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Go, server, go!: parallel computing with moving servers

Published: 01 October 2013 Publication History
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  • Abstract

    In data centers today, servers are stationary and data flows on a hierarchical network of switches and routers. But such static server arrangements require very scalable networks, and many applications are bottlenecked by network bandwidth. In addition, server density is kept low to enable maintenance and upgrades, as well as to increase air flow. In this paper, we propose a design in which servers move physically, and communicate via point-to-point connections (instead of switches). We argue that this allows data transfer bandwidth to scale linearly with the number of servers, and that moving servers is not as expensive as it sounds, at least in terms of power consumption. Moreover, while servers move around, they regularly reach the perimeters of the system, which helps with heat dissipation and with servicing of failed nodes. This design also helps in traditional switch-based networks, to improve density and maintainability.

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    cover image ACM Conferences
    SOCC '13: Proceedings of the 4th annual Symposium on Cloud Computing
    October 2013
    427 pages
    ISBN:9781450324281
    DOI:10.1145/2523616
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    New York, NY, United States

    Publication History

    Published: 01 October 2013

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    SOCC '13
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    SOCC '13: ACM Symposium on Cloud Computing
    October 1 - 3, 2013
    California, Santa Clara

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    SOCC '13 Paper Acceptance Rate 23 of 114 submissions, 20%;
    Overall Acceptance Rate 169 of 722 submissions, 23%

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