一种蚁群竞争WSN能量均衡路由算法

针对无线传感器网络路由在能量控制和拥塞控制上的特殊要求，通过利用蚁群算法(ACS)对路由中最短路径的加速收敛的同时，兼顾网络节点能量均衡消耗，提出了一种新算法——AERA。该算法引入了多蚁群竞争机制，并将多蚁群挥发的信息素与网络节点能量参数共同构成路由控制因子。此算法能有效地控制网络拥塞，并使网络节点能量消耗相对均衡，延长了整个网络的生命周期，实现了高效路由与能量消耗的最优权衡。通过NS仿真实验验证了该方法的可行性，并给出了实验结果。     

一种基于蚁群算法的WSN路由算法

针对蚁群算法（Ant Colony System,ACS）在无线传感器网络路由中对网络拥塞问题和能量控制方面的不足,提出了一种改进的蚁群算法。该算法将蚁群的信息素与网络节点的能量结合起来,在蚁群算法收敛的同时,减少其最优路径上的信息素浓度,避免了网络拥塞和个别节点能量消耗过快的问题,从而延长了整个网络的生命周期。通过实验验证了该方法的可行性,并给出了实验结果。     

基于量子蚁群算法的无线传感器网络路由

无线传感器网络路由是无线传感器网络研究领域的一个研究热点;针对能最控制在无线传感器网络路由上的特殊要求,为了促使网络节点能量消耗相对均衡,研究者将蚁群算法应用于无线传感器网络的路由,但是蚁群算法在求解无线传感器路由问题时存在易于陷入局部最优和收敛速度慢等问题,将量子蚁群算法应用于无线传感器网络路由,用量子比特的概率幅表示蚂蚁当前位置信息,用量子旋转门更新蚂蚁携带的量子比特,用量子非门实现蚂蚁所在位置的变异;仿真实验表明该方法具有收敛速度快,解的质量高、稳定性好等优点,为蚁群算法在无线传感器网络中应用提出了一种新的解决方案.     

无线传感器网络多种群蚁群优化路由算法*

从无线传感器网络自身的特点出发,在蚁群算法的基础上,提出了一种适合该网络的多种群蚁群优化路由算法(MACO)。该算法设计了一个新的能够均衡传输能量消耗和节点剩余能量的蚂蚁前向移动的选择概率模型,并且能得到多条优化路径,使得均衡网络的能量消耗。仿真实验表明,该算法能延长网络的生存时间,并且可以有效地缓解网络拥塞。     

蚁群算法在无线传感器网络中的应用研究

针对蚁群算法（Ant ColoW System,ACS）在无线传感器网络路由中对网络拥塞问题和能量控制方面的不足,提出了一种改进的蚁群算法。该算法将蚁群的信息素与网络节点的能量结合起来,在蚁群算法收敛的同时,通过动态地调整信息素来减少其最优路径上的信息素浓度．通过采用最优、最差路径信息素全局更新策略加快搜索速度,避免了网络拥塞和个别节点能量消耗过快的问题。从而延长了整个网络的生命周期。通过实验验证了该方法的可行性,并给出了实验结果。     

基于多路径蚁群算法的无线传感器网络的路由

针对能量控制在无线传感器网络路由上的特殊要求,为了促使网络节点能量消耗相对均衡,将基本蚁群算法(ACS)应用于无线传感器网络的路由,提出一种基于多路径蚁群算法的无线传感器网络的路由(MACS).该算法利用蚁群的自组织、自适应和动态寻优能力,通过蚂蚁并行地寻找从源节点到达目的节点的最优路径和次优路径,使得网络中的节点不需要维护全局信息,形成多条传榆路径,延长了整个网络的生命期.仿真结果表明,该算法和定向扩散路由(DD)、基本蚁群算法及极大一极小蚁群算法(MMAS)相比,在路由代价和节能方面效果显著.     

无线传感器网络移动代理路由算法的仿真研究

路由选择问题是无线传感器网络中的核心问题.针对无线传感器网络节点能景、计算能力和通信能力有限等特点,为了降低能量开销和延长网络的生命周期,将蚁群算法和移动代理技术结合.提出一种新的无线传感器路由算法.考虑节点之间距离、路径能量消耗和节点剩余能量情况,使网络中的能量消耗更加均衡,同时对蚁群信息素更新规则进行了改进,加快了蚁群算法收敛到最优解的速度.仿真结果表明,与其它移动代理路由算法相比,算法在全局性和收敛速度方面都有所提高,有效地减少冗余数据传输,降低通信消耗,延长网络的生存周期,为路由传感器设计提供了参考.     

