@inproceedings{dc15f18363d14cfc94d937ab783c33f9,
title = "Workload-Aware Revenue Maximization in SDN-Enabled Data Center",
abstract = "Nowadays many companies and organizations choose to deploy their applications in data centers to leverage resource sharing. The increase in tasks of multiple applications, however, makes it challenging for a data center provider to maximize its revenue by intelligently scheduling tasks in software-defined networking (SDN)-enabled data centers. Existing SDN controllers only reduce network latency while ignoring virtual machine (VM) latency, thus may lead to revenue loss. In the context of SDN-enabled data centers, this paper presents a workload-aware revenue maximization (WARM) approach to maximize the revenue from a data center provider's perspective. The core idea is to jointly consider the optimal combination of VMs and routing paths for tasks of each application. Comparing with state-of-the-art methods, the experimental results show that WARM yields the best schedules that not only increase the revenue but also reduce the round-trip time of tasks of all applications.",
keywords = "Cloud data center, metaheuristic, revenue maximization, software-defined networking, task scheduling",
author = "Haitao Yuan and Jing Bi and Jia Zhang and Wei Tan and Keman Huang",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 10th IEEE International Conference on Cloud Computing, CLOUD 2017 ; Conference date: 25-06-2017 Through 30-06-2017",
year = "2017",
month = sep,
day = "8",
doi = "10.1109/CLOUD.2017.12",
language = "英语",
series = "IEEE International Conference on Cloud Computing, CLOUD",
publisher = "IEEE Computer Society",
pages = "18--25",
editor = "Fox, \{Geoffrey C.\}",
booktitle = "Proceedings - 2017 IEEE 10th International Conference on Cloud Computing, CLOUD 2017",
address = "美国",
}