Quality of Service Aware Reliable Task Scheduling in Vehicular Cloud Computing

Vehicular Cloud Computing (VCC) facilitates real-time execution of many emerging user and intelligent transportation system (ITS) applications by exploiting under-utilized on-board computing resources available in nearby vehicles. These applications have heterogeneous time criticality, i.e., they de...

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Bibliographic Details
Published in:Mobile networks and applications 2016-06, Vol.21 (3), p.482-493
Main Authors: Adhikary, Tamal, Das, Amit Kumar, Razzaque, Md. Abdur, Almogren, Ahmad, Alrubaian, Majed, Hassan, Mohammad Mehedi
Format: Article
Language:English
Subjects:
Algorithms
Cloud computing
Communications Engineering
Computation
Computer Communication Networks
Delay
Electrical Engineering
Engineering
Heterogeneity
Infrastructure
Integer programming
Intelligent transportation systems
IT in Business
Linear programming
Networks
Optimization
Quality of service
Scheduling
Sensors
Task scheduling
Vehicles
Wireless networks
Workers
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Summary:Vehicular Cloud Computing (VCC) facilitates real-time execution of many emerging user and intelligent transportation system (ITS) applications by exploiting under-utilized on-board computing resources available in nearby vehicles. These applications have heterogeneous time criticality, i.e., they demand different Quality-of-Service levels. In addition to that, mobility of the vehicles makes the problem of scheduling different application tasks on the vehicular computing resources a challenging one. In this article, we have formulated the task scheduling problem as a mixed integer linear program (MILP) optimization that increases the computation reliability even as reducing the job execution delay. Vehicular on-board units (OBUs), manufactured by different vendors, have different architecture and computing capabilities. We have exploited MapReduce computation model to address the problem of resource heterogeneity and to support computation parallelization. Performance of the proposed solution is evaluated in network simulator version 3 (ns-3) by running MapReduce applications in urban road environment and the results are compared with the state-of-the-art works. The results show that significant performance improvements in terms of reliability and job execution time can be achieved by the proposed task scheduling model.
ISSN:1383-469X
1572-8153
DOI:10.1007/s11036-015-0657-5