Mobile Crowd Computing with Mobile Agents and Work Stealing

Mobile Crowd Computing (MCC) is a computing paradigm that leverages the collective power of idle smart mobile devices to perform computationally demanding tasks. Since a mobile crowd consists of diverse smart mobile devices (i.e. varying processing capacities, memory, battery, etc.) load balancing becomes an important aspect to achieve expected outcomes. We hypothesize that effective load balancing for MCC can be achieved using a combination of mobile agents and a work stealing approach. Thus, in this paper, we present the design, implementation, and evaluation of our mobile agent based MCC framework which uses work stealing for load balancing.

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Publication Details

Published
2024-08-08
DOI
https://doi.org/10.1109/mercon63886.2024.10688742
Citations
1
Primary Topic
Mobile Crowdsensing and Crowdsourcing
Type
article
Field-Weighted Citation Impact
0.41
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article

Mobile Crowd Computing with Mobile Agents and Work Stealing

Kutila Gunasekera, Thamindu Bandara Kiridana, Sathsarani Kapukotuwa, Bhanuja Sasanka Dissanayake
1 citations
Mobile Crowdsensing and Crowdsourcing
0.41
article

Mobile Crowd Computing with Mobile Agents and Work Stealing

Kutila Gunasekera, Thamindu Bandara Kiridana, Sathsarani Kapukotuwa, Bhanuja Sasanka Dissanayake
article en
1 citations

Abstract

Mobile Crowd Computing (MCC) is a computing paradigm that leverages the collective power of idle smart mobile devices to perform computationally demanding tasks. Since a mobile crowd consists of diverse smart mobile devices (i.e. varying processing capacities, memory, battery, etc.) load balancing becomes an important aspect to achieve expected outcomes. We hypothesize that effective load balancing for MCC can be achieved using a combination of mobile agents and a work stealing approach. Thus, in this paper, we present the design, implementation, and evaluation of our mobile agent based MCC framework which uses work stealing for load balancing.

University of Moratuwa (LK)
Decent work and economic growth
Openalex Percentile: Top 27%
Mobile Crowdsensing and Crowdsourcing
0.41
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