An Optimized Meta-heuristic Bees Algorithm for Players’ Frame Rate Allocation Problem in Cloud Gaming Environments

Abstract

Recently, cloud gaming has attracted much attention from service providers. The majority of cloud users have hardware limitations on their devices, hence why users are termed “thin clients”. A cloud service provider aims to afford the best-required frames of game scenes with each thin client in order to provide the best Quality of Experience (QoE). The importance of this issue is particularly critical with the emergence of 4K game service levels. Since 4K game scenes impose many demands upon the Central Processing Unit, Graphical Processing Unit, memory and bandwidth, cloud service providers tend to use the strategy of satisfying the highest number of gamers with the least amount of resources. Given that the problem of frame rate allocation is NP-hard, it is not possible to solve it with exact mathematical methods. In this paper, we propose a method inspired by the Bees algorithm. The approach presented in this article could significantly increases cloud providers’ profitability and reduce server-side wastage. Given the emergence of a new game-as-a-service paradigm for cloud-based games, cloud service providers must pay close attention to the issues of profitability and optimal resource allocation. The simulation of the proposed algorithm on the CloudSim simulator platform illustrates its robustness in terms of significant criteria such as runtime, number of admitted users, frame quality level, the QoE, etc.