Dynamic load balancing for distributed memory multiprocessors
Journal of Parallel and Distributed Computing
Analysis of a graph coloring based distributed load balancing algorithm
Journal of Parallel and Distributed Computing
Load balancing and Poisson equation in a graph
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Approximate load balancing on dynamic and asynchronous networks
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Efficient schemes for nearest neighbor load balancing
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Strategies for Dynamic Load Balancing on Highly Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
Performance Comparison of Dynamic Load-Balancing Strategies for Distributed Computing
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Dynamic load balancing by diffusion in heterogeneous systems
Journal of Parallel and Distributed Computing
Synchronous distributed load balancing on dynamic networks
Journal of Parallel and Distributed Computing - Special issue: Design and performance of networks for super-, cluster-, and grid-computing: Part II
Design and analysis of the M2LL policy distributed algorithm for load balancing in dynamic networks
ISPA'06 Proceedings of the 2006 international conference on Frontiers of High Performance Computing and Networking
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Load balancing a distributed/parallel system consists in allocating work (load) to its processors so that they have to process approximately the same amount of work or amounts in relation with their computation power. In this paper, we present a new distributed algorithm that implements the Most to Least Loaded (M2LL) policy. This policy aims at indicating pairs of processors, that will exchange loads, taking into account actually broken edges as well as the current load distribution in the system. The M2LL policy fixes the pairs of neighboring processors by selecting in priority the most loaded and the least loaded processor of each neighborhood. Our first and main result is that the M2LL distributed implementation terminates after at most (n/2)驴d t iterations where n and d t are respectively the number of nodes and the degree of the system at time t. We then present a performance comparison between Generalized Adaptive Exchange (GAE) that uses M2LL and Relaxed First Order Scheme (RFOS), two load balancing algorithms for dynamic networks in which only link failures are considered. The comparison is carried out on a dedicated test bed that we have designed and implemented to this end. Our second important result is that although generating more communications, the GAE algorithm with the M2LL policy is faster than RFOS in balancing the system load. In addition, GAE M2LL is able to achieve a more stable balanced state than RFOS and scales well.