顺序改造方案中多服务器崩溃的随机分解

K. Sivaselvan, C. Vijayalakshmi
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摘要

网络优化技术在大型网络的框架设计和运行分析中有重要的应用。在通信和计算机网络的随机系统中,服务器崩溃受到越来越多的关注,因为它会对计算机网络的性能和功能产生明显的负面影响,如处理器故障、服务中断、工作优先级和一些外围设备骚乱因素。本文研究了N服务器的多队列网络可能随机发生多种类型的崩溃。源-目的地节点之间可能存在多条路径,这些路径指导通信负载变化、开销或响应时间。每种类型的崩溃都需要在服务变得更智能之前进行有限数量的修复。失效服务器按照前一阶段的顺序进行修复。此外,通信拥塞已成为影响网络用户服务质量的重要问题。随机分解被用来获得队列长度分布的近似。一个特定的随机模型的有用性既取决于它的计算优势,也取决于它能在多大程度上被调整来描述不同的现象。图形化表示了该方法在多服务器崩溃情况下对排队网络性能度量的改进。
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Stochastic decomposition on multi-server crash in sequential revamp scheme
Network optimization techniques have found a prime application to design the framework and operational analysis for large scale network. In the stochastic system of communication and computer network the server crash have massively more attention, for the reason that noticeably a negative impact on the performance and functionality of computer networks such as processor failure, a service disruption, job priority and some peripheral riot factor. This paper deals with multi queue network of N server may occur randomly with many types of crashes. Multiple paths may exists between the source-destination nodes that direct that traffic load variations, overhead or response time. Each types of crash require repairs a finite number of stages before the service is smarten up. Abortive servers are repair in the sequential order follows the previous stage. Moreover the traffic congestion has become a critical problem which deteriorate the Quality of Service for network users. Stochastic decomposition has employed to obtain approximations for the queue length distributions. The usefulness of a particular stochastic model depends on both its computational advantages and on the extent to which it can be adjust to describe different phenomena. Graphical representation shows that how the new method improves papers the performance measure on queueing network in multi server crash.
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