In the upcoming B5G/6G era,Virtual Reality(VR)over wireless has become a typical application,which is an inevitable trend in the development of video.However,in immersive and interactive VR experiences,VR services typ...In the upcoming B5G/6G era,Virtual Reality(VR)over wireless has become a typical application,which is an inevitable trend in the development of video.However,in immersive and interactive VR experiences,VR services typically exhibit high delay,while simultaneously posing challenges for the energy consumption of local devices.To address these issues,this paper aims to improve the performance of VR service in the edge-terminal cooperative system.Specifically,we formulate a joint Caching,Computing,and Communication(3C)VR service policy problem by optimizing the weighted sum of the total VR delivery delay and the energy consumption of local devices.To design the optimal VR service policy,the optimization problem is decoupled into three independent subproblems to be solved separately.To improve the caching efficiency within the network,a Bert-based user interest analysis method is first proposed to accurately characterize the content request behavior.Based on this,a service cost minimum-maximization problem is formulated under the consideration of performance fairness among users.Then,the joint caching and computing scheme is derived for each user with a given allocation of communication resources while a bisection-based communication scheme is acquired with the given information on the joint caching and computing policy.With alternative optimization,an optimal policy for joint 3C based on user interest can be finally obtained.Simulation results are presented to demonstrate the superiority of the proposed user interest-aware caching scheme and the effectiveness of the joint 3C optimization policy while considering user fairness.Our code is available at https://github.com/mrfuqaq1108/Interest-Aware-Joint-3C-Optimization.展开更多
基金supported in part by the Graduate Research Innovation Project of Chongqing under grant CYB23237in part by the Doctoral Candidate Innovative Talent Program of CQUPT under grant BYJS202201+3 种基金in part by the National Natural Science Foundation of China(62271096,U20A20157)in part by the Natural Science Foundation of Chongqing,China(cstc2020jcyjzdxmX0024)in part by the University Innovation Research Group of Chongqing(CXQT20017)in part by the Youth Innovation Group Support Program of ICE Discipline of CQUPT(SCIE-QN-2022-04).
文摘In the upcoming B5G/6G era,Virtual Reality(VR)over wireless has become a typical application,which is an inevitable trend in the development of video.However,in immersive and interactive VR experiences,VR services typically exhibit high delay,while simultaneously posing challenges for the energy consumption of local devices.To address these issues,this paper aims to improve the performance of VR service in the edge-terminal cooperative system.Specifically,we formulate a joint Caching,Computing,and Communication(3C)VR service policy problem by optimizing the weighted sum of the total VR delivery delay and the energy consumption of local devices.To design the optimal VR service policy,the optimization problem is decoupled into three independent subproblems to be solved separately.To improve the caching efficiency within the network,a Bert-based user interest analysis method is first proposed to accurately characterize the content request behavior.Based on this,a service cost minimum-maximization problem is formulated under the consideration of performance fairness among users.Then,the joint caching and computing scheme is derived for each user with a given allocation of communication resources while a bisection-based communication scheme is acquired with the given information on the joint caching and computing policy.With alternative optimization,an optimal policy for joint 3C based on user interest can be finally obtained.Simulation results are presented to demonstrate the superiority of the proposed user interest-aware caching scheme and the effectiveness of the joint 3C optimization policy while considering user fairness.Our code is available at https://github.com/mrfuqaq1108/Interest-Aware-Joint-3C-Optimization.
