Decentralized algorithms using both local and random probes for P2P load balancing

We study randomized algorithms for placing a sequence of n nodes on a circle with unit perimeter. Nodes divide the circle into disjoint arcs. We desire that a newly-arrived node (which is oblivious of its index in the sequence) choose its position on the circle by learning the positions of as few existing nodes as possible. At the same time, we desire that that the variation in arc-lengths be small. To this end, we propose a new algorithm that works as follows: The kth node chooses r random points on the circle, inspects the sizes of v arcs in the vicinity of each random point, and places itself at the mid-point of the largest arc encountered. We show that for any combination of r and v satisfying rv ≥ c log k, where c is a small constant, the ratio of the largest to the smallest arc-length is at most eight w.h.p., for an arbitrarily long sequence of n nodes. This strategy of node placement underlies a novel decentralized load-balancing algorithm that we propose for Distributed Hash...

• Type: Conference
• Year: 2005
• Where: SPAA
• Authors: Krishnaram Kenthapadi, Gurmeet Singh Manku
• Keywords: Algorithm, Disjoint Arcs, Distributed And Parallel Computing, Random Point, SPAA 2005