基于蚁群优化算法的Ad Hoc网络路由协议研究

路由协议的研究是Ad Hoc网络的重点和难点。文章在分析已有Ad Hoc网络路由协议的基础上,结合蚁群算法的原理,首次提出了根据蚂蚁释放有效信息素的比率,引入服务代理来减少蚂蚁代理开销的路由协议。在网络仿真平台NS-2上进行了算法仿真实现,并与现有的典型协议在不同的实验场景下进行性能分析比较,仿真结果表明新的基于蚁群优化算法的Ad Hoc网路由算法具有比其它算法更好的性能。     

基于改进蚁群算法的卫星光网络波长分配方法

路由与波长分配是下一代光网络的需要解决的核心问题之一。本文采用智能蚁群算法,研究了卫星光网络的路由与波长分配问题,为通信请求寻找最优的数据传输光路径。基于请求区域受限策略(Restricted Request Area,RRA)和链路波长负载平衡策略,建立了考虑传输延迟和波长连续性约束的双主星分布式星群节点结构光网络系统模型。利用智能蚁群路由和波长分配(Smart Ant Colony Routing AndWavelength Assignment,SAC-RWA)算法求解系统模型,以找到具有稀疏波长转换的卫星光网络中最小成本波长路径。所提出的算法允许单个蚂蚁同时完成路由和波长分配,仿真结果表明,RRA能够明显改进卫星光网络的性能,以略微增加拥塞率的代价显著降低了计算复杂度。     

一种基于蚁群优化的多媒体传感器网络 服务感知路由算法

本文针对多媒体传感器网络中三类基本服务:异常事件告警服务、信息查询服务以及流媒体查询服务,分析了不同服务的QoS需求,并抽象出多媒体传感器网络QoS路由模型.进而,利用改进的蚁群算法,设计了一个基于蚁群优化的服务感知路由算法ASAR (Ant-colony optimization based Service Aware Routing).本文设计服务感知的路由协议,旨在依据各类媒体数据包不同的QoS需求,选择相应的路由以合理利用全网资源、提高网络性能.最后,我们通过NS2仿真表明了较其他路由算法,本文提出的方法能够为多媒体传感器网络的多种服务提供更好的QoS保障,同时,比传统的蚁群算法具有更好的收敛性.     

基于分级结构的优化QoS路由算法

Ad hoc(自组织)网络中包含延迟、延迟抖动、带宽和丢包率等约束条件在内的QoS(服务质量)路由问题,是一个NP完全问题,传统的平面QoS蚂蚁路由算法难以解决提高算法全局搜索能力和加快收敛速度之间的矛盾。针对以上问题,提出了HQAC(分级QoS蚁群)算法,在分级的基础上对蚁群算法的路由搜寻过程进行了改进,同时对信息素更新公式进行了优化。仿真结果表明,与传统的QoS路由算法相比,HQAC算法在搜索全局最优解,尤其是收敛速度等性能上有了很大的提高。     

基于分级结构的优化QoS路由算法北大核心

Ad hoc(自组织)网络中包含延迟、延迟抖动、带宽和丢包率等约束条件在内的QoS(服务质量)路由问题,是一个NP完全问题,传统的平面QoS蚂蚁路由算法难以解决提高算法全局搜索能力和加快收敛速度之间的矛盾。针对以上问题,提出了HQAC(分级QoS蚁群)算法,在分级的基础上对蚁群算法的路由搜寻过程进行了改进,同时对信息素更新公式进行了优化。仿真结果表明,与传统的QoS路由算法相比,HQAC算法在搜索全局最优解,尤其是收敛速度等性能上有了很大的提高。     

基于改进蚁群算法的Ad hoc路由协议的研究

现有Ad hoc网络路由协议技术研究中,路由稳定性和可靠性问题尚未得到很好解决,不能很好地适应Adhoc网络.针对已有Ad hoc路由技术中存在的开销大以及网络稳定性较低的问题,该文引入蚁群算法,并对其进行改进.研究基于改进蚂蚁算法的Ad hoc路由协议,并与比较成熟的AODV(Ad hoc On-Demand Distance Vector)进行对比.仿真实验结果表明,通过发挥网络中结点群体功能,新协议减小了端对端传输延时,改善了数据包传输成功率与协议开销,有效地提高了网络的稳定性和通信效率.     

车载自组织网络中基于十字路口的地理感知路由协议

为了解决城市道路多十字路口,对单个车辆节点运动感知不敏感所带来的通信性能下降问题,提出一种车载自组织网络中基于十字路口的地理感知路由(IGPR)协议,通过网络网关选择道路十字路口,形成骨干路由,在保证高连通概率的同时满足时延和误比特率要求.在双向道路模型的基础上分析获得平均时延和平均跳数的数学计算式.仿真结果表明,IGPR协议与FRGR协议、VRR协议相比,传输时延小,跳数少,通信性能好.     

