传感器网络拥塞避免与控制的模糊AQM算法

传感器网络节点通信能力有限,当数据到达速率持续超过节点转发能力时网络会发生拥塞;传感器网络是任务型网络,对不同优先级的信息具有不同的服务质量要求.针对传感器网络信息传输的上述特性,提出了一种新的拥塞避免与控制算法FAQM（Fuzzy Active Queue Management）.该算法在综合考虑数据包的随机指数标记概率和优先级权值的基础上,建立了模糊逻辑推理系统,并以数据包丢弃因子作为参量来实现数据流的智能调控.NS2仿真实验结果表明：FAQM算法能减少高优先级数据包的丢弃率和节点间链路的时延,稳定节点队列长度,在有效避免与控制拥塞网络的同时提升网络整体QoS（Quality of Service）性能.     

一种改进的蚁群WSN路由算法

针对能量控制和拥塞控制在无线传感器网络路由上的特殊要求,利用蚁群算法(Ant Colony System,ACS)对路由中最短路径加速收敛。为了促使网络节点能量消耗相对均衡,提出一种改进的蚁群路由算法。该算法将多蚁群挥发的信息素与网络节点剩余能量结合成算法控制因子,并且引入了多蚁群竞争机制来避免单一收敛。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较优权衡。最后通过Matlab仿真实验验证了该方法的可行性,并给出实验结果。     

基于动态获知节点状态的间断连接网络拥塞控制机制

间断连接网络中通常是利用多副本数据转发方式来提高数据成功投递概率;但多副本的数据转发易导致冗余数据副本出现的频率升高。对此,设计了动态获知节点状态的间断连接网络拥塞控制机制(SCCS,State-aware Congestion Control Strategy)。引入平滑数学模型,结合节点间的相遇历史信息,构造了效用函数,从而以间接获知网络信息的方式预测下一时刻网络的拥塞情况,进而以分布式的方式动态选择较为合适的中继节点,以更加合理地利用有限的网络资源。仿真结果表明:与当前性能较好的拥塞控制机制相比,该机制的数据成功投递概率更高,而网络负载率更低。     

基于蚁群算法的无线传感器网络数据聚合路由算法

传感器网络为减少冗余数据的传输耗能。降低延迟,需要在路由过程中采用数据聚合技术。文中采用定向传输方式,在消息路由机制基础上提出了一种基于蚁群算法的数据聚合路由算法。该算法主要思想在于将节点能耗、传输距离与聚合收益3方面作为启发因子,通过一组称为“蚂蚁”的人工代理寻找到达汇聚节点的最优路径。该算法利用蚁群算法的正反馈效应来达到数据汇集的目的,不需要网络节点维护全局信息,因此是一种实现数据聚合在能量与时延上折中的分布式路由算法。理论分析和仿真结果说明了新算法的有效性。     

Hadoop平台下一种改进蚂蚁算法的QoS路由研究

随着未来云计算的发展,各种云服务的应用将需要更高的网络性能。链路拥塞导致的数据包传输时延或数据包丢弃使得网络无法保障业务的QoS。目前普遍使用的链路状态路由算法不具有拥塞响应机制。本文通过在拥塞节点间发送连接蚂蚁寻找新路由来解决拥塞问题。NS2仿真结果表明,该算法能加快新的路由搜索,满足QoS的需求,并有效控制丢包率,时延等性能。     

一种基于跨层设计和蚁群优化的自组网负载均衡路由协议

针对大部分现有替代路径共同存在的替代路径老化和构建效率问题,本文提出了一种基于跨层设计和蚁群优化的负载均衡路由协议(CALRA),利用蚁群优化算法特有的信息素挥发方法实现对替代路径的老化问题,将蚁群优化和跨层优化方法结合起来解决自组网中的负载均衡问题,通过双向逐跳更新的方式较好的解决了替代路径构建效率问题,并将蚂蚁在所经过的各中间节点为路由表带来的信息素增量映射为蚂蚁离开源节点的距离、移动过程中所遇到的节点拥塞程度、节点当前信息素浓度和节点移动速度等各协议层的统计信息的函数,通过对各种信息所对应的参数赋予不同加权值的方法对概率路由表进行控制,改善了自组网中现有基于蚁群优化的路由协议中普遍存在的拥塞问题、捷径问题、收敛速度问题和引入的路由开销问题.仿真表明,CALRA在分组成功递交率、路由开销、端到端平均时延等方面具有优良性能,能很好地实现网络中的业务负载均衡.     

