Stable Load Balancing with Overlapping ID-space Management in Range-based Structured Overlay Networks

Q4 Computer Science Journal of Information Processing Pub Date : 2016-01-01 DOI:10.11185/IMT.11.1
Kimihiro Mizutani, Takeru Inoue, Toru Mano, Osamu Akashi, S. Matsuura, K. Fujikawa
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引用次数: 4

Abstract

Structured overlay networks that support range queries cannot hash data IDs for load balancing, in order to preserve the total order on the IDs. Since data and queries are not equally distributed on the ID-space without hashing in range-based overlay networks, uneven loads are imposed on the overlay nodes. Existing load balancing techniques for range-based overlay networks distribute the loads by using data reallocation or node migration, which makes the networks very unstable due to heavy data reallocation or frequent churn. This paper proposes a novel scheme that distributes, fairly, the loads without node migration and with little data reallocation, by sharing some ID-space regions between neighboring nodes. Our “overlapping” ID-space management scheme derives the optimal overlap based on kernel density estimations; the query loads based on the statistical theory are used to calculate the best overlap regions. This calculation is executed in a distributed manner with no central coordinator. We conduct thorough computer simulations, and show that our scheme alleviates the worst node load by 20–90 % against existing techniques without node migration and with least data reallocation.
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基于距离的结构化覆盖网络中具有重叠id空间管理的稳定负载均衡
支持范围查询的结构化覆盖网络不能为负载平衡散列数据id,以保持id上的总顺序。由于在基于范围的覆盖网络中,如果没有散列,数据和查询在id空间上的分布并不均匀,因此覆盖节点上的负载不均匀。现有的基于距离的覆盖网络负载均衡技术通过数据重分配或节点迁移来分配负载,这使得网络由于大量的数据重分配或频繁的数据流失而非常不稳定。本文提出了一种新的方案,通过在相邻节点之间共享一些id空间区域,在不迁移节点的情况下公平地分配负载,并且减少了数据的重新分配。我们的“重叠”id空间管理方案基于核密度估计导出最优重叠;利用基于统计理论的查询负载来计算最佳重叠区域。此计算以分布式方式执行,没有中央协调器。我们进行了全面的计算机模拟,结果表明,与现有技术相比,我们的方案在不迁移节点和减少数据重新分配的情况下,将最坏节点负载减轻了20 - 90%。
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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来源期刊
Journal of Information Processing
Journal of Information Processing Computer Science-Computer Science (all)
CiteScore
1.20
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