基于MAODV协议的多路径扩展方法

提出了一种基于MAODV协议的多路径扩展方法,选择两条节点不相交的路径分流发送数据分组以提高网络利用率,均衡网络负载;只有当两条路径都中断,源节点才重新进行路由寻找,从而减少路由寻找次数,降低了路由控制开销.仿真表明,随着网络负载增加,多路径MAODV较好的保证了网络多方面的性能.     

Ad Hoc网络中AOMDV协议的一种改进方案

多路径路由协议是Ad Hoc网络最重要的协议之一,通过它可以获得多条通信路径,并且能够减少路由发现延迟,实现负载均衡,因此受到广泛应用.该文介绍了AOMDV多路径路由协议的工作过程和特点,分析了其在减少延迟和均衡负载中的作用.在此基础上提出了一种对AOMDV路由表结构的改进方案,理论和模拟表明该方案能显著提高网络传输性能.     

一种粒子群优化的多路径路由负载均衡算法

多路径路由的一个重要问题是如何有效地均衡网络负载.针对丢包率比较敏感的应用需求,本文利用最优化理论研究了在多路径环境下的负载均衡问题.均衡算法首先利用路径QoS指标预测每条路径的丢包率,然后将多路径负载均衡问题转化为最优化问题,在此基础上,利用粒子群优化算(particle swarm optimization algorithm,PSO)动态求解调整每个路径的转发比例,并分析了影响转发比例的因素.通过理论分析及仿真实验表明,该算法能有效地降低网络丢包率,提高网络性能.     

关键路径优先WSNs负载均衡多路数据传输协议

由于无线传感器网络中节点能量有限,如何实现各节点负载均衡以延长网络生存周期是亟待解决的问题.利用关键路径优先原则提出一种多路径数据传输协议,快速选择适合路径并剔除不适合数据传输的路径,并用剩余能量均衡法为各传送路径分配数据,以有效均衡各节点能量,延长网络生存周期.仿真实验表明:算法显著延长了网络寿命,与其他多路径传输算法相比网络寿命延长超过37%.     

基于负载均衡的战场自组织网络多径路由研究

移动Ad hoc网络中的多路径路由协议能够减小路由发现延迟,提高网络生存时间,受到了人们的广泛关注.详细分析了AOMDV多路径路由协议的机制和特点,针对多径路由协议在负载均衡时采用的随机转发策略,提出了一种改进的基于AOMDV协议的负载均衡传输方案,该方案能够避免TCP在多径传输时的乱序.仿真结果表明,在不影响UDP性能的情况下,该方法能显著改善TCP的传输性能.     

基于流量分配倾向度的SDN多路径负载均衡

针对SDN多路径网络环境下的负载均衡问题,提出一种基于流量分配倾向度(flow distribution propensity,FDP)的SDN多路径路由负载均衡策略。在SDN多路径网络中,每当有数据流需要传输时,通过深度优先遍历算法(DFS)获取并存储多路径信息及每条路径的带宽与时延参数;依据文中定义的流量分配倾向度,结合OpenFlow组表技术,公平地分配网络流量到每条可用路径。仿真结果表明,该策略可有效增加所有可用路径的数据包传输量,降低SDN网络中单一路径的负载,实现了基于多路径路由的负载均衡。     

能量感知的无线传感器网络多路径路由研究

针对现有多路径路由协议AOMDV的不足,提出了适用于无线传感器网络的能量感知多路径路由协议IMEA.IMEA在建立链路不相关的多路径时能优先建立节点不相关的多路径,在主路径失效时能优先选择与主路径共用节点最少的作为次优路径,而能量感知的路径选择策略能均衡网络中节点的能量消耗,实现数据传输路径的低能耗.对IMEA进行了仿真实验,结果表明IMEA有效延长了网络的生存时间.     

基于蚁群算法的能量均衡多路径路由算法的研究

本文对现有的基于蚁群算法的路由协议进行了深入的研究,并提出了一种基于蚁群算法的能量均衡多路径路由算法（ABMR）,该算法在蚂蚁数据包结构、信息素更新公式、信息素更新方式和多路径建立机制等方面作了改进。在信息素更新公式中综合考虑了路径的能量消耗速度、路径上剩余的最小能量、距离目的节点Sink的跳数和路径的拥塞程度。在信息素更新方式上,改变传统的信息素的累加更新方式,采用彻底的链路信息素更新方式,使网络负载更加均衡。ABMR的多路径生成机制可以在源节点和目的节点间更加合理的建立起多条路径。数据发送阶段,概率路由选择策略使数据流量均衡的注入无线传感器网络。本文在NS-2仿真环境下对ABMR协议进行仿真实验,仿真结果表明,和传统协议比较, ABMR协议在能量有效性、数据分组投递率以及分组端到端时延等方面都有一定的提高。     

