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2017 IEEE 10th International Conference on Cloud Computing (CLOUD) (2017)
Honolulu, Hawaii, United States
June 25, 2017 to June 30, 2017
ISSN: 2159-6190
ISBN: 978-1-5386-1993-3
pp: 18-25
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.
INDEX TERMS
Routing, Control systems, Resource management, Scheduling, Servers, Load management
CITATION

H. Yuan, J. Bi, J. Zhang, W. Tan and K. Huang, "Workload-Aware Revenue Maximization in SDN-Enabled Data Center," 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), Honolulu, Hawaii, United States, 2017, pp. 18-25.
doi:10.1109/CLOUD.2017.12
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