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A proximity-aware load balancing in peer-to-peer-based volunteer computing systems

机译:基于对等的志愿者计算系统中的接近感知负载平衡

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摘要

One of the main challenges in peer-to-peer-based volunteer computing systems is an efficient resource discovery algorithm. Load balancing is a part of resource discovery algorithm and aims to minimize the overall response time of the system. This paper introduces an analytical model based on distributed parallel queues to optimize the average response time of the system in a distributed manner. The proposed resource discovery algorithm consists of two phases. In the first phase, it selects peers in a load-balanced manner based on QoS constraints of request. In the second phase, a proximity-aware feature is applied to select the peer with minimum communication overhead among selected peers in the first phase. Two dispatching strategies are proposed for the load balancing based on stochastic analysis of routing in the distributed parallel queues. These policies adopt probabilistic and deterministic sequences to redirect requests to the capable peers in the system. Simulation results show that the proposed resource discovery algorithm improves the response time of user's requests by a factor of 1.8 under a moderate load.
机译:基于对等的志愿者计算系统的主要挑战之一是有效的资源发现算法。负载平衡是资源发现算法的一部分,旨在最大程度地减少系统的总体响应时间。本文介绍了一种基于分布式并行队列的分析模型,以分布式方式优化系统的平均响应时间。所提出的资源发现算法包括两个阶段。在第一阶段,它基于请求的QoS约束以负载平衡的方式选择对等体。在第二阶段中,应用接近感知功能来选择第一阶段中选定对等方之间的通信开销最小的对等方。基于对分布式并行队列中路由的随机分析,提出了两种用于负载均衡的调度策略。这些策略采用概率和确定性序列将请求重定向到系统中有能力的对等方。仿真结果表明,该算法在中等负载下将用户请求的响应时间提高了1.8倍。

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