic loads (low probability of collisions). Finally, we briefly discuss how this path length minimization algorithm can guide the development of cross-layer throughput maximization algorithms with soft maximum delay guarantees.     

An adaptive‐aware energy and queue improvement of AOMDV

Because the node energy and network resources in the wireless sensor network (WSN) are very finite, it is necessary to distribute data traffic reasonably and achieve network load balancing. Ad hoc on‐demand multipath distance vector (AOMDV) is a widely used routing protocol in WSN, but it has some deficiencies: establishes the route by only using hop counts as the routing criterion without considering other factors such as energy consumption and network load; forwards route request in fixed delay resulting in building the nonoptimal path; and cannot update the path status after built paths. For the deficiency of AOMDV, this paper proposes a multipath routing protocol adaptive energy and queue AOMDV (AEQAOMDV) based on adaptively sensing node residual energy and buffer queue length. When sending a routing request, the forwarding delay of the routing request is adaptively adjusted by both the residual energy and the queue length of the intermediate node; when establishing routes, a fitness is defined as a routing criterion according to the link energy and the queue load, predicting the available duration of the node based on the energy consumption rate and adjusting the weight of the routing criterion by the available duration of the node; after the routes are established, the path information status are updated via periodically broadcasting Hello that carries the path information with the minimum fitness, making the source node update the path information periodically. By using NS‐2, simulations demonstrate that compared with AOMDV, AEQAOMDV has obvious improvements in increasing packet delivery ratio, reducing network routing overhead, reducing route discovery frequency, and decreasing the network delay. And AEQAOMDV is more suitable for WSN.     

Improved ant colony-based multi-constrained QoS energy-saving routing and throughput optimization in wireless Ad-hoc networks简

In order to establish a route supporting multi-constrained quality of service（QoS）, increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving routing algorithm（IAMQER） is proposed. The ant colony algorithm, as one of the available heuristic algorithms, is used to find the optimal route from source node to destination node. The proposed IAMQER algorithm, which is based on the analysis of local node information such as node queue length, node forwarding number of data packets and node residual energy, balances the relationship between the network throughput and the energy consumption, thus improving the performance of network in multi-constrained QoS routing. Simulation results show that this IAMQER algorithm can find the QoS route that reduce average energy consumption and improves network packet delivery ratio under the end-to-end delay and packet loss ratio constraints.     

车载自组织网中基于蚁群算法的延迟感知路由协议

针对城市道路环境下车载自组织网( VANETs)中通信性能下降以及数据传输失败的问题,提出了一种基于蚁群算法的延迟感知路由( ACDR)协议。首先,建立双向车道的数学延迟模型;然后,根据提出的端点十字路口( EI)的概念,ACDR利用蚁群优化( ACO)寻找最佳路线,其中前向蚂蚁根据本地路段延迟以及当前十字路口与目的节点的端点十字路口之间的全局时延来选择路径,后向蚂蚁则负责在返回路径时更新信息素,同时,相邻十字路口之间利用贪婪转发算法进行数据包的传递。最后仿真比较了ACDR协议与连通性感知路由( CAR)协议的性能,结果表明提出的ACDR协议的数据包的传输延迟小,丢包率低,通信性能好。     

Stability-based routing,link scheduling and channel assignment in cognitive radio mobile ad-hoc networks

One fundamental issue in cognitive radio mobile ad hoc networks (CR-MANETs) is the selection of a stable path between any source and destination node to reduce the end-to-end delay and energy consumption arisen from route reconstruction. In this way, we analyse the link stability by calculating the link life time that is dependent on failures caused by secondary users’ (SUs) movements and primary users’ (PUs) activities. We propose a joint stability-based routing, link scheduling and channel assignment (SRLC) algorithm in CR-MANETs, which is benefited from considering the link life time, amount of interference imposed on PUs and energy consumption. The proposed algorithm selects a frequency channel/time slot in a way that channel utilization and previous behaviours of SUs and PUs, are taken into account. In the proposed SRLC, the concept of load balancing is applied by avoiding to route packets through SUs with insufficient energy. The effectiveness of the proposed algorithm is verified by evaluating the aggregate interference energy, end-to-end delay, goodput and the energy usage per packet transmission under three different scenarios. The results show our proposed scheme finds better routes compared to the recently proposed joint stable routing and channel assignment protocol.

     

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

Sensor node energy conservation is the primary design parameters in wireless sensor networks (WSNs). Energy efficiency in sensor networks directly prolongs the network lifetime. In the process of route discovery, each node cooperates to forward the data to the base station using multi‐hop routing. But, the nodes nearer to the base station are loaded more than the other nodes that lead to network portioning, packet loss and delay as a result nodes may completely loss its energy during the routing process. To rectify these issues, path establishment considers optimized substance particle selection, load distribution, and an efficient slot allocation scheme for data transmission between the sensor nodes in this paper. The selection of forwarders and conscious multi‐hop path is selected based on the route cost value that is derived directly by taking energy, node degree and distance as crucial metrics. Load distribution based slot allocation method ensures the balance of data traffic and residual energy of the node in areal‐time environment. The proposed LSAPSP simulation results show that our algorithm not only can balance the real‐time environment load and increase the network lifetime but also meet the needs of packet loss and delay.     

一种基于蚁群的新型按能需求路由算法研究

提出了一种基于蚁群的新型按能需求路由算法(ARADE),针对移动网络节点剩余能量分布不均而导致网络生命周期短和蚁群算法收敛速度慢这两种缺陷做了相应的改进.存有路由信息的反向信息素表的引入简化了路由请求数据包的数据结构,将节点剩余能量、路径消耗能量以及跳数通过相应的影响因子归一化成一个参数作为路由性能评价值,以此来达到均衡整个网络节点剩余能量的目的.此外,迭代过程中信息素的最大值Гhigh可以当作参数进行一次自我迭代,使得当前节点维护在反向信息素表中的信息素值得到正反馈变化,从而加快整个算法的收敛速度.整个实验仿真是在NS-2平台上进行,随着数据包的传输速率的增加,它的生命周期、平均能量消耗和端到端延迟都会优于AODV.