一种适用于移动自组网的多径多信道负载均衡路由协议

为了降低邻居节点之间的信道冲突,提高移动自组网网络性能和服务质量,提出一种跨层设计的多径多信道负载均衡路由协议CMM_LB.协议可以发现多条完全不相交路由,路径上的节点可在路由建立之后分布式的自主选择信道,减少与邻居节点的信道冲突.源节点通过探测机制,以信道可用带宽和节点接口队列长度作为负载轻重的依据,收集链路负载信息,在多条路径间动态调整负载分配比,实现多路径间最大程度上的负载均衡.仿真结果表明,与改进前的CMMRP和AODV相比,CMM_LB在网络吞吐量、平均端到端时延等方面有明显的性能提升.     

基于距离成本能量有效的传感器网络路由协议

负载均衡和路径恢复给数据分发的大规模传感器网络带来了挑战。这些问题可以通过多路径和故障恢复路由能够部分得到解决。不幸的是现存的协议还不能满足大规模传感器网络的需求。文中提出了一种新的路由算法，DCEP。它通过计算节点间距离来建立传输路径。此协议不需要节点的位置信息。仿真表明此协议与DD、GPSR协议相比具有优异的表现。     

A dual-direction technique for fast file downloads with dynamic load balancing in the Cloud

File downloads make up a large percentage of the Internet traffic to satisfy various clients using distributed environments for their Cloud, Grid and Internet applications. In particular, the Cloud has become a popular data storage provider and users (individuals and corporates) are relying heavily on it to keep their data. Furthermore, most cloud data servers replicate their data storage infrastructures and servers at various sites to meet the overall high demands of their clients and increase availability. However, most of them do not use that replication to enhance the download performance per client. To make use of this redundancy and to enhance the download speed, we introduce a fast and efficient concurrent technique for downloading large files from replicated Cloud data servers and traditional FTP servers as well. The technique, DDFTP utilizes the availability of replicated files on distributed servers to enhance file download times through concurrent downloads of file blocks from opposite directions in the files. DDFTP does not require coordination between the servers and relies on the in-order and reliability features of TCP to provide fast file downloads. In addition, DDFTP offers efficient load balancing among multiple heterogeneous data servers with minimal overhead. As a result, we can maximize network utilization while maintaining efficient load balancing on dynamic environments where resources, current loads and operational properties vary dynamically. We implemented and evaluated DDFTP and experimentally demonstrated considerable performance gains for file downloads compared to other concurrent/parallel file/data download models.     

基于流量预测的无线mesh网络负载均衡路由协议

提出了一种基于神经网络预测模型的无线mesh网络负载均衡协议NNP-L2MPM。协议根据网络中泛洪的HELLO包计算路径质量,从而选择出到达目的节点的最优下一跳,并以MAC层接口队列长度作为流量负载的衡量依据,然后利用RBF神经网络预测模型对mesh网路中的节点流量负载进行预测,根据预测的下一时刻的流量负载优化路径质量,提前实现路由更新,避免中间节点发生拥塞,进而提高网络性能。仿真结果表明:与原有路由协议相比,所提协议在数据包投递率上提高了约9%,平均端到端延时降低了约16%。     

A paracasting model for concurrent access to replicated Internet content

In this paper, we develop a model to study how to effectively download a document from a set of replicated servers. We propose a generalized application-layer anycasting protocol, known as paracasting, to advocate concurrent access of a subset of replicated servers to cooperatively satisfy a client's request. Each participating server satisfies the request in part by transmitting a subset of the requested file to the client. The client can recover the complete file when different parts of the file sent from the participating servers are received. This model allows us to estimate the average time to download a file from the set of homogeneous replicated servers, and the request blocking probability when each server can accept and serve a finite number of concurrent requests. Our results show that the file download time drops when a request is served concurrently by a larger number of homogeneous replicated servers, although the performance improvement quickly saturates when the number of servers increases. If the total number of requests that a server can handle simultaneously is finite, the request blocking probability increases with the number of replicated servers used to serve a request concurrently. Therefore, paracasting is effective when a small number of servers, say, up to four, are used to serve a request concurrently.     

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。     

HPC Cloud环境中基于网络Ⅰ/O负载的虚拟机放置算法

随着虚拟化技术和云计算技术的发展,越来越多的高性能计算应用运行在云计算资源上.在基于虚拟化技术的高性能计算云系统中,高性能计算应用运行在多个虚拟机之中,这些虚拟机可能放置在不同的物理节点上.若多个通信密集型作业的虚拟机放置在相同的物理节点上,虚拟机之间将竞争物理节点的网络Ⅰ/O资源,如果虚拟机对网络Ⅰ/O资源的需求超过物理节点的网络Ⅰ/O带宽上限,将严重影响通信密集型作业的计算性能.针对虚拟机对网络Ⅰ/O资源的竞争问题,提出一种基于网络Ⅰ/O负载均衡的虚拟机放置算法NLPA,该算法采用网络Ⅰ/O负载均衡策略来减少虚拟机对网络Ⅰ/O资源的竞争.实验表明,与贪心算法进行比较,对于同样的高性能计算作业测试集,NLPA算法在完成作业的计算时间、系统中的网络Ⅰ/O负载吞吐率、网络Ⅰ/O负载均衡3个方面均有更好的表现.     