基于蚁群的无线传感器网络路由算法

针对无线传感器节点能量、通信能力及计算能力有限等特点,将蚁群算法应用于无线传感器网络,提出一种改进的蚁群路由算法,考虑了节点的能量、距离、通信半径和传输方向等参数.实验结果表明:该算法有效地减少了网络能量消耗、节点死亡数、路由跳数和数据传输的路径长度,延长了无线传感器网络的寿命,实现无线传感器网络在通信过程中快速、节能的路由。     

基于多蚁群算法的无线传感器网络路由的跨层设计

针对事件驱动型无线传感器网络对数据传输的强实时性和高可靠性的要求,将统计获得的节点接入效率和负载队列长度等MAC层状态信息作为路由度量参数。考虑到蚂蚁网络算法在重负荷网络中存在传输延迟大、聚合速度慢等缺陷,提出了一种基于多蚁群算法的负载感知和高效接入的跨层路由协议,该协议把节点的单跳延迟、负载及带宽接入效率等参数作为路径的启发值进行路由优化。仿真结果表明,基于多蚁群算法的路由协议能够保证数据传输的实时性,能够实现无线传感器网络的拥塞控制及负载平衡。     

蚁群算法在传感器网络数据融合中的应用

研究无线传感器网络数据融合优化问题,采集数据过程节点间存在大量的冗余数据,需对数据进行融合,提高数据传输效率。为了更好地消除冗余数据,提出一种采用蚁群算法的传感器网络数据融合方法。通过建立传感器数据的传输初始路由,再用蚁群算法找到最佳数据路由,即数据传输最优传感器节点序列,从而实现数据融合。仿真结果表明,蚁群算法能够有效消除冗余数据,减少网络中数据传输量,降低传感器节点能量消耗,延长整个网络的寿命。     

模糊需求车辆路径问题及其启发式算法

对模糊需求信息条件下的车辆路径问题进行策略分析，提出解决此类问题的改进蚁群算法。采用多蚁群协作，修改信息素更新规则，根据收敛要求动态调整主要参数等对蚁群算法进行改进，应用该方法解决机会约束策略和可能性策略下的模糊需求车辆路径问题。实验结果证明了改进算法对优化模糊需求车辆问题非常有效。     

A decentralized energy-based diffusion algorithm to increase the lifetime of MANETs

In this paper, we introduce a novel approach to improve overall lifetime in mobile ad hoc networks. Given the energy constraint on each node, this problem is formulated as an energy-controlled load balancing problem. Thus, our approach is quite different from usual energy-efficient routing or topology control methods. The proposed algorithm is fully distributed and ensures that each node will cooperate in proportion to its remaining energy, increasing the network lifetime. The relevance of the algorithm is evaluated through both theoretical analysis and simulations.     

Long-term information collection with energy harvesting wireless sensors: a multi-armed bandit based approach

This paper reports on the development of a multi-agent approach to long-term information collection in networks of energy harvesting wireless sensors. In particular, we focus on developing energy management and data routing policies that adapt their behaviour according to the energy that is harvested, in order to maximise the amount of information collected given the available energy budget. In so doing, we introduce a new energy management technique, based on multi-armed bandit learning, that allows each agent to adaptively allocate its energy budget across the tasks of data sampling, receiving and transmitting. By using this approach, each agent can learn the optimal energy budget settings that give it efficient information collection in the long run. Then, we propose two novel decentralised multi-hop algorithms for data routing. The first proveably maximises the information throughput in the network, but can sometimes involve high communication cost. The second algorithm provides near-optimal performance, but with reduced computational and communication costs. Finally, we demonstrate that, by using our approaches for energy management and routing, we can achieve a 120% improvement in long-term information collection against state-of-the-art benchmarks.     

