Abstract
There is increasing competition among cloud object storage service (COSS) providers as demand for COSSs grows. While various pricing models exist for commercial COSS providers, they do not effectively adapt to changing client demand and resource supply. As a result, many COSS providers are still facing fundamental problems in operational strategy to maximize their profit. In this paper, we propose TD-PnS based on the Lyapunov-drift-minus-profit technique which jointly and dynamically makes decisions on (i) service pricing, (ii) CPU clock scaling and encoding scheduling, (iii) network scheduling, and (iv) energy storage management to maximize COSS provider's profits. We also propose an additional version of TD-PnS, namely TD-PnS-Adv, that adds realistic aspects such as system stabilization. Finally, through trace-driven simulation using real dataset, we demonstrate that the proposed algorithms outperform existing algorithms and pricing models in terms of profit.
Original language | English |
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Title of host publication | Proceedings - 2023 IEEE 16th International Conference on Cloud Computing, CLOUD 2023 |
Editors | Claudio Ardagna, Nimanthi Atukorala, Pete Beckman, Carl K. Chang, Rong N. Chang, Constantinos Evangelinos, Jing Fan, Geoffrey C. Fox, Judy Fox, Christoph Hagleitner, Zhi Jin, Tevfik Kosar, Manish Parashar |
Publisher | IEEE Computer Society |
Pages | 439-449 |
Number of pages | 11 |
ISBN (Electronic) | 9798350304817 |
DOIs | |
State | Published - 2023 |
Event | 16th IEEE International Conference on Cloud Computing, CLOUD 2023 - Hybrid, Chicago, United States Duration: 2 Jul 2023 → 8 Jul 2023 |
Publication series
Name | IEEE International Conference on Cloud Computing, CLOUD |
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Volume | 2023-July |
ISSN (Print) | 2159-6182 |
ISSN (Electronic) | 2159-6190 |
Conference
Conference | 16th IEEE International Conference on Cloud Computing, CLOUD 2023 |
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Country/Territory | United States |
City | Hybrid, Chicago |
Period | 2/07/23 → 8/07/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- Object storage, time dependent pricing, service provider, energy storage system, data encoding