基于布谷鸟搜索蚁群优化的按需计算负载均衡事务调度

D. P. Mahato
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引用次数: 5

摘要

在按需计算系统中,负载均衡事务调度是一个np难题。为了解决这一问题,本文引入了一种称为布谷鸟搜索-蚁群优化的混合方法。该方法通过考虑按需计算资源的负载对其进行聚类,动态生成最优调度,并在其截止日期内完成事务的执行。该方法还可以在调度事务之前平衡系统负载。对于资源的聚类,我们使用布谷鸟搜索法。我们使用蚁群优化来选择合适和最优的资源。我们用六种现有算法来评估所提出算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Load balanced transaction scheduling in on-demand computing using cuckoo search-ant colony optimization
Load balanced transaction scheduling in on-demand computing system is known to be NP-hard problem. In order to solve this problem, this paper introduces a hybrid approach named cuckoo search-ant colony optimization. The approach dynamically generates an optimal schedule by clustering the on-demand computing resources considering their load and completes the transaction execution within their deadlines. The approach also balances the load of the system before scheduling the transactions. For clustering the resources we use cuckoo search method. We use ant colony optimization for selecting the appropriate and optimal resources. We evaluate the performance of the proposed algorithm with six existing algorithms.
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