Peer-to-peer distributed computing framework

Prashan Dharmapala, Lumeshkantha Koneshvaran, Darshanun Sivasooriyathevan, I. Ismail, D. Kasthurirathna
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引用次数: 2

Abstract

Public-Resource Computing (PRC) is an innovative approach to high performance computing that depends on volunteers who contribute their personal computers, where underutilized computing resources are collected and used for computationally intensive research projects. Existing systems basically operate on centralized clusters of nodes to achieve high performance. However, these centralized clusters of nodes can be unrealistic for users who infrequently have a demand of solving large distributed problems. Therefore, large-scale computation time-sharing systems need a decentralized architecture. Peer-to-peer systems are modelled around the assumption that all peers willingly contribute resources to a global pool. This dissertation presents design requirements of sharing the workload among many computational nodes, peer management, and most importantly peer failure management for improving fault tolerance. It represents a Java based peer-to-peer distributed computing framework that allows cross-platform support.
点对点分布式计算框架
公共资源计算(PRC)是一种创新的高性能计算方法,它依赖于志愿者贡献他们的个人计算机,其中未充分利用的计算资源被收集并用于计算密集型研究项目。现有的系统基本上是在集中的节点集群上运行,以实现高性能。然而,对于不经常需要解决大型分布式问题的用户来说,这些集中的节点集群可能是不现实的。因此,大规模计算分时系统需要一个去中心化的架构。点对点系统是围绕这样一个假设建模的,即所有的节点都愿意为一个全球池贡献资源。本文提出了在多个计算节点之间分担工作负载、对等管理以及最重要的对等故障管理以提高容错性的设计要求。它代表了一个基于Java的点对点分布式计算框架,允许跨平台支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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