Abstract
Vehicular cloud (VC) is an emerging technology where multiple vehicles form a cloud to share their abundant resources and carry out a heavy job in a cooperative manner. By using VC, each vehicle can perform various VC applications requiring heavy resources. In this regards, it is not a trivial issue to choose appropriate vehicles to complete the given task according to vehicular mobility and each VC service type. In this paper, we suggest a reliable vehicle selection algorithm (RVSA) to minimize the cost of completing the requested task for solving mixed integer nonlinear programming (MINLP) vehicle selection problem. Evaluation result demonstrates that RVSA can achieve to reduce significantly the task completion cost over a wide range of vehicular mobility compared with other conventional algorithms.
Original language | English |
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Title of host publication | 19th Asia-Pacific Network Operations and Management Symposium |
Subtitle of host publication | Managing a World of Things, APNOMS 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 319-321 |
Number of pages | 3 |
ISBN (Electronic) | 9781538611012 |
DOIs | |
Publication status | Published - 2017 Nov 1 |
Event | 19th Asia-Pacific Network Operations and Management Symposium, APNOMS 2017 - Seoul, Korea, Republic of Duration: 2017 Sep 27 → 2017 Sep 29 |
Other
Other | 19th Asia-Pacific Network Operations and Management Symposium, APNOMS 2017 |
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Country | Korea, Republic of |
City | Seoul |
Period | 17/9/27 → 17/9/29 |
Keywords
- mixed integer nonlinear programming (MINLP)
- vehicles selection
- Vehicular cloud (VC)
ASJC Scopus subject areas
- Computer Networks and Communications
- Hardware and Architecture
- Information Systems and Management