Issue No. 02 - April-June (2017 vol. 2)
Jungmin Son , School of Computing and Information Systems, Cloud Computing and Distributed Systems (CLOUDS) Laboratory, University of Melbourne, Melbourne, Vic, Australia
Amir Vahid Dastjerdi , PwC, Melbourne, Australia
Rodrigo N. Calheiros , Engineering and Mathematics, School of Computing, Western Sydney University, NSW, Australia
Rajkumar Buyya , School of Computing and Information Systems, Cloud Computing and Distributed Systems (CLOUDS) Laboratory, University of Melbourne, Melbourne, Vic, Australia
Power management of cloud data centers has received great attention from industry and academia as they are expensive to operate due to their high energy consumption. While hosts are dominant to consume electric power, networks account for 10 to 20 percent of the total energy costs in a data center. Resource overbooking is one way to reduce the usage of active hosts and networks by placing more requests to the same amount of resources. Network resource overbooking can be facilitated by Software Defined Networking (SDN) that can consolidate traffics and control Quality of Service (QoS) dynamically. However, the existing approaches employ fixed overbooking ratio to decide the amount of resources to be allocated, which in reality may cause excessive Service Level Agreements (SLA) violation with workloads being unpredictable. In this paper, we propose dynamic overbooking strategy which jointly leverages virtualization capabilities and SDN for VM and traffic consolidation. With the dynamically changing workload, the proposed strategy allocates more precise amount of resources to VMs and traffics. This strategy can increase overbooking in a host and network while still providing enough resources to minimize SLA violations. Our approach calculates resource allocation ratio based on the historical monitoring data from the online analysis of the host and network utilization without any pre-knowledge of workloads. We implemented it in simulation environment in large scale to demonstrate the effectiveness in the context of Wikipedia workloads. Our approach saves energy consumption in the data center while reducing SLA violations.
Cloud computing, Power demand, Optimization, Routing, Energy consumption, Quality of service
J. Son, A. V. Dastjerdi, R. N. Calheiros and R. Buyya, "SLA-Aware and Energy-Efficient Dynamic Overbooking in SDN-Based Cloud Data Centers," in IEEE Transactions on Sustainable Computing, vol. 2, no. 2, pp. 76-89, 2017.