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Efficient, proximity-aware load balancing for structured P2P systems

机译:针对结构化P2P系统的高效,感知距离的负载平衡

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Structured peer-to-peer (P2P) systems address the load balancing issue in a rather naive way, by simply resorting to the uniformity of the hash function utilized to generate object IDs. Such a random choice of object IDs could result in O(log N) load imbalance. We propose an efficient, proximity-aware load balancing algorithm for such systems. To our knowledge, this is the first work to utilize the proximity information to guide load balancing. In particular, our main contributions are: (1) A self-organized, fully distributed K-nary tree structure is constructed on top of a DHT for load balancing information collection/dissemination and load reassignment. (2) Load balancing is achieved by aligning those two skews in both load distribution and node capacity inhere in P2P systems - that is, have higher capacity nodes carry more loads. (3) Proximity information is utilized to guide load balancing such that virtual servers are assigned and transferred between physically close heavy nodes and light nodes, thereby minimizing the load transferring overhead and making load balancing fast and efficient.
机译:结构化对等(P2P)系统通过简单地求助于用于生成对象ID的哈希函数的一致性,以一种相当幼稚的方式解决了负载平衡问题。对象ID的这种随机选择可能会导致O(log N)负载不平衡。我们为此类系统提出了一种有效的,具有接近感知能力的负载平衡算法。据我们所知,这是利用邻近信息指导负载平衡的第一项工作。特别是,我们的主要贡献是:(1)在DHT之上构造了一个自组织的,完全分布式的K进制树结构,用于负载平衡信息的收集/分发和负载重新分配。 (2)在P2P系统中,通过调整负载分布和节点容量中的两个偏斜来实现负载平衡-也就是说,具有更高容量的节点将承载更多负载。 (3)利用邻近信息来指导负载均衡,以便在物理上接近的重节点和轻节点之间分配和传输虚拟服务器,从而最大程度地减少了负载传输开销,并使负载平衡快速高效。

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