ABSTRACT
Cloud computing utilizes arbitrary mega-scale computing infrastructures and is currently revolutionizing the ICT landscape by allowing remote access to computing power and data over the Internet. Besides the huge economical impact Cloud technology exhibits a high potential to be a cornerstone of a new generation of sustainable and energy-efficient ICT. The challenging issue thereby is the energy-efficient utilization of physical machines (PMs) and the resource-efficient management of virtual machines (VMs) while attaining promised non-functional qualities of service expressed by means of Service Level Agreements (SLAs). Currently, there exist solutions for PM power management, VM migrations, and dynamic reconfiguration of VMs. However, most of the existing approaches consider each of them alone, and only use rudimentary concepts for migration costs or disrespect the nature of the highly volatile workloads. In this paper we present an integrated approach for VM migration and reconfiguration, and PM power management. Thereby, we incorporate an autonomic management loop, where proactive actions are suggested for all three areas in a hierarchically structured way. We evaluate our approach with both, synthetic workload data and real-word monitoring data of a Next Generation Sequencing (NGS) application used for the protein folding in the bioinformatics area. The efficacy of our approach is evaluated by considering classical algorithms like First Fit, Monte Carlo and Vector Packing, adapted for energy-efficient reallocation. The results show energy savings up to 61.6% while keeping acceptably low SLA violation rates.
- Drools, www.drools.org.Google Scholar
- Raphael M. Bahati and Michael A. Bauer. Adapting to run-time changes in policies driving autonomic management. In ICAS '08: Proceedings of the 4th Int. Conf. on Autonomic and Autonomous Systems, Washington, DC, USA, 2008. IEEE Computer Society. Google ScholarDigital Library
- Anton Beloglazov, Jemal Abawajy, and Rajkumar Buyya. Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Generation Computer Systems, (0):--, 2011. Google ScholarDigital Library
- Martin Bichler, Thomas Setzer, and Benjamin Speitkamp. Capacity Planning for Virtualized Servers. Presented at Workshop on Information Technologies and Systems (WITS), Milwaukee, Wisconsin, USA, 2006, 2006.Google Scholar
- Damien Borgetto, Georges Da Costa, Jean-Marc Pierson, and Amal Sayah. Energy-Aware Resource Allocation. In Proc. of the Energy Efficient Grids, Clouds and Clusters Workshop (E2GC2), page (electronic medium). IEEE, October 2009.Google Scholar
- Vincent C. Emeakaroha, Pawel Labaj, Michael Maurer, Ivona Brandic, and David P. Kreil. Optimizing bioinformatics workflows for data analysis using cloud management techniques. In The 6th Workshop on Workflows in Support of Large-Scale Science (WORKS11), 2011. Google ScholarDigital Library
- Xiaobo Fan, Wolf dietrich Weber, and Luiz André Barroso. Power provisioning for a warehouse-sized computer. In In Proceedings of ISCA, 2007. Google ScholarDigital Library
- Marko Hoyer, Kiril Schröder, and Wolfgang Nebel. Statistical static capacity management in virtualized data centers supporting fine grained qos specification. In Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking, e-Energy '10, pages 51--60, New York, NY, USA, 2010. ACM. Google ScholarDigital Library
- Markus C. Huebscher and Julie A. McCann. A survey of autonomic computing---degrees, models, and applications. ACM Comput. Surv., 40(3):1--28, 2008. Google ScholarDigital Library
- Sadeka Islam, Jacky Keung, Kevin Lee, and Anna Liu. Empirical prediction models for adaptive resource provisioning in the cloud. Future Generation Computer Systems, 28(1):155--162, 2012. Google ScholarDigital Library
- Peter Johnson and Tony Marker. Data center energy efficiency product profile. Technical report, 2009.Google Scholar
- Gabor Kecskemeti, Gabor Terstyanszky, Peter Kacsuk, and Zsolt Neméth. An approach for virtual appliance distribution for service deployment. Future Gener. Comput. Syst., 27:280--289, March 2011. Google ScholarDigital Library
- Bithika Khargharia, Salim Hariri, and Mazin S. Yousif. Autonomic power and performance management for computing systems. Cluster Computing, 11(2):167--181, 2008. Google ScholarDigital Library
