Open AccessA SMDP Approach to Evaluate the Performance of a Vehicular Cloud Computing System with Prioritize Requests
Author(s) -
Amal Ezzidani,
Abdellah Ouammou,
Mohamed Hanini,
Abdelghani Ben Tahar
Publication year - 2021
Publication title -
mathematical modelling and engineering problems/mathematical modelling of engineering problems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.26
H-Index - 11
eISSN - 2369-0747
pISSN - 2369-0739
DOI - 10.18280/mmep.080612
Subject(s) - computer science , cloud computing , markov decision process , resource allocation , scheme (mathematics) , service (business) , computation , distributed computing , process (computing) , resource (disambiguation) , operations research , mathematical optimization , markov process , computer network , engineering , algorithm , mathematical analysis , statistics , mathematics , economy , economics , operating system
In intelligent transportation systems, Vehicular Cloud Computing (VCC) is a new technology that can help ensure road security and transport efficiency. The study and evaluation of performances of a VCC is a topic of crucial interest in these environments. This paper presents a model of the computation resource allocation problem in VCC by considering heterogeneity and priority of service requests. We consider service requests from two classes, Primary service requests and Secondary service requests. We involve a Semi-Markov Decision Process (SMDP) to achieve the optimal policy that maximizes the performances of the VCC system taking into account the variability of resources, the income and the system cost. We utilize an iterative approach to achieve the optimal scheme that characterizes the action to be taken under each state. We validate our study by numerical results that show the effectiveness of the proposed SMDP-based scheme.