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Mobility-aware balanced scheduling algorithm in mobile Grid based on mobile agent

Authors
Lee, JonghyukChoi, SungjinSuh, TaeweonYu, Heonchang
Issue Date
9월-2014
Publisher
CAMBRIDGE UNIV PRESS
Citation
KNOWLEDGE ENGINEERING REVIEW, v.29, no.4, pp.409 - 432
Indexed
SCIE
SCOPUS
Journal Title
KNOWLEDGE ENGINEERING REVIEW
Volume
29
Number
4
Start Page
409
End Page
432
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/97578
DOI
10.1017/S0269888914000149
ISSN
0269-8889
Abstract
The emerging Grid is extending the scope of resources to mobile devices and sensors that are connected through loosely connected networks. Nowadays, the number of mobile device users is increasing dramatically and the mobile devices provide various capabilities such as location awareness that are not normally incorporated in fixed Grid resources. Nevertheless, mobile devices exhibit inferior characteristics such as poor performance, limited battery life, and unreliable communication, compared with fixed Grid resources. Especially, the intermittent disconnection from network owing to users' movements adversely affects performance, and this characteristic makes it inefficient and troublesome to adopt the synchronous message delivery in mobile Grid. This paper presents a mobile Grid system architecture based on mobile agents that support the location management and the asynchronous message delivery in a multi-domain proxy environment. We propose a novel balanced scheduling algorithm that takes users' mobility into account in scheduling. We analyzed users mobility patterns to quantitatively measure the resource availability, which is classified into three types: full availability, partial availability, and unavailability. We also propose an adaptive load-balancing technique by classifying mobile devices into nine groups depending on availability and by utilizing adaptability based on the multi-level feedback queue to handle the job type change. The experimental results show that our scheduling algorithm provides a superior performance in terms of execution times to the one without considering mobility and adaptive load-balancing.
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