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Proceedings ArticleDOI

Near-perfect load balancing by randomized rounding

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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Citations
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Threshold Load Balancing in Networks

TL;DR: It is shown that convergence is achieved in a number of rounds that is only logarithmic in m and polynomial in structural properties of the graph, and even when migration is fully controlled by users, protocols obtain rapid convergence to approximately balanced states.
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Improved Analysis of Deterministic Load-Balancing Schemes

TL;DR: It is proved that algorithms which are cumulatively fair and where every node retains a sufficient part of its load in each step, achieve a discrepancy of O(d√log n/μ, d√n) in time O(T), and that in general neither of these assumptions may be omitted without increasing discrepancy.
Proceedings ArticleDOI

Discrete Load Balancing in Heterogeneous Networks with a Focus on Second-Order Diffusion

TL;DR: A framework for randomly rounding the flow generated by continuous diffusion schemes over the edges of a graph in order to obtain corresponding discrete schemes and a bound for the minimum initial load in a network that is sufficient to prevent the occurrence of negative load during the execution of second order diffusion schemes are provided.
Posted Content

Balancing indivisible real-valued loads in arbitrary networks

TL;DR: This work proposes a novel algorithm for dynamic balancing of indivisible, real-valued loads, and indicates that the increased communication cost of the proposed algorithm is compensated by a higher solution quality, leading on average to about an order of magnitude gain in overall performance.
Proceedings ArticleDOI

Gossip vs. Markov chains, and randomness-efficient rumor spreading

TL;DR: This work establishes a new connection between the rumor spreading process in an arbitrary graph and certain Markov chains, and establishes a reduction from rumor spreading processes to branching programs, and shows that, for many graph families, O(poly log n) random bits in total suffice for fast rumor spreading.
References
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Journal ArticleDOI

Randomized gossip algorithms

TL;DR: This work analyzes the averaging problem under the gossip constraint for an arbitrary network graph, and finds that the averaging time of a gossip algorithm depends on the second largest eigenvalue of a doubly stochastic matrix characterizing the algorithm.
Journal ArticleDOI

Randomized rounding: a technique for provably good algorithms and algorithmic proofs

TL;DR: In this paper, the relation between a class of 0-1 integer linear programs and their rational relaxations was studied and a randomized algorithm for transforming an optimal solution of a relaxed problem into a provably good solution for the 0 -1 problem was given.
Journal ArticleDOI

Randomized broadcast in networks

TL;DR: This study has two important applications in distributed computation: in simple, robust and efficient broadcast protocols, and in the maintenance of replicated databases.
Journal ArticleDOI

Counting networks

TL;DR: Two counting network constructions are given that avoid the sequential bottlenecks inherent to earlier solutions and substantially lower the memory contention, and are provided with experimental evidence that they outperform conventional synchronization techniques under a variety of circumstances.
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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