@article{oai:muroran-it.repo.nii.ac.jp:00010212,
 author = {LI, He and 李, 鶴 and OTA,  Kaoru and 太田, 香 and DONG,  Mianxiong and 董, 冕雄 and VASILAKOS, Athanasios V. and 永野,  宏治 and NAGANO, Koji},
 journal = {IEEE Transactions on Cloud Computing},
 month = {Feb},
 note = {application/pdf, 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 GPU-accelerated multimedia processing service pricing strategy for maximize the profits of both 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 provider's 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.},
 pages = {1--1},
 title = {Multimedia Processing Pricing Strategy in GPU-accelerated Cloud Computing},
 year = {2017},
 yomi = {リ, ホ and オオタ, カオル and トウ, メンユウ and ナガノ, コウジ}
}