帧中继网络的一种拥塞控制机制

本文介绍一帧中继网络的拥塞控制机制－输入速率控制机制。它采用漏桶算法调节从源节点到网络节点的数据流量。本文着重介绍了该输入速度控制机制的实现并作了性能分析。依据帧中继子网的拓扩结构，进行理论分析和计算机模拟，给出了不同参数下的各项性能曲线。     

基于GA-ACO-BP的WSN数据融合算法实现

在无线传感网络中,为了提高多传感器数据融合性能,解决传感器电池频繁更换,延长网络生命周期,提出一种将遗传算法与蚁群算法相结合改进BP神经网络的多传感器数据融合算法(GA-ACO-BP)。GA-ACO-BP算法结合了遗传算法和蚁群算法的优势,传感器网络节点将信息通过LEACH协议对数据进行融合处理,降低数据发往Sink节点的传输量,减少数据传输造成的能量消耗。通过实验仿真显示,GA-ACO-BP算法和基于LEACH协议的算法、ACO-BP算法相比,该算法能减少需要传输的数据量,延长网络生存周期。     

节点状态感知的延迟容忍网络拥塞控制策略

为了有效提高延迟容忍网络中的数据传输效率,节点普遍采用多副本方式转发数据,然而此种方式将造成网络中冗余数据增多,导致网络拥塞.本文提出了一种带有节点状态感知的拥塞控制策略,根据运动过程中所获知的相关历史信息,节点以直接获取及间接推荐的方式准确地感知网络中各个节点的拥塞状态,进而以分布式的方式动态地为数据选择中继节点,达到更加合理地利用有限的网络资源的目的.结果表明所提出的拥塞控制能有效地改善数据成功投递概率和网络负载率.     

城市车载网络中的消息安全传输机制

针对城市车载网络中因自私节点及恶意节点存在造成的消息成功传输率低下的问题,提出一种消息安全传输机制。在城市环境下,用TPM芯片标识车辆。综合节点间成功转发消息及接触次数,得出好感值,并融入对车辆节点的移动方向及速度的考虑,得出节点的效用值,以此衡量节点间的信任程度,找出适当的下一跳车辆节点,保证消息的安全传输。同时,利用两次握手协议来确保节点间的连通性,减少网络中断问题,增加消息的成功传输率。此外,引入图论的概念,构造城市车载网络中的无向加权图,利用Floyd算法求出消息的最短传输路径,减少网络开销。仿真结果表明,该种机制下的消息成功传输率达到90%以上,且网络开销性能值低于200。     

Path planning algorithm for WCE with joint energy replenishment and data collection based on multi-objective optimization

Considering limited energy of the wireless charging equipment (WCE) in wireless rechargeable sensor network,an energy replenishment strategy and a data collection strategy are designed.On the basis of these,a path planning model for WCE with functions of joint energy replenishment and data collection based on multi-objective optimization is constructed with two optimization objectives,maximizing the total energy utility of WCE and minimizing the average delay of data transmission of all the sensor nodes in the network.To deal with it,a multi-objective ant colony optimization algorithm based on elitist strategy was proposed,where the state transition strategy and the pheromone updating strategy were improved.Then,the Pareto set was obtained in terms of this multi-objective optimization problem.The parameter setting of ant colony algorithm’s effects on the proposed algorithm were analyzed under 20 sensor nodes.50 groups of contrastive experiments show that the average number of energy utilization obtained by ES-MOAC algorithm is 4.53% higher than that of NSGA-II algorithm.The average number of average delay of all node data transmission obtained by ES-MOAC algorithm is 5.12% lower than that of NSGA-II algorithm.     

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.     

