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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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Citations
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Proceedings ArticleDOI

Almost tight bounds for rumour spreading with conductance

TL;DR: It is shown that if a connected graph with n nodes has conductance φ then rumour spreading, also known as randomized broadcast, successfully broadcasts a message within ~O(φ-1 • log n), many rounds with high probability, regardless of the source, by using the PUSH-PULL strategy.
Proceedings ArticleDOI

Rumour spreading and graph conductance

TL;DR: It is shown that if a connected graph with n nodes has conductance φ then rumour spreading, also known as randomized broadcast, successfully broadcasts a message within O(log4n/φ6) many steps, with high probability, using the PUSH-PULL strategy.
Proceedings ArticleDOI

Tight Bounds for Randomized Load Balancing on Arbitrary Network Topologies

TL;DR: This work investigates several randomized protocols for different communication models in the discrete case of discrete load balancing and demonstrates that there is almost no difference between the discrete and continuous case.
Proceedings ArticleDOI

Quasirandom load balancing

TL;DR: It is shown that first-passage probabilities of a random walk on a path with arbitrary weights can be expressed as a convolution of independent geometric probability distributions and the quasirandom algorithm is the first known algorithm for this setting which is optimal both in time and achieved smoothness.
Proceedings ArticleDOI

Scalable software-defined networking through hybrid switching

TL;DR: A novel hybrid switching design is presented, which integrates traditional switching and SDN switching for the purpose of achieving both scalability and optimal performance and shows that the integration also leads to unexpected benefits of making both types of switching more efficient under the hybrid design.
References
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Journal ArticleDOI

A new analytical method for parallel, diffusion-type load balancing

TL;DR: A new proof technique is proposed which can be used to analyse many parallel load balancing algorithms, and is designed to handle concurrent load balancing actions, which are often the main obstacle in the analysis.
Proceedings ArticleDOI

A new analytical method for parallel, diffusion-type load balancing

TL;DR: A new proof technique is proposed which can be used to analyze many parallel load balancing algorithms, designed to handle concurrent load balancing actions, which are often the main obstacle in the analysis.
Journal ArticleDOI

Distributing Unit Size Workload Packages in Heterogeneous Networks

TL;DR: By modifying a randomized strategy invented for homogeneous systems, this paper can achieve an asymptotically minimal expected overload in l1, l2 and l1 norm while only slightly increasing the run-time by a logarithmic factor.
Book

Small-depth counting networks and related topics

TL;DR: A uniform polynomial-time construction of an O(lg n)-depth counting network which depends heavily on the existential result, but makes use of extractor functions introduced in [25].
Journal ArticleDOI

The Convergence of Realistic Distributed Load-Balancing Algorithms

TL;DR: It is proved that the largest load difference between any two processors, in the final stable situation of the load-balancing algorithms in this model, is upper-bounded by the diameter of the topology.
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