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Proceedings ArticleDOI

Near-perfect load balancing by randomized rounding

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TLDR
It is proved that in comparison to the corresponding model of Rabani, Sinclair, and Wanka (1998) with arbitrary roundings, the randomization yields an improvement of roughly a square root of the achieved discrepancy in the same number of time-steps on all graphs.
Abstract
We consider and analyze a new algorithm for balancing indivisible loads on a distributed network with n processors. The aim is minimizing the discrepancy between the maximum and minimum load. In every time-step paired processors balance their load as evenly as possible. The direction of the excess token is chosen according to a randomized rounding of the participating loads.We prove that in comparison to the corresponding model of Rabani, Sinclair, and Wanka (1998) with arbitrary roundings, the randomization yields an improvement of roughly a square root of the achieved discrepancy in the same number of time-steps on all graphs. For the important case of expanders we can even achieve a constant discrepancy in O(log n (log log n)3) rounds. This is optimal up to loglog-factors while the best previous algorithms in this setting either require ©(log2 n) time or can only achieve a logarithmic discrepancy. Our new result also demonstrates that with randomized rounding the difference between discrete and continuous load balancing vanishes almost completely.

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Proceedings ArticleDOI

Improved Analysis of Deterministic Load-Balancing Schemes

TL;DR: In this article, the authors consider the problem of deterministic load balancing of tokens in the discrete model, where each node exchanges some of its tokens with each of its neighbors in the network.
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Tight Bounds for Randomized Load Balancing on Arbitrary Network Topologies

TL;DR: In this paper, the authors consider the problem of balancing load items (tokens) in networks, and show that for any regular network in the matching model, all nodes have the same load up to an additive constant in (asymptotically) the same number of rounds as required in the continuous case.
Proceedings ArticleDOI

A simple approach for adapting continuous load balancing processes to discrete settings

TL;DR: A general method that converts a wide class of continuous neighborhood load balancing algorithms into a discrete version that achieves asymptotically lower discrepancies and presents a randomized version of the algorithm balancing the load if the initial load on every node is large enough.
Proceedings ArticleDOI

Improved Bounds for Discrete Diffusive Load Balancing

TL;DR: A potential function argument is used to show that a better load balance can be obtained when the algorithm is allowed to run longer compared to the algorithm of [1], which is deterministic and extends the algorithm from the case of uniform speeds to non-uniform speeds.
Posted Content

Efficiently Enumerating Hitting Sets of Hypergraphs Arising in Data Profiling

TL;DR: In this article, a method to enumerate the inclusion-wise minimal hitting sets of a hypergraph has been proposed, where the cardinality of the set which is to be extended is defined as the largest minimal solution.
References
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Randomized gossip algorithms

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Proceedings ArticleDOI

Local divergence of Markov chains and the analysis of iterative load-balancing schemes

TL;DR: This work develops a general technique for the quantitative analysis of iterative distributed load balancing schemes, and applies this technique to obtain bounds on the number of rounds required to achieve coarse balancing in general networks, cycles and meshes in these models.
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