Research Area:  Cloud Computing
Graphics processing unit (GPU) accelerated processing performs significant efficiency in many multimedia applications. With the development of GPU cloud computing, more and more cloud providers focus on GPU-accelerated services. Since the high maintenance cost and different speedups for various applications, GPU-accelerated services still need a different pricing strategy. Thus, in this paper, we propose an optimal pricing strategy of GPU-accelerated multimedia processing services for maximizing the profits of both the cloud provider and users. We first analyze the revenues and costs of the cloud provider and users when users adopt GPU-accelerated multimedia processing services then state the profit functions of both the cloud provider and users. With a game theory based method, we find the optimal solutions of both the cloud providers and users profit functions. Finally, through large scale simulations, our pricing strategy brings higher profit to the cloud provider and users compared to the original pricing strategy of GPU cloud services.
Author(s) Name:  He Li,Kaoru Ota,Mianxiong Dong,Athanasios V. Vasilakos and Koji Nagano
Journal name:  IEEE Transactions on Cloud Computing
Publisher name:  IEEE
Volume Information:  Oct.-Dec. 2020, pp. 1264-1273, vol. 8
Paper Link:   https://www.computer.org/csdl/journal/cc/2020/04/07862178/13rRUB6SpNP