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Adaptive Dispatching of Tasks in the Cloud

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Title: Adaptive Dispatching of Tasks in the Cloud
Authors: Gelenbe, E
Wang, L
Item Type: Journal Article
Abstract: The increasingly wide application of Cloud Computing enables the consolidation of tens of thousands of applications in shared infrastructures. Thus, meeting the QoS requirements of so many diverse applications in such shared resource environments has become a real challenge, especially since the characteristics and workload of applications differ widely and may change over time. This paper presents an experimental system that can exploit a variety of online QoS aware adaptive task allocation schemes, and three such schemes are designed and compared. These are a measurement driven algorithm that uses reinforcement learning, secondly a “sensible” allocation algorithm that assigns tasks to sub-systems that are observed to provide a lower response time, and then an algorithm that splits the task arrival stream into sub-streams at rates computed from the hosts’ processing capabilities. All of these schemes are compared via measurements among themselves and with a simple round-robin scheduler, on two experimental test-beds with homogenous and heterogenous hosts having different processing capacities.
Issue Date: 28-Aug-2015
Date of Acceptance: 18-Aug-2015
URI: http://hdl.handle.net/10044/1/25819
DOI: https://dx.doi.org/10.1109/TCC.2015.2474406
ISSN: 2168-7161
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Journal / Book Title: IEEE Transactions on Cloud Computing
Copyright Statement: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 610764
Publication Status: Published
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering



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