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Sensor cloud computing for vehicular applications: from analysis to practical implementation

Authors:

Zhengguo Sheng,

Peyman TalebiFard,

Victor C.M. Leung,

Yingjie ZhouAuthors Info & Claims

DIVANet '14: Proceedings of the fourth ACM international symposium on Development and analysis of intelligent vehicular networks and applications

Pages 53 - 59

https://doi.org/10.1145/2656346.2656350

Published: 21 September 2014 Publication History

Abstract

Advances in sensor cloud computing to support vehicular applications are becoming more important as the need to better utilize computation and communication resources and make them energy efficient. In this paper, we propose a novel approach to minimize energy consumption of processing a vehicular application within mobile wireless sensor networks (MWSN) while satisfying a certain completion time requirement. Specifically, the application can be optimally partitioned, offloaded and executed with helps of peer sensor devices, e.g., a smart phone, thus the proposed solution can be treated as a joint optimization of computing and networking resources. Our theoretical analysis is supplemented by simulation results to show the significance of energy saving by 63% compared to the traditional cloud computing methods. Moreover, a prototype cloud system has been developing to validate the efficiency of sensor cloud strategies in dealing with diverse vehicular applications.

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Cited By

Aloqaily MBalasubramanian VZaman FAl Ridhawi IJararweh YNotare MSun PCoutinho R(2018)Congestion Mitigation in Densely Crowded Environments for Augmenting QoS in Vehicular CloudsProceedings of the 8th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications10.1145/3272036.3272038(49-56)Online publication date: 25-Oct-2018
https://dl.acm.org/doi/10.1145/3272036.3272038
Misic JMisic VBanaie F(2017)Performance of Data Caching in Cloud Sensing2017 IEEE 86th Vehicular Technology Conference (VTC-Fall)10.1109/VTCFall.2017.8288168(1-5)Online publication date: Sep-2017
https://doi.org/10.1109/VTCFall.2017.8288168
Li ZTesfatsion SBastani SAli-Eldin AElmroth EKihl MRanjan R(2017)A Survey on Modeling Energy Consumption of Cloud Applications: Deconstruction, State of the Art, and Trade-Off DebatesIEEE Transactions on Sustainable Computing10.1109/TSUSC.2017.27228222:3(255-274)Online publication date: 1-Jul-2017
https://doi.org/10.1109/TSUSC.2017.2722822
Show More Cited By

Index Terms

Sensor cloud computing for vehicular applications: from analysis to practical implementation
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

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Information

Published In

cover image ACM Conferences

DIVANet '14: Proceedings of the fourth ACM international symposium on Development and analysis of intelligent vehicular networks and applications

September 2014

178 pages

ISBN:9781450330282

DOI:10.1145/2656346

General Chair:
Mirela S.M.A. Notare
Sao Jose Municipal University, Brazil
,
Program Chair:
Robson E. De Grande
NSERC DIVA Research Centre, Canada

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSIM: ACM Special Interest Group on Simulation and Modeling

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 September 2014

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Funding Sources

Natural Sciences and Engineering Research Council of Canada

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MSWiM'14

Sponsor:

SIGSIM

MSWiM'14: 17th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

September 21 - 26, 2014

QC, Montreal, Canada

Acceptance Rates

DIVANet '14 Paper Acceptance Rate 20 of 78 submissions, 26%;

Overall Acceptance Rate 70 of 308 submissions, 23%

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Cited By

Aloqaily MBalasubramanian VZaman FAl Ridhawi IJararweh YNotare MSun PCoutinho R(2018)Congestion Mitigation in Densely Crowded Environments for Augmenting QoS in Vehicular CloudsProceedings of the 8th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications10.1145/3272036.3272038(49-56)Online publication date: 25-Oct-2018
https://dl.acm.org/doi/10.1145/3272036.3272038
Misic JMisic VBanaie F(2017)Performance of Data Caching in Cloud Sensing2017 IEEE 86th Vehicular Technology Conference (VTC-Fall)10.1109/VTCFall.2017.8288168(1-5)Online publication date: Sep-2017
https://doi.org/10.1109/VTCFall.2017.8288168
Li ZTesfatsion SBastani SAli-Eldin AElmroth EKihl MRanjan R(2017)A Survey on Modeling Energy Consumption of Cloud Applications: Deconstruction, State of the Art, and Trade-Off DebatesIEEE Transactions on Sustainable Computing10.1109/TSUSC.2017.27228222:3(255-274)Online publication date: 1-Jul-2017
https://doi.org/10.1109/TSUSC.2017.2722822
Misic VMisic JBanaie F(2017)Towards efficient monitoring in a sensor cloud2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)10.1109/PIMRC.2017.8292662(1-6)Online publication date: Oct-2017
https://doi.org/10.1109/PIMRC.2017.8292662
Udoh EPatterson B(2016)Using the Balanced Scorecard Approach to Appraise the Performance of Cloud ComputingInternational Journal of Grid and High Performance Computing10.4018/IJGHPC.20160101048:1(50-57)Online publication date: Jan-2016
https://doi.org/10.4018/IJGHPC.2016010104
Udoh EPatterson BCordle S(2014)A Performance Analysis of Cloud Computing Using the Balanced Scorecard ApproachProceedings of the 2014 Annual Global Online Conference on Information and Computer Technology10.1109/GOCICT.2014.8(11-16)Online publication date: 3-Dec-2014
https://dl.acm.org/doi/10.1109/GOCICT.2014.8

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