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Load balancing oriented computation offloading in mobile cloudlet
Yao D.3; Gui L.3; Hou F.4; Sun F.3; Mo D.1; Shan H.2
2018-02-08
Conference Name86th IEEE Vehicular Technology Conference (VTC-Fall)
Source PublicationIEEE Vehicular Technology Conference
Volume2017-September
Pages1-6
Conference DateSEP 24-27, 2017
Conference PlaceToronto, CANADA
CountryCANADA
Author of SourceIEEE
Publication Place345 E 47TH ST, NEW YORK, NY 10017 USA
PublisherIEEE
Abstract

The limited computing ability of mobile device constrains its performance on complex mobile applications. Mobile cloud computing (MCC) has therefore emerged to migrate computation-intensive tasks to remote clouds or mobile cloudlets. Most strategies allocate tasks with minimal response time yet few consider the load of the nodes. In this paper, we focus on the load balancing problem for nodes when they conduct offloading. We first establish a five-tuple characterized task model to capture the response time of offloaded tasks. Then, we formulate the task allocation problem as an integer linear problem (ILP) under certain conditions. Furthermore, we propose a two-step appointment-driven strategy to solve this problem with minimal task response time. Specifically, a modified genetic algorithm (GA) is adopted to coordinate the load of the nodes. Simulations are conducted to prove the feasibility of our strategy and evaluate the performance of load coordination.

DOI10.1109/VTCFall.2017.8288336
URLView the original
Indexed BySCI
Language英语
WOS Research AreaEngineering ; Telecommunications
WOS SubjectEngineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000428141602096
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Affiliation1.Institute of China Electronic Equipment System Engineering Corporation
2.Zhejiang University
3.Shanghai Jiao Tong University
4.Universidade de Macau
Recommended Citation
GB/T 7714
Yao D.,Gui L.,Hou F.,et al. Load balancing oriented computation offloading in mobile cloudlet[C]//IEEE. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2018:1-6.
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