Research On Joint Optimization Of Inter-player Delay And Electricity Costs In The Cloud Gaming

Prompted by the remarkable progress in both cloud computing and GPU virtualization,cloud gaming has become increasingly more popular in the gaming industry.In cloud gaming,games are stored and run on cloud servers and the gamers interact with games through thin clients.Cloud gaming service providers generally employ multiple geographically distributed data centers to deliver their services.The main challenge for cloud gaming service providers is to find the best tradeoff between two contradicting objectives: reducing the infrastructure operating costs and increasing the quality of player's experience.In order to provide a high-quality gaming experience,MCG need to ensure that the response delay between interacting players in different regions is as same as possible,while preserving good-enough absolute response delay experienced by players.In addition,that geo-distributed data centers in different regions are located in different power regions,so that the fluctuation trend of electricity prices is also different,and the PUE of each cloud data center also differ,which makes it becomes possible to reduce power cost by reasonable allocated virtual machines in geo-distributed data centers.In this paper,we address a virtual machine allocation problem for multiple cloud gaming with the objective of minimizing both the inter-player delay among interacting players and the electricity costs of multiple cloud gaming service providers,while providing the good-enough response delay to gamers.We formulate the problem into a constrained multi-objective optimization problem and propose an improved grey wolf algorithm to solve the problem.The performance of our proposed algorithm is assessed by extensive experiments using real-world parameters.The results show that the proposed algorithm is more efficient and effective in comparison with the state-of-the-art algorithms applied to similar problems.