A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular Clouds
Main Author: | |
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Publication Date: | 2017 |
Other Authors: | , , , |
Format: | Conference object |
Language: | eng |
Source: | Repositório Institucional da UNESP |
Download full: | http://hdl.handle.net/11449/163843 |
Summary: | Currently, the number of resources within a vehicle is growing. The vehicle can provide its idle resources to other vehicles through a cloud. Thus, these vehicles can communicate with each other to dynamically create a vehicular cloud. Therefore, this vehicular cloud needs to adapt according to the number of available resources that the vehicle members in the cloud are sharing. In this kind of cloud, the control of allocated and shared resources becomes a challenge due to the high mobility of vehicles. With this challenge in mind, we propose an optimal resource allocation scheme in order to maximize the use of the available resources. The optimal problem to maximize the expected average reward system is formulated as a Semi-Markov Decision Process (SMDP). The SMDP problem is solved by an iterative algorithm. Numerical results have shown that the proposed scheme has a stable behavior independent of the frequency of requests or the amount of resources. Furthermore, the proposed solution keeps the block rate at 20%, priorizing the allocation that will maximize the utilization of the available resources. |
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A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular CloudsCurrently, the number of resources within a vehicle is growing. The vehicle can provide its idle resources to other vehicles through a cloud. Thus, these vehicles can communicate with each other to dynamically create a vehicular cloud. Therefore, this vehicular cloud needs to adapt according to the number of available resources that the vehicle members in the cloud are sharing. In this kind of cloud, the control of allocated and shared resources becomes a challenge due to the high mobility of vehicles. With this challenge in mind, we propose an optimal resource allocation scheme in order to maximize the use of the available resources. The optimal problem to maximize the expected average reward system is formulated as a Semi-Markov Decision Process (SMDP). The SMDP problem is solved by an iterative algorithm. Numerical results have shown that the proposed scheme has a stable behavior independent of the frequency of requests or the amount of resources. Furthermore, the proposed solution keeps the block rate at 20%, priorizing the allocation that will maximize the utilization of the available resources.NSERCDiva networkTransit networkFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Canada Resarch chairs grantFed Inst Sao Paulo IFSP, Catanduva, SP, BrazilUniv Ottawa, Sch Elect Engn & Comp Sci, Ottawa, ON, CanadaUniv Fed Sao Carlos, Dept Comp Sci, Sao Carlos, SP, BrazilUniv Estadual Paulista, Dept Matemat & Comp, Presidente Prudente, SP, BrazilUniv Estadual Paulista, Dept Matemat & Comp, Presidente Prudente, SP, BrazilFAPESP: 2015/11536-4FAPESP: 2015/18898-9IeeeFed Inst Sao Paulo IFSPUniv OttawaUniversidade Federal de São Carlos (UFSCar)Universidade Estadual Paulista (Unesp)Meneguette, Rodolfo I.Boukerche, AzzedinePimenta, Adinovam H. M.Meneguette, Messias [UNESP]IEEE2018-11-26T17:45:10Z2018-11-26T17:45:10Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject62017 Ieee International Conference On Communications (icc). New York: Ieee, 6 p., 2017.1550-3607http://hdl.handle.net/11449/163843WOS:000424872102070Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2017 Ieee International Conference On Communications (icc)info:eu-repo/semantics/openAccess2021-10-23T21:44:29Zoai:repositorio.unesp.br:11449/163843Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:44:29Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular Clouds |
title |
A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular Clouds |
spellingShingle |
A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular Clouds Meneguette, Rodolfo I. |
title_short |
A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular Clouds |
title_full |
A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular Clouds |
title_fullStr |
A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular Clouds |
title_full_unstemmed |
A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular Clouds |
title_sort |
A Resource Allocation Scheme Based on Semi-Markov Decision Process for Dynamic Vehicular Clouds |
author |
Meneguette, Rodolfo I. |
author_facet |
Meneguette, Rodolfo I. Boukerche, Azzedine Pimenta, Adinovam H. M. Meneguette, Messias [UNESP] IEEE |
author_role |
author |
author2 |
Boukerche, Azzedine Pimenta, Adinovam H. M. Meneguette, Messias [UNESP] IEEE |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Fed Inst Sao Paulo IFSP Univ Ottawa Universidade Federal de São Carlos (UFSCar) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Meneguette, Rodolfo I. Boukerche, Azzedine Pimenta, Adinovam H. M. Meneguette, Messias [UNESP] IEEE |
description |
Currently, the number of resources within a vehicle is growing. The vehicle can provide its idle resources to other vehicles through a cloud. Thus, these vehicles can communicate with each other to dynamically create a vehicular cloud. Therefore, this vehicular cloud needs to adapt according to the number of available resources that the vehicle members in the cloud are sharing. In this kind of cloud, the control of allocated and shared resources becomes a challenge due to the high mobility of vehicles. With this challenge in mind, we propose an optimal resource allocation scheme in order to maximize the use of the available resources. The optimal problem to maximize the expected average reward system is formulated as a Semi-Markov Decision Process (SMDP). The SMDP problem is solved by an iterative algorithm. Numerical results have shown that the proposed scheme has a stable behavior independent of the frequency of requests or the amount of resources. Furthermore, the proposed solution keeps the block rate at 20%, priorizing the allocation that will maximize the utilization of the available resources. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01 2018-11-26T17:45:10Z 2018-11-26T17:45:10Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
2017 Ieee International Conference On Communications (icc). New York: Ieee, 6 p., 2017. 1550-3607 http://hdl.handle.net/11449/163843 WOS:000424872102070 |
identifier_str_mv |
2017 Ieee International Conference On Communications (icc). New York: Ieee, 6 p., 2017. 1550-3607 WOS:000424872102070 |
url |
http://hdl.handle.net/11449/163843 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2017 Ieee International Conference On Communications (icc) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
6 |
dc.publisher.none.fl_str_mv |
Ieee |
publisher.none.fl_str_mv |
Ieee |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1799964581729140736 |