Efficient multi-player computation offloading for VR edge-cloud computing systems

Abstract

Virtual reality (VR) is considered to be one of the main use cases of the fifth-generation cellular system (5G). In addition, it has been categorized as one of the ultra-low latency applications in which VR applications require an end-to-end latency of 5 ms. However, the limited battery capacity and computing resources of mobile devices restrict the execution of VR applications on these devices. As a result, mobile edge-cloud computing is considered as a new paradigm to mitigate resource limitations of these devices through computation offloading process with low latency. To this end, this paper introduces an efficient multi-player with multi-task computation offloading model with guaranteed performance in network latency and energy consumption for VR applications based on mobile edge-cloud computing. In addition, this model has been formulated as an integer optimization problem whose objective is to minimize the sum cost of the entire system in terms of network latency and energy consumption. Afterwards, a low-complexity algorithm has been designed which provides comprehensive processes for deriving the optimal computation offloading decision in an efficient manner. Furthermore, we provide a prototype and real implementation for the proposed system using OpenAirInterface software. Finally, simulations have been conducted to validate our proposed model and prove that the network latency and energy consumption can be reduced by up to 26.2%, 27.2% and 10.9%, 12.2% in comparison with edge and cloud execution, respectively.