{"title":"Fair Connectivity-Oriented Allocation for Combined Resources in VCC Networks","authors":"Binal Tejani, R. E. Grande","doi":"10.1109/ISCC55528.2022.9912984","DOIUrl":null,"url":null,"abstract":"The allocation and management of vehicular resources are essential in enabling services in Vehicular Cloud networks. Combined Resource Units (CRUs) allow for relaxed resource management by utilizing vehicular resources clustered in virtualized units and easing the fulfillment of service requests. Previous works have used mobility-based models such as SMDP and MDP for resource allocation. However, these models have presented significant system overhead, which has impacted the network's performance. Therefore, this work proposes a game theory model for assigning CRUs to satisfy service requests. The utility function of CRUs is maximized by playing a non-cooperative game between service requests. Two different game models are implemented based on exhaustive search and pruning methods. These models use distinct utility functions, which differ in terms of distance and signal strength of the CRUs. Comparing the performance of the two models, the pruning model offers a 90% success rate towards satisfying service requests.","PeriodicalId":309606,"journal":{"name":"2022 IEEE Symposium on Computers and Communications (ISCC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Symposium on Computers and Communications (ISCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCC55528.2022.9912984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The allocation and management of vehicular resources are essential in enabling services in Vehicular Cloud networks. Combined Resource Units (CRUs) allow for relaxed resource management by utilizing vehicular resources clustered in virtualized units and easing the fulfillment of service requests. Previous works have used mobility-based models such as SMDP and MDP for resource allocation. However, these models have presented significant system overhead, which has impacted the network's performance. Therefore, this work proposes a game theory model for assigning CRUs to satisfy service requests. The utility function of CRUs is maximized by playing a non-cooperative game between service requests. Two different game models are implemented based on exhaustive search and pruning methods. These models use distinct utility functions, which differ in terms of distance and signal strength of the CRUs. Comparing the performance of the two models, the pruning model offers a 90% success rate towards satisfying service requests.