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IEEE Transactions on Parallel and Distributed Systems
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ICPP '05 Proceedings of the 2005 International Conference on Parallel Processing
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Dynamic load balancing in distributed hash tables
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IEEE Transactions on Parallel and Distributed Systems
Hash-based proximity clustering for efficient load balancing in heterogeneous DHT networks
Journal of Parallel and Distributed Computing
Fast and proximity-aware multi-source overlay multicast under heterogeneous environment
Computer Communications
A fair load balancing algorithm for hypercube-based DHT networks
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
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NETWORKING'08 Proceedings of the 7th international IFIP-TC6 networking conference on AdHoc and sensor networks, wireless networks, next generation internet
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DHT networks based on consistent hashing functions have an inherent load uneven distribution problem. The objective of DHT load balancing is to balance the workload of the network nodes in proportion to their capacity so as to eliminate traffic bottleneck. It is challenging because of the dynamism nature of DHT networks and time-varying load characteristics. In this paper, we present a hash-based proximity clustering approach for load balancing in heterogeneity DHTs. In the approach, DHT nodes are classified as regular nodes and supernodes according to their computing and networking capacities. Regular nodes are grouped and associated with supernodes via consistent hashing of their physical proximity information on the Internet. The supernodes form a self-organized and churn resilient auxiliary network for load balancing. The hierarchical structure facilitates the design and implementation of a locality-aware randomized load balancing algorithm. The algorithm introduces a factor of randomness in the load balancing processes in a range of neighborhood so as to deal with both the proximity and dynamism. Simulation results show the superiority of the approach, in comparison with a number of other DHT load balancing algorithms. The approach performs no worse than existing proximity-aware algorithms and exhibits strong resilience to the effect of churn. It also greatly reduces the overhead of resilient randomized load balancing algorithms due to the use of proximity information.