AIMD scheduling and resource allocation in distributed computing systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)
118 Downloads (Pure)

Abstract

We consider the problem of simultaneous scheduling and resource allocation of an incoming flow of requests to a set of computing units. By representing each computing unit as a node, we model the overall system as a multi-queue scheme. Inspired by congestion control approaches in communication networks, we propose an AIMD-like (additive increase multiplicative decrease) admission control policy that is stable irrespective of the total number of nodes and AIMD parameters. The admission policy allows us to establish an event-driven discrete model, triggered by a locally identifiable enabling condition. Subsequently, we propose a decentralized resource allocation strategy via a simple nonlinear state feedback controller, guaranteeing global convergence to a bounded set in finite time. Last, we reveal the connection of these properties with Quality of Service specifications, by calculating local queuing time via a simple formula consistent with Little’s Law.
Original languageEnglish
Title of host publication 2021 60th IEEE conference on decision and control (CDC): proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4642-4647
Number of pages6
ISBN (Electronic)9781665436595
ISBN (Print)9781665436601
DOIs
Publication statusPublished - 01 Feb 2022
Event60th IEEE Conference on Decision and Control - Austin, United States
Duration: 13 Dec 202117 Dec 2021
https://2021.ieeecdc.org/

Publication series

NameIEEE Conference on Decision and Control: Proceedings
PublisherIEEE
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference60th IEEE Conference on Decision and Control
Abbreviated titleCDC 2021
Country/TerritoryUnited States
CityAustin
Period13/12/202117/12/2021
Internet address

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