一种基于改进蚁群算法的选播路由算法

为了在网络负载较大的情况下实现多目标多路径的选播路由,该文根据蚂蚁寻径与选播路由的相似性,提出了一种基于改进蚁群算法的选播路由算法。在运用数据包传输的历史信息来模拟路径信息素的基础上,增加了目标地址泛洪负载信息来模拟食物气味散发的过程,使得各个节点可以获得服务器和链路的最新信息。节点根据路径上的信息素、食物的气味以及链路的可见度等综合生成概率表,作为后继蚂蚁路径选择的依据。运用NS-2对该算法进行仿真,测试结果表明它可以减少传输时延,降低服务器负载的波动幅度,实现链路的负载均衡,增加网络的容量,提高选播服务的可扩展性。     

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.     

基于蚁群算法的典型路由协议的比较研究

针对Ad hoc网络拓扑结构的多变和基本蚁群算法易失去多解的情况,在对算法的节点选择进行改进后,提出把蚁群算法与DSR、AODV和DSDV相结合,即ant-DSR、ant-AODV和ant-DSDV。利用改进的蚁群算法寻找最优路径,在节点速率、停留时间这2种不同场景下分析比较了端到端时延、吞吐量、路由开销和跳数等参数的性能。仿真结果表明,先应式路由协议比按需路由协议在提高性能上更适合于蚁群算法,但却增加了路由开销,并且每个节点产生最优路径时需要更多的计算。     

Multi-constraints QoS routing optimization based on improved immune clonal shuffled frog leaping algorithm

Aiming at the multi-constraint routing problem,a mathematical model was designed,and an improved immune clonal shuffled frog leaping algorithm (IICSFLA) was proposed,which combined immune operator with traditional SFLA.Under the constraints of bandwidth,delay,packet loss rate,delay jitter and energy cost,total energy cost from the source node to the terminal node was computed.The proposed algorithm was used to find an optimal route with minimum energy cost.In the simulation,the performance of IICSFLA with adaptive genetic algorithm and adaptive ant colony optimization algorithm was compared.Experimental results show that IICSFLA solves the problem of multi-constraints QoS unicast routing optimization.The proposed algorithm avoids local optimum and effectively reduces energy loss of data on the transmission path in comparison with adaptive genetic algorithm and adaptive ant colony optimization algorithm.     

An improved distance‐based ant colony optimization routing for vehicular ad hoc networks

Vehicular ad hoc network (VANET) has earned tremendous attraction in the recent period due to its usage in a wireless intelligent transportation system. VANET is a unique form of mobile ad hoc network (MANET). Routing issues such as high mobility of nodes, frequent path breaks, the blind broadcasting of messages, and bandwidth constraints in VANET increase communication cost, frequent path failure, and overhead and decrease efficiency in routing, and shortest path in routing provides solutions to overcome all these problems. Finding the shortest path between source and destination in the VANET road scenario is a challenging task. Long path increases network overhead, communication cost, and frequent path failure and decreases routing efficiency. To increase efficiency in routing a novel, improved distance‐based ant colony optimization routing (IDBACOR) is proposed. The proposed IDBACOR determines intervehicular distance, and it is triggered by modified ant colony optimization (modified ACO). The modified ACO method is a metaheuristic approach, motivated by the natural behavior of ants. The simulation result indicates that the overall performance of our proposed scheme is better than ant colony optimization (ACO), opposition‐based ant colony optimization (OACO), and greedy routing with ant colony optimization (GRACO) in terms of throughput, average communication cost, average propagation delay, average routing overhead, and average packet delivery ratio.     

软件定义卫星光网络蚁群优化波长路由技术

针对卫星光网络中网络拓扑动态时变和业务类型多样化的问题,研究了在软件定义网络架构下保障服务质量的路由技术,提出了一种基于多业务的卫星光网络蚁群优化波长路由算法。通过改进蚁群算法的启发函数,将波长空闲率、时延、时延抖动、丢包率作为蚂蚁选路的重要依据,为业务选择了满足多种服务质量的最优路径;采用分组波长分配方法对不同等级的业务进行了区分服务,为不同业务分配了不同的波长集。仿真结果表明:与CL-ACRWA算法和Dijkstra算法相比,降低了卫星光网络的平均时延、平均时延抖动、平均丢包率,提高了波长利用率,同时也降低了高优先级业务的网络拥塞概率。     

基于蚁群优化的无线多媒体传感器网络区分服务路由

无线多媒体传感器网络中存在多种类型的数据,而且这些数据的服务质量需求并不相同。针对这种情况,提出一种基于蚁群优化的区分服务路由协议（DSACO, differentiated service and ant colony optimization based routing protocol）。DSACO在网络分层的基础上通过限制蚂蚁的搜索范围以减少建立路由的时间和能量消耗,对不同服务质量需求的数据采用区分服务路由以满足不同类型数据的服务质量需求。仿真结果表明,新协议能够为多媒体数据的传输提供更好的QoS保障,在数据传输的平均时延、分组丢失率和能量消耗上优于已有路由协议。     

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.     

