The use of memory in randomized load balancing - Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on
نویسنده
چکیده
We consider the following canonical load balancing problem: D r o p n balls in to n bins so as to minimize the m a x i m u m loading. A n execut ion of the well-known “load the least loaded bin” a lgor i thm results in an opt imal loading of one ball per bin. Azar e t . al. (1994) consider an a lgor i thm which assigns each ball to the least loaded of d randomly chosen b ins and show that the m a x i m u m load is + O(1) for d > 2, as compared t o &(1 + o(1)) for d = 1. A dynamic version of the load balancing problem involves j o b s arr iving as a rate nX Poisson process at n r a t e 1 exponent ia l se rver queues is considered in Mi tzenmacher (1996) and in Vvedenskaya e t . al. (1996). T h e y find similar exponent ia l improvements i n per formance for d 2 2 as compared w i t h d = 1. In th is paper, w e consider a var ia t ion of randomized load balancing schemes which involve the use of memory. This is motivated by the observat ion that the loads do not change b y much be tween iterations; hence remember ing “good samples” f r o m one iterat ion for use in fu tu re i terations ought t o pay off significantly. We find th i s is indeed true, and quant i fy the improvement .
منابع مشابه
Unit-Memory Hamming Turbo Codes - Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on
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