Joint Design Optimization Of Communication,Computing And Caching In Mobile VR Systems

Virtual reality(VR)can bring users an immersive experience and is expected to become a popular application for 5G networks.VR transmission has the requirements of ultra-high bandwidth and low delay,and the generation of VR content also needs to encode and decode a large amount of data.Therefore,VR transmission requires wireless network systems with a lot of computing resources and communication resources.In recent years,Mobile Edge Computing(MEC)has been recognized as one of the key technologie for transmitting VR content in wireless systems.The MEC can deploy computing and storage resources at network edge nodes(e.g.,base stations)to provide services at the edge of the network.However,current research on the MEC framework mainly focuses on reducing the energy consumption caused by the calculation of the mobile device,the mobile device uploading the data to the server of the edge node,and the edge server performs the calculation,which reduce the amount of data that mobile devices need to calculate,and the energy caused by calculation is also decreased.This framework reduce the energy consumption by increasing the communication cost,it is suitable for Augmented Reality(AR)applications with a small amount of data,and is not suitable for VR services with huge bandwidth consumption.In this paper,we proposed a MEC framework that exploiting the computation and caching resources at the mobile VR device,and the edge server caches and offloads a part of data to mobile VR devices in advance,by joint designing optimization of communication,computing and storage resources,the wireless communication resource consumption is minimized under the guaranteed delay requirement.Specifically,for VR video with weak interaction,we use video modular technology to modularize VR video,all VR video chunks are pre-cached on the MEC server,and some of the popular VR video chunks are cached on the mobile device.The MEC server only delivers the components which requested by user and have not been stored in the VR device,and then the VR device uses the received components and other cached components to construct the task,the transmission of the entire VR video is avoided,thereby reducing communication bandwidth consumption.The MEC server can also computes the task by itself and transmit the entire VR video to the user,however,it consumes more communication-resource.Therefore,we proposed a task scheduling strategy to decide which computation model should the MEC server operates to minimize the communication-resource consumption under the delay constraint.We divided the system state into several different situations and analyzed the task scheduling strategy in each case,then the system optimization problem is modeled according to the scheduling strategy.According to the above MEC framework and optimization problems,an optimal task scheduling algorithm based on Lyapunov theory is proposed.We transform the original stochastic optimization problem into a discrete linear programming problem solved in each time slot by Lyapunov principle,and the task scheduling policy is only related to the current system status.Finally,the tradeoffs among communications,computing,and caching are also discussed,and we analytically find that given a target communication resource consumption,the transmission rate is inversely proportional to the computing ability of mobile VR device.This paper builds the simulation platform with MATLAB,the theoretically optimal system performance is used as a benchmark to verify the performance of the optimal task scheduling algorithm proposed in this paper,the paper also verifies the impact of communication,computation and cache resources on system performance.