Working Set Theorems for Routing in Self-Adjusting Skip List Networks

Chen Avin, Iosif Salem, Stefan Schmid

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    This paper explores the design of dynamic network topologies which adjust to the workload they serve, in a demand-aware and online manner. Such self-adjusting networks (SANs) are enabled by emerging optical technologies, and can be found, e.g., in datacenters. SANs can be used to reduce routing costs by moving frequently communicating nodes topologically closer. However, such reconfigurations also come at a cost, introducing a need for online algorithms which strike an optimal balance between the benefits and costs of reconfigurations.This paper presents SANs which provide, for the first time, provable working set guarantees: the routing cost between node pairs is proportional to how recently these nodes communicated last time. Our SANs rely on a distributed implementation of skip lists (which serves as the topology) and provide additional interesting properties such as local routing. Our first contribution is SASL2, which is a randomized and sequential SAN algorithm that achieves the working set property. Then we show how SASL2 can be converted to a distributed algorithm that handles concurrent communication requests and maintains SASL2's properties. Finally, we present deterministic SAN algorithms.

    Original languageAmerican English
    Title of host publicationINFOCOM 2020 - IEEE Conference on Computer Communications
    Pages2175-2184
    Number of pages10
    ISBN (Electronic)9781728164120
    DOIs
    StatePublished - 1 Jul 2020
    Event38th IEEE Conference on Computer Communications, INFOCOM 2020 - Toronto, Canada
    Duration: 6 Jul 20209 Jul 2020

    Publication series

    NameProceedings - IEEE INFOCOM
    Volume2020-July

    Conference

    Conference38th IEEE Conference on Computer Communications, INFOCOM 2020
    Country/TerritoryCanada
    CityToronto
    Period6/07/209/07/20

    All Science Journal Classification (ASJC) codes

    • General Computer Science
    • Electrical and Electronic Engineering

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