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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >On the Design of Adaptive and Decentralized Load Balancing Algorithms with Load Estimation for Computational Grid Environments
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On the Design of Adaptive and Decentralized Load Balancing Algorithms with Load Estimation for Computational Grid Environments

机译：计算网格环境下基于负载估计的自适应分散负载均衡算法设计

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摘要

In this paper, we address several issues that are imperative to Grid environments such as, handling resource heterogeneity and sharing, communication latency, job migration from one site to other, and load balancing.We address these issues by proposing two job migration algorithms, which are MELISA (Modified ELISA) and LBA (Load Balancing on Arrival). The algorithms differ in the way load balancing is carried out and is shown to be efficient in minimizing the response time on large and small scale heterogeneous Grid environments, respectively. MELISA, applicable to large scale systems (i.e., interGrid [1]), is a modified version of ELISA [2] in which we consider job migration cost, resource heterogeneity and network heterogeneity when load balancing is considered. LBA algorithm, applicable for small scale systems (i.e., intraGrid [1]), performs load balancing by estimating expected finish time of job on buddy processors on each job arrival. Both algorithms estimate system parameters such as job arrival rate, CPU processing rate, load at processor and balance the load by migrating jobs to buddy processors by taking into account job transfer cost, resource heterogeneity and network heterogeneity. We quantify the performance of our algorithms using several influencing parameters such as, job size, data transfer rate, status exchange period, migration limit, and we discuss the implications of the performance and choice of our approaches.
机译：在本文中，我们解决了网格环境中必不可少的一些问题，例如处理资源异构和共享，通信延迟，从一个站点到另一个站点的作业迁移以及负载平衡。我们通过提出两种作业迁移算法来解决这些问题。是MELISA（改良ELISA）和LBA（到达时负载平衡）。这些算法的不同之处在于执行负载平衡的方式，并分别显示出在最小化大型和小型异构网格环境中的响应时间方面的效率。适用于大规模系统（即interGrid [1]）的MELISA是ELISA [2]的改进版本，在考虑负载平衡时，我们考虑了工作迁移成本，资源异质性和网络异质性。适用于小型系统（即intraGrid [1]）的LBA算法通过估算每次作业到达时伙伴处理器上作业的预期完成时间来执行负载平衡。两种算法都估计系统参数，例如作业到达率，CPU处理速率，处理器负载，并通过考虑作业转移成本，资源异构性和网络异构性，通过将作业迁移到伙伴处理器来平衡负载。我们使用几个影响参数来量化算法的性能，这些参数包括作业大小，数据传输速率，状态交换周期，迁移限制，并讨论了性能的影响和方法的选择。

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