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|Title:||Histogram-based global load balancing in structured peer-to-peer systems|
|Source:||Vu, Q.H., Ooi, B.C., Rinard, M., Tan, K.-L. (2009). Histogram-based global load balancing in structured peer-to-peer systems. IEEE Transactions on Knowledge and Data Engineering 21 (4) : 595-608. ScholarBank@NUS Repository. https://doi.org/10.1109/TKDE.2008.182|
|Abstract:||Over the pass few years, peer-to-peer (P2P) systems have rapidly grown in popularity and become a dominant means for sharing resources. In these systems, load balancing is a key challenge because nodes are often heterogeneous. While several load balancing schemes have been proposed in the literature, these solutions are typically ad-hoc, heuristic-based and localized. In this paper, we present a general framework, HiGLOB, for global load balancing in structured P2P systems. Each node in HiGLOB has two key components: (1) A histogram manager maintains a histogram that reflects a global view of the distribution of the load in the system, and (2) A load-balancing manager that redistributes the load whenever the node becomes over or under loaded. We exploit the routing metadata to partition the P2P network into non-overlapping regions corresponding to the histogram buckets. We propose mechanisms to keep the cost of constructing and maintaining the histograms low. We further show that our scheme can control and bound the amount of load imbalance across the system. Finally, we demonstrate the effectiveness of HiGLOB by instantiating it over three existing structured P2P systems: Chord, Skip Graph and BATON. Our experimental results indicate that our approach works well in practice. © 2006 IEEE.|
|Source Title:||IEEE Transactions on Knowledge and Data Engineering|
|Appears in Collections:||Staff Publications|
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