首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >NEW MODEL AND GENETIC ALGORITHM FOR DIVISIBLE LOAD SCHEDULING IN HETEROGENEOUS DISTRIBUTED SYSTEMS
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NEW MODEL AND GENETIC ALGORITHM FOR DIVISIBLE LOAD SCHEDULING IN HETEROGENEOUS DISTRIBUTED SYSTEMS

机译:异构分布式系统中负荷调度的新模型和遗传算法。

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摘要

The problem of divisible load scheduling in network based heterogeneous distributed systems is addressed in this paper, where a general platform is considered, and the communication is in non-blocking message receiving mode, moreover, the communication speeds, computation speeds, start-up overheads and workload size are arbitrary. To solve the problem efficiently, we set up an optimization model which can effectively tackle the following three issues: (1) how many and which processors are required in computation; (2) in which order the load fractions are distributed to processors; (3) how much the load fraction should be distributed to each processor. For this model, a novel genetic algorithm is proposed, and the convergence of the proposed algorithm to a globally optimal solution with probability one is proved. Finally, the experiments on several examples indicate the efficiency and effectiveness of the proposed algorithm.
机译:本文解决了基于网络的异构分布式系统中可分担负载调度的问题,其中考虑了通用平台,并且通信处于无阻塞消息接收模式,此外,通信速度,计算速度,启动开销和工作负载大小是任意的。为了有效地解决该问题,我们建立了一个优化模型,可以有效解决以下三个问题:(1)计算中需要多少个处理器和哪个处理器; (2)负载分数按什么顺序分配给处理器; (3)应将多少负载比例分配给每个处理器。针对该模型,提出了一种新的遗传算法,并证明了该算法与概率为1的全局最优解的收敛性。最后,在几个例子上的实验表明了该算法的有效性和有效性。

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