一种多信道Ad Hoc网络的多径负载均衡路由协议

针对移动Ad Hoc网络固有的路由耦合问题,提出了一种基于OLSR的多信道多径负载均衡路由协议MMRP_LB.MMRP_LB将信道的可用带宽作为衡量节点负载轻重的依据,在建立路由时,同时考虑路径的负载和跳数,通过运行多重改进的Dijska算法,得到多条节点不相交的最优路径;依次给每条路径分配一个信道,并按照加权轮询方式分配业务.仿真结果显示,与单信道下的协议相比,MMRP_LB在网络吞吐量、平均端到端时延等方面具有良好的性能,有效地避免了路由耦合.     

A dynamic and adaptive load balancing strategy for parallel file system with large-scale I/O servers

Many solutions have been proposed to tackle the load imbalance issue of parallel file systems. However, all these solutions either adopt centralized algorithms, or lack considerations for both the network transmission and the tradeoff between benefits and side-effects of each dynamic file migration. Therefore, existing solutions will be prohibitively inefficient in large-scale parallel file systems. To address this problem, this paper presents SALB, a dynamic and adaptive load balancing algorithm which is totally based on a distributed architecture. To be also aware of the network transmission, SALB on the one hand adopts an adaptively adjusted load collection threshold in order to reduce the message exchanges for load collection, and on the other hand it employs an on-line load prediction model with a view to reducing the decision delay caused by the network transmission latency. Moreover, SALB employs an optimization model for selecting the migration candidates so as to balance the benefits and the side-effects of each dynamic file migration. Extensive experiments are conducted to prove the effectiveness of SALB. The results show that SALB achieves an optimal performance not only on the mean response time but also on the resource utilization among the schemes for comparison. The simulation results also indicate that SALB is able to deliver high scalability.     

Elastic Routing Table with Provable Performance for Congestion Control in DHT Networks

Consistent hashing-based DHT networks have an inherent load balancing problem. The problem becomes more severe in heterogeneous networks with nonuniform and time-varying popular files. Existing DHT load balancing algorithms are mainly focused on the issues caused by node heterogeneity. To deal with skewed lookups, this paper presents an elastic routing table (ERT) mechanism for query load balancing, based on the observation that high-degree nodes tend to receive more traffic load. The mechanism allows each node to have a routing table of variable size corresponding to node capacities. The indegree and outdegree of the routing table can also be adjusted dynamically in response to the change of file popularity and network churn. Theoretical analysis proves that the routing table degree is bounded. The ERT mechanism facilitates locality-aware randomized query forwarding to further improve lookup efficiency. By relating query forwarding to a supermarket customer service model, we prove that a two-way randomized query forwarding policy should lead to an exponential improvement in query processing time over random walking. Simulation results demonstrate the effectiveness of the ERT mechanism and its related query forwarding policy for congestion and query load balancing. In comparison with existing "virtual-server”-based load balancing algorithms and other routing table control approaches, the ERT-based congestion control protocol yields significant improvement in query lookup efficiency.     

Efficient task migration algorithm for distributed systems

The objective of the study was to achieve balanced load among processors, reduce the communication overhead of the load balancing algorithm, and improve respource utilization, which results in better average resonse time. A communication protocol and a fully distributed algorithm for dynamic load balancing through task migration in a connected N-processor network are presented. Each processor communicates its load directly with only a subset (of the size √ N) of processors, reducing communication traffic and average response time. It is proved that the given algorithm will perform task migration even if there is only one light load processor and one heavy load processor in the system. Simulation results show that the proposed scheme can save up to 60% of the protocol messages used by the broadcast algorithms and can reduce the average response time     

Ad Hoc网络中基于负载均衡的多径路由协议研究

Ad Hoc网络中的多径路由协议可以获得源节点和目的节点之间的多条路径,能够减小路由发现延迟,提高路由稳定性,受到了人们的广泛关注。详细分析了AOMDV多径路由协议的机制和特点,从负载均衡的角度仿真评估了AOMDV协议的性能,研究表明可以显著提高网络整体生存性。在此基础上提出了一种优化的负载均衡传输方案,能够减小TCP在多径传输时的乱序问题,仿真表明显著改善了TCP传输的吞吐量。