Analysis,design and simulation of Internet of Things routing algorithm based on ant colony optimization

In this paper, a routing algorithm to optimize the selection of the best path for the transmitted data within the Internet of Things (IoT) system is proposed. The algorithm controls the use of ant colony ideas in the IoT system to obtain the best routing benefit. It divides the IoT environment into categorized areas depending on network types. Then, it applies the most suitable ant colony algorithm to the concerned network within each area. Furthermore, the algorithm considers routing problem in intersected areas that may arise in case of IoT system. Finally, Network Simulator 2 is used to evaluate the proposed algorithm performance. Simulation results demonstrate the effectiveness of the proposed routing algorithm in terms of end‐to‐end delay, packet loss ratio, bandwidth consumption, throughput, overhead of control bits, and energy consumption ratio. Copyright © 2016 John Wiley & Sons, Ltd.     

Solution to the problem of ant being stuck by ant colony routing algorithm

Many ant colony routing (ACR) algorithms have been presented in recent years, but few have studied the problem that ants will get stuck with probability in any terminal host when they are searching paths to route packets around a network. The problem has to be faced when designing and implementing the ACR algorithm. This article analyzes in detail the differences between the ACR and the ant colony optimization (ACO). Besides, particular restrictions on the ACR are pointed out and the three causes of ant being-stuck problem are obtained. Furthermore, this article proposes a new ant searching mechanism through dual path-checking and online routing loop removing by every intermediate node an ant visited and the destination host respectively, to solve the problem of ant being stuck and routing loop simultaneously. The result of numerical simulation is abstracted from one real network. Compared with existing two typical ACR algorithms, it shows that the proposed algorithm can settle the problem of ant being stuck and achieve more effective searching outcome for optimization path.     

Security and performance enhancement of AODV routing protocol

A mobile ad hoc networks (MANET) is a decentralized, self‐organizing, infrastructure‐less network and adaptive gathering of independent mobile nodes. Because of the unique characteristics of MANET, the major issues to develop a routing protocol in MANET are the security aspect and the network performance. In this paper, we propose a new secure protocol called Trust Ad Hoc On‐demand Distance Vector (AODV) using trust mechanism. Communication packets are only sent to the trusted neighbor nodes. Trust calculation is based on the behaviors and activities information of each node. It is divided in to trust global (TG) and trust local (TL). TG is a trust calculation based on the total of received routing packets and the total of sending routing packets. TL is a comparison between total received packets and total forwarded packets by neighbor node from specific nodes. Nodes conclude the total trust level of its neighbors by accumulating the TL and TG values. The performance of Trust AODV is evaluated under denial of service/distributed denial of service (DOS/DDOS) attack using network simulator NS‐2. It is compared with the Trust Cross Layer Secure (TCLS) protocol. Simulation results show that the Trust AODV has a better performance than TCLS protocol in terms of end‐to‐end delay, packet delivery ratio, and overhead. Next, we improve the performance of Trust AODV using ant algorithm. The proposed protocol is called Trust AODV + Ant. The implementation of ant algorithm in the proposed secure protocol is by adding an ant agent to put the positive pheromone in the node if the node is trusted. Ant agent is represented as a routing packet. The pheromone value is saved in the routing table of the node. We modified the original routing table by adding the pheromone value field. The path communication is selected based on the pheromone concentration and the shortest path. Trust AODV + Ant is compared with simple ant routing algorithm (SARA), AODV, and Trust AODV under DOS/DDOS attacks in terms of performance. Simulation results show that the packet delivery ratio and throughput of the Trust AODV increase after using ant algorithm. However, in terms of end‐to‐end delay, there is no significant improvement. Copyright © 2014 John Wiley & Sons, Ltd.     

Ad hoc网络中一种新的路由选择算法

提出了一种基于平均分组时延与分组能量消耗乘积最小的路由路径选择算法。该算法根据路径的平均分组时延和分组能量消耗情况来进行路由路径选择。仿真表明，该算法可以动态调整网络路由路径，使所选路径的平均分组时延与分组能量消耗乘积达到最小。