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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Efficient, proximity-aware load balancing for DHT-based P2P systems
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Efficient, proximity-aware load balancing for DHT-based P2P systems

机译：基于DHT的P2P系统的高效，近距离感知负载平衡

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Many solutions have been proposed to tackle the load balancing issue in DHT-based P2P systems. However, all these solutions either ignore the heterogeneity nature of the system, or reassign loads among nodes without considering proximity relationships, or both. In this paper, we present an efficient, proximity-aware load balancing scheme by using the concept of virtual servers. To the best of our knowledge, this is the first work to use proximity information in load balancing. In particular, our main contributions are: 1) relying on a self-organized, fully distributed k-ary tree structure constructed on top of a DHT, load balance is achieved by aligning those two skews in load distribution and node capacity inherent in P2P systems - that is, have higher capacity nodes carry more loads; 2) proximity information is used to guide virtual server reassignments such that virtual servers are reassigned and transferred between physically close heavily loaded nodes and lightly loaded nodes, thereby minimizing the load movement cost and allowing load balancing to perform efficiently; and 3) our simulations show that our proximity-aware load balancing scheme reduces the load movement cost by 11-65 percent for all the combinations of two representative network topologies, two node capacity profiles, and two load distributions of virtual servers. Moreover, we achieve virtual server reassignments in O(log N) time.
机译：已经提出了许多解决方案来解决基于DHT的P2P系统中的负载平衡问题。但是，所有这些解决方案要么忽略系统的异质性，要么在不考虑邻近关系的情况下在节点之间重新分配负载，或者两者兼而有之。在本文中，我们通过使用虚拟服务器的概念提出了一种有效的，可感知邻近的负载平衡方案。据我们所知，这是在负载平衡中使用邻近信息的第一项工作。特别是，我们的主要贡献是：1）依靠在DHT之上构建的自组织，完全分布的Kary树结构，通过对齐P2P系统固有的负载分布和节点容量的这两个偏差来实现负载平衡。 -即，具有更高容量的节点承载更多负载； 2）邻近性信息用于指导虚拟服务器的重新分配，以便在物理上紧密的重负载节点和轻负载节点之间重新分配和传输虚拟服务器，从而最大程度地减少了负载移动成本并允许负载平衡有效地执行； 3）仿真结果表明，对于两种代表性网络拓扑，两个节点容量配置文件和两个虚拟服务器负载分布的所有组合，我们的接近感知负载平衡方案将负载移动成本降低了11-65％。此外，我们在O（log N）时间内实现了虚拟服务器的重新分配。

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