蚁群-遗传算法的无线传感器网络路径优化

为了提高无线传感器网络路径优化效率,快速找到最优路径,提出基于蚁群-遗传算法的传感器路径优化方法.利用遗传算法的快速全局搜索能力和蚁群算法的正反馈机制,实现了两种算法的融合.仿真结果表明,蚁群-遗传算法在时间和性能上都优于单独的蚁群算法和遗传算法,能快速找到无线传感器网络最优路径,有效延长了网络的生命周期.     

GCTA:一种群组命令传输算法

基于尽力而为服务模式的Internet,在支持群组命令传输过程中,容易产生路径竞争问题.定义出有效路径统计网络,并进一步定义出基于有效路径统计网络的群组多约束多目标优化问题.提出一种群组命令传输算法.该算法,分别定义出模糊球体划分、连续空间蚁群搜索及重叠区域解可信度衰减策略.实验从服务延迟率和传输成功率两个方面,验证了该算法在支持群组命令传输过程的有效性.     

一种基于蚁群优化的分簇路由算法

在无线传感器网络路由协议的研究中,能量高效是其首要设计目标.传统LEACH协议产生簇头数目比较随机,并且簇头直接与基站通信导致能量消耗过快.在分析传统和改进LEACH路由协议的基础上,提出了一种簇头数目固定的簇头选择机制,解决了簇头分布不均匀的问题.并且将蚁群优化算法应用到无线传感器网络的路径选择中,利用蚁群的动态适应性和寻优能力,在簇头与基站之间形成一条最优路径进行通信.在Matlab平台下对新提出的算法进行仿真测试实验,实验结果表明,相对于LEACH路由协议,该算法降低了平均能量消耗,延长了网络的生命周期.     

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。     

蚁群优化和能量有效的Ad Hoc路由协议

为了延长Ad Hoc网络的生存周期,提出了一种基于蚁群优化和能量有效的Ad Hoc网络多路径动态路由算法ACOERA。该算法根据路径的有效能量率进行路由选择,路径建立后通过蚁群优化算法动态收集路径信息,并对路由表进行更新。仿真结果表明,该算法能有效延长网络生存时间,增强通信网络的自适应能力。     

Discovering the backbone network with a novel designed ant colony algorithm

Forthe problem that in interactive network,the illegal and abnormal behaviors were becoming more hidden,moreover,the complex relation in real interactive network heightens the difficulty of detecting anomalous entities,an ant colony model was proposed for extracting the backbone network from the complex interactive network.The novel model simulated the relationships among entities based on the theory of path optimization,reduced the network size after quantifying the significance of each flow of information.Firstly,a strategy of initial location selection was proposed taking advantage of network centrality.Secondly,a novel path transfer mechanism was devised for the ant colony to fit the flow behavior of entities.Finally,an adaptive and dynamic pheromone update mechanism was designed for guiding the optimization of information flows.The experimental results show that the proposed model is superior to the traditional ant colony algorithm in both solving quality and solving performance,and has better coverage and accuracy than the greedy algorithm.     

Energy and delay efficient dynamic cluster formation using hybrid AGA with FACO in EAACK MANETs

MANET is a set of mobile nodes which works in a dynamic changing network and it is capable of communicating with each other efficiently where all the nodes perform a dual role as that of a transmitter and a receiver. MANETs do not use any centralized administration for communication. The performance of a MANET can be further enhanced by adapting a cluster mechanism with the help of CEAACK to provide security from penetrators. In this paper we propose a new improved ant colony optimization algorithm with two strategies to reduce the overhead in communication by predicting mobility of node and cluster formation. Firstly, a dynamic mechanism is designed for determining one or more heuristic parameters for improving the performance of the MANET. Secondly a dynamic list of nodes are maintained which helps in forming clusters and electing the cluster head faster. In addition a dynamic broadcast approach algorithm is incorporated to provide the information about the status of the nodes to the hybrid fuzzy-ant colony algorithm. This approach ensures low maintenance cost and is expected to be robust against node failures and network topology changes. The positive outcome of these two techniques consumes low energy and in the process provides better efficiency in data transmission in MANETs. It also achieves correct delivery of packets without unnecessary delay.