@inproceedings{fdc27a224180473492731682122f21b1,
title = "Location-sensitive resource optimization for profit maximization in distributed data centers",
abstract = "Infrastructure in distributed cloud computing systems (DC2Ss) is concurrently shared by multiple different applications to flexibly and cost-effectively provide various services. It becomes a challenge to maximize the profit of DC2Ss due to the fact that Internet service provider (ISP) bandwidth price, availability of green energy, electricity price, and revenue brought by tasks differ from multiple sites. To solve it, this work designs a Location-Sensitive Resource optimization approach by considering spatial variations in DC2Ss to achieve profit maximization for DC2Ss by optimizing ISP and server resources. This work formulates the profit maximization problem as convex optimization and solved with the interior point method. Realistic data-based simulations prove that higher profit and throughput are achieved than two widely used approaches.",
keywords = "Convex optimization, Data centers, Distributed computing, Profit maximization, Task scheduling",
author = "Haitao Yuan and Jing Bi",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 ; Conference date: 06-10-2019 Through 09-10-2019",
year = "2019",
month = oct,
doi = "10.1109/SMC.2019.8914588",
language = "英语",
series = "Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "39--44",
booktitle = "2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019",
address = "美国",
}