The development of intelligent connected vehicles(ICVs)has tremendously inspired the emergence of a new computing paradigm called mobile edge computing(MEC),which meets the demands of delay-sensitive on-vehicle applic...The development of intelligent connected vehicles(ICVs)has tremendously inspired the emergence of a new computing paradigm called mobile edge computing(MEC),which meets the demands of delay-sensitive on-vehicle applications.Most existing studies focusing on the issue of task offloading in ICVs assume that the MEC server can directly complete computation tasks without considering the necessity of service caching.However,this is unrealistic in practice because a large number of tasks require the use of corresponding third-party libraries and databases,that is,service caching.Therefore,we investigate the delay optimization in an MEC-enabled ICVs system with multiple mobile vehicles,resource-limited base stations(BSs),and one cloud server.We aim to determine the optimal service caching and task offloading decisions to minimize the overall system delay using mixed-integer nonlinear programming.To address this problem,we first convert it into a quadratically constrained quadratic program and then propose an efficient semidefinite relaxation-based joint service caching and task offloading(JSCTO)algorithm to obtain the service caching and task offloading decisions.In the simulations,we validate the efficiency of our proposed method by setting different numbers of vehicles and the storage capacity of BSs.The results show that our proposed JSCTO algorithm can significantly decrease the total delay of all offloaded tasks compared with the cloud processing only scheme.展开更多
With the development of automobile intelligence and connectivity,Intelligent and Connected Vehicle(ICV)is an inevitable trend in the transformation and upgrading of the automotive industry.The maturity of any advanced...With the development of automobile intelligence and connectivity,Intelligent and Connected Vehicle(ICV)is an inevitable trend in the transformation and upgrading of the automotive industry.The maturity of any advanced technology is inseparable from a large number of test verifications,especially the research and application of automotive technology require a large number of reliable tests for evaluation and confirmation.Therefore,the ICV Test Site(ICVTS)will become a key deployment area.In this paper,we analyze the development status of ICVTS outside and within China,summarize the shortcomings of the existing test sites,and put forward some targeted suggestions,in an effort to guide the development and construction of ICVTS towards the path that seems to be most promising.展开更多
基金the National Natural Science Foundation of China(Nos.61772130 and 62072096)the Fundamental Research Funds for the Central Universities(No.2232020A-12)+1 种基金the International S&T Cooperation Program of Shanghai Science and Technology Commission(No.20220713000)the Young Top-Notch Talent Program in Shanghai。
文摘The development of intelligent connected vehicles(ICVs)has tremendously inspired the emergence of a new computing paradigm called mobile edge computing(MEC),which meets the demands of delay-sensitive on-vehicle applications.Most existing studies focusing on the issue of task offloading in ICVs assume that the MEC server can directly complete computation tasks without considering the necessity of service caching.However,this is unrealistic in practice because a large number of tasks require the use of corresponding third-party libraries and databases,that is,service caching.Therefore,we investigate the delay optimization in an MEC-enabled ICVs system with multiple mobile vehicles,resource-limited base stations(BSs),and one cloud server.We aim to determine the optimal service caching and task offloading decisions to minimize the overall system delay using mixed-integer nonlinear programming.To address this problem,we first convert it into a quadratically constrained quadratic program and then propose an efficient semidefinite relaxation-based joint service caching and task offloading(JSCTO)algorithm to obtain the service caching and task offloading decisions.In the simulations,we validate the efficiency of our proposed method by setting different numbers of vehicles and the storage capacity of BSs.The results show that our proposed JSCTO algorithm can significantly decrease the total delay of all offloaded tasks compared with the cloud processing only scheme.
文摘With the development of automobile intelligence and connectivity,Intelligent and Connected Vehicle(ICV)is an inevitable trend in the transformation and upgrading of the automotive industry.The maturity of any advanced technology is inseparable from a large number of test verifications,especially the research and application of automotive technology require a large number of reliable tests for evaluation and confirmation.Therefore,the ICV Test Site(ICVTS)will become a key deployment area.In this paper,we analyze the development status of ICVTS outside and within China,summarize the shortcomings of the existing test sites,and put forward some targeted suggestions,in an effort to guide the development and construction of ICVTS towards the path that seems to be most promising.