基于改进支持向量机的无线传感器网络路由优化算法

为了解决当前无线传感器网络路由算法能耗大的缺陷,设计了基于改进支持向量机的无线传感器网络路由算法(PSO-LSSVM)。首先建立了无线传感器网络路由能耗的数学模型,然后通过组合模型的节点剩余能量进行在线估计,选择能耗最小的路由进行数据传输,最后在Matlab 平台上对该算法的性能进行测试。结果表明,PSO-LSSVM可以快速找到能耗最小的路由,改善了数据传输的可靠性,降低了数据的传输时延,而且综合性能优于对比的无线传感器网络路由算法。     

New routing framework base on rumor routing in wireless sensor networks

Rumor routing is a classic routing algorithm based on agents’ random walk. This paper proposes a novel approach based on this routing algorithm. Here, we try to improve the latency and energy consumption of the traditional algorithm using propagation of query and event agents within straight lines, instead of using purely random walk paths. As can be seen in our results, this method improves the delivery ratio of the queries which is a drawback of traditional rumor routing. Due to the reduction of final path length between source and destination, we introduce a second layer geographical routing. Moreover, a method is proposed to reduce the cost of localization equipments by using cheaper equipments like AoA antennas. In order to compare the performance measures with traditional algorithm, a simulation framework is developed and extensive simulations are performed.     

无线传感器网络节能的高效路由算法

无线传感器网络节能问题,是当今研究的热点问题.本文首先对无线传感器网络的体系结构进行了介绍,然后依据无线传感器网络的体系结构给出了无线传感器网络的一个研究模型.在对现有的无线传感器网络的路由算法进行综合考虑的基础上,给出了一个新的无线传感器网络节能的高效路由算法.最后对此新算法进行了简要的性能评价.     

A novel forwarding and routing mechanism design in SDN-based NDN architecture

Combining named data networking (NDN) and software-defined networking (SDN) has been considered as an important trend and attracted a lot of attention in recent years. Although much work has been carried out on the integration of NDN and SDN, the forwarding mechanism to solve the inherent problems caused by the flooding scheme and discard of interest packets in traditional NDN is not well considered. To fill this gap, by taking advantage of SDN, we design a novel forwarding mechanism in NDN architecture with distributed controllers, where routing decisions are made globally. Then we show how the forwarding mechanism is operated for interest and data packets. In addition, we propose a novel routing algorithm considering quality of service (QoS) applied in the proposed forwarding mechanism and carried out in controllers. We take both resource consumption and network load balancing into consideration and introduce a genetic algorithm (GA) to solve the QoS constrained routing problem using global network information. Simulation results are presented to demonstrate the performance of the proposed routing scheme.     

An aggregated clustering approach using multi-ant colonies algorithms

This paper presents a multi-ant colonies approach for clustering data that consists of some parallel and independent ant colonies and a queen ant agent. Each ant colony process takes different types of ants moving speed and different versions of the probability conversion function to generate various clustering results with an ant-based clustering algorithm. These results are sent to the queen ant agent and combined by a hypergraph model to calculate a new similarity matrix. The new similarity matrix is returned back to each ant colony process to re-cluster the data using the new information. Experimental evaluation shows that the average performance of the aggregated multi-ant colonies algorithms outperforms that of the single ant-based clustering algorithm and the popular K-means algorithm. The result also shows that the lowest outliers strategy for selecting the current data set has the best performance quality.     

多蚁群伪并行优化算法

针对传统蚁群算法容易出现早熟和停滞现象,提出了一种多蚁群伪并行优化算法,将蚁群分成若干个子蚁群,在各子蚁群中引入信息素平滑机制,通过设计迁移算子,使多个子蚁群并行、协同寻优,从而使算法跳离局部最优解。类比实验表明,该算法比传统的蚁群算法具有更好的搜索全局最优解的能力。     

Ad Hoc移动网络多路径研究

在Ad Hoc移动网络中,由于结点的移动性,网络拓扑结构的易变性,路由成为研究的热点和难点。当前AdHoc路由协议一般都是单路径协议。然而由于多路径路由方式可以大大减少路由开销,提高数据传输率,减少网络拥塞,越来越多的研究表明,它将是未来Ad Hoc网络路由的主要方式。本文介绍了几种典型的多路径路由协议,并对这些多路径协议进行评价,对其性能进行比较,然后介绍多路径协议在QoS、能源和安全方面的应用,最后指出未来多路径研究的关键问题。