Mobile Agent: Linux环境下负载均衡的进程迁移

M. Nimbalkar, Ganesh R. Pathak, Hema Nagargoje
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引用次数: 0

摘要

这是在分布式环境中执行进程时获得更好性能的一种尝试,它允许执行环境在进程生命周期的任何时刻动态地将进程从一个处理器移动到另一个处理器。本文提出了一种以CPU负载为迁移标准,将进程动态迁移到轻负载主机的迁移算法。在迁移过程中,该算法负责识别活动节点并将进程迁移到负载较轻的工作站。集中式服务器维护NOW中各节点的状态和负载。代理独立运行,完全负责根据主机负载决定是否需要迁移进程。代理节点将负责跟踪负载,如果超过定义的阈值,将做出迁移流程的决定。在确定的情况下,它标识轻负载主机,并将进程的状态传输到目标主机。在目标主机上,收集状态,进程恢复执行,并将结果发送回发起迁移进程请求的源机器。通过在整个生命周期内动态移动流程,系统可以更好地适应在任务开始时无法预见的负载变化。进程迁移的支持者声称,与静态进程调度相比,这种动态适应可以更好地利用系统范围内的可用资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mobile Agent: Load Balanced Process Migration in Linux Environments
This is an attempt to gain better performance in executing the processes in distributed environments, which allows execution environments to move processes from processor to processor dynamically at any point in the life of the process. In this paper, a migration algorithm is proposed to migrate the processes dynamically to lightly loaded host using the CPU load as migration criteria. During the migration, the algorithm takes care of identifying the live nodes and migrate the process to lightly loaded workstation. The centralized server maintains the status and load of each node in the NOW. Agents are running independently and are solely responsible for deciding if process need to be migrated or not based on the load of hosts. Agent node will be responsible for keeping track of load and if exceeds the defined threshold, decision will be made to migrate the process. In a case decided, it identifies the lightly loaded host and transfers state of the process to the target hosts. On the target hosts, the state is collected and the process resumes the execution and sends the result back to the source machine which initiated the request to migrate the process. By dynamically moving processes throughout their lifetimes, the system can potentially adapt better to changes in the load that could not be foreseen at the start of the tasks. Proponents of process migration claim that this dynamic adaptation leads to a better system-wide utilization of available resources than static process scheduling.
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