Hash-based Proximity Clustering for Load Balancing in Heterogeneous DHT Networks

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Hash-based Proximity Clustering for Load Balancing in Heterogeneous DHT Networks (2006)

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by Haiying Shen, Cheng-zhong Xu

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BibTeX

@MISC{Shen06hash-basedproximity,
    author = {Haiying Shen and Cheng-zhong Xu},
    title = {Hash-based Proximity Clustering for Load Balancing in Heterogeneous DHT Networks},
    year = {2006}
}

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Abstract

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.

Keyphrases

load balancing heterogeneous dht network hash-based proximity clustering dht network regular node networking capacity proximity-aware algorithm proximity information dht node hash-based proximity churn resilient auxiliary network strong resilience network node heterogeneity dhts time-varying load characteristic dht load physical proximity information inherent load uneven distribution problem locality-aware randomized load traffic bottleneck simulation result consistent hashing dht load balancing hierarchical structure dynamism nature

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