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A heuristic-genetic algorithm for client web service scheduling constrained by one I/O port

机译:受一个I / O端口约束的启发式遗传算法用于客户端Web服务调度

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Enhancing heterogeneous distributed computing systems requires effective scheduling approach to achieve high performance and satisfy the clients request. Many scheduling algorithms have been proposed to map and order clients requests running on a suitable processor at the minimum makespan and maximum resource utilization. However, they do not take into account the task scheduling under bounded number of I/O port constraint which is a realistic communications model between client and server. Based on the I/O port constraint, this paper proposes a one I/O port task scheduling using a hybrid heuristicgenetic algorithm to achieve minimum completion time. For practical scenario, web service workflow represented by the Directed Acyclic Graph (DAG) of tasks is implemented as an input task set. The proposed algorithm focuses on sending the clients request of web services and receiving results having minimum makespan and delay. Unlike Genetic Algorithm (GA) providing near optimal results but high time complexity, the proposed approach named Critical Path with Genetic Algorithm (CPGA) incorporates GA to produce the good quality schedule with lower processing time. Preliminary result of fair comparisons with existing scheduling methods shows that the proposed approach outperforms them in terms of minimum makespan and delay.
机译:增强异构分布式计算系统需要有效的调度方法来实现高性能并满足客户的要求。已经提出了许多调度算法,以最小的制造时间和最大的资源利用率来映射和排序在合适的处理器上运行的客户端请求。但是,它们没有考虑在有限的I / O端口约束下的任务调度,这是客户端和服务器之间的一种实际通信模型。基于I / O端口约束,本文提出了一种基于混合启发式遗传算法的I / O端口任务调度算法,以实现最小的完成时间。对于实际情况,将由任务的有向无环图(DAG)表示的Web服务工作流实现为输入任务集。所提出的算法着重于发送客户对Web服务的请求以及接收具有最小有效期和延迟的结果。与提供接近最佳结果但时间复杂度高的遗传算法(GA)不同,所提出的名为遗传算法的关键路径(CPGA)的方法结合了遗传算法以产生高质量的进度表,并缩短处理时间。与现有调度方法进行公平比较的初步结果表明,所提出的方法在最小有效期和延迟方面优于它们。

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