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Multimedia Processing Pricing Strategy in GPU-Accelerated Cloud Computing

delete2020-10-01
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OA
AI
H
He Li *
K
Kaoru Ota
Mianxiong Dong cover
Mianxiong Dong (Mianxiong Dong)
A
Athanasios V. Vasilakos
K
Koji Nagano
DOI:10.1109/TCC.2017.2672554delete
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Abstract

Abstract

En 中文
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 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.
Keywords:
Multimedia
GPU-accelerated
cloud computing
pricing

Journal

I
IEEE Transactions on Cloud Computing
IF:
5
Papers:
1.9K
Citations:
5.1K

Organization

L
Lulea University of Technology
Scholars:
207
Papers: 105
Citations: 957
M
muroran institute of technology
Scholars:
31
Papers: 18
Citations: 112
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