- Haikun Liu, Cheng-Zhong Xu, Hai Jin, Jiayu Gong, and Xiaofei Liao. Performance and energy modeling for live migration of virtual machines. In Proceedings of the 20th international symposium on High performance distributed computing, HPDC '11, pages 171--182, New York, NY, USA, 2011. ACM. Google ScholarDigital Library
- Liang Liu, Hao Wang, Xue Liu, Xing Jin, Wen Bo He, Qing Bo Wang, and Ying Chen. Greencloud: a new architecture for green data center. In Proceedings of the 6th international conference industry session on Autonomic computing and communications industry session, pages 29--38, New York, NY, USA, 2009. Google ScholarDigital Library
- Michael Maurer, Ivona Brandic, Vincent C. Emeakaroha, and Schahram Dustdar. Towards knowledge management in self-adaptable clouds. In IEEE 2010 Fourth International Workshop of Software Engineering for Adaptive Service-Oriented Systems, Miami, USA, 2010. Google ScholarDigital Library
- Michael Maurer, Ivona Brandic, and Rizos Sakellariou. Simulating autonomic sla enactment in clouds using case based reasoning. In ServiceWave 2010, Ghent, Belgium, 2010.Google ScholarCross Ref
- Michael Maurer, Ivona Brandic, and Rizos Sakellariou. Enacting slas in clouds using rules. In Euro-Par 2011, Bordeaux, France, 2011. Google ScholarDigital Library
- M. Mazzucco, D. Dyachuk, and R. Deters. Maximizing cloud providers' revenues via energy aware allocation policies. In CLOUD 2010, pages 131--138, 2010. Google ScholarDigital Library
- Xiaoqiao Meng, Canturk Isci, Jeffrey Kephart, Li Zhang, Eric Bouillet, and Dimitrios Pendarakis. Efficient resource provisioning in compute clouds via vm multiplexing. In Proceeding of the 7th international conference on Autonomic computing, ICAC '10, pages 11--20, New York, NY, USA, 2010. ACM. Google ScholarDigital Library
- Amit Nathani, Sanjay Chaudhary, and Gaurav Somani. Policy based resource allocation in iaas cloud. Future Generation Computer Systems, 28(1):94--103, 2012. Google ScholarDigital Library
- Adrian Paschke and Martin Bichler. Knowledge representation concepts for automated SLA management. Decision Support Systems, 46(1):187--205, 2008. Google ScholarDigital Library
- Vinicius Petrucci, Orlando Loques, and Daniel Mossé. A dynamic optimization model for power and performance management of virtualized clusters. In e-Energy '10, pages 225--233, New York, NY, USA, 2010. ACM. Google ScholarDigital Library
- Jia Rao, Xiangping Bu, Cheng-Zhong Xu, Leyi Wang, and George Yin. Vconf: a reinforcement learning approach to virtual machines auto-configuration. In ICAC '09, pages 137--146, New York, NY, USA, 2009. ACM. Google ScholarDigital Library
- Mark Stillwell, David Schanzenbach, Frederic Vivien, and Henri Casanova. Resource allocation algorithms for virtualized service hosting platforms. Journal of Parallel and Distributed Computing, 70(9):962--974, 2010. Google ScholarDigital Library
- H. Viswanathan, E. K. Lee, I. Rodero, D. Pompili, M. Parashar, and M. Gamell. Energy-aware application-centric vm allocation for hpc workloads. In Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on, pages 890--897, may 2011. Google ScholarDigital Library
- William Voorsluys, James Broberg, and Srikumar Venugopal. Cost of virtual machine live migration in clouds: A performance evaluation.Google Scholar
- Timothy Wood, Prashant Shenoy, Arun Venkataramani, and Mazin Yousif. Sandpiper: Black-box and gray-box resource management for virtual machines. Computer Networks, 53(17):2923--2938, 2009. Google ScholarDigital Library
- Y.O. Yazir, C. Matthews, R. Farahbod, S. Neville, A. Guitouni, S. Ganti, and Y. Coady. Dynamic resource allocation in computing clouds using distributed multiple criteria decision analysis. In Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on, pages 91--98, 2010. Google ScholarDigital Library
Index Terms
- Energy-efficient and SLA-aware management of IaaS clouds
Recommendations
Performance-to-Power Ratio Aware Virtual Machine (VM) Allocation in Energy-Efficient Clouds
CLUSTER '15: Proceedings of the 2015 IEEE International Conference on Cluster ComputingThe last decade witnesses a dramatic advance of cloud computing research and techniques. One of the key faced challenges in this field is how to reduce the massive amount of energy consumption in cloud computing data centers. To address this issue, many ...
Enabling Instantaneous Relocation of Virtual Machines with a Lightweight VMM Extension
CCGRID '10: Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid ComputingWe are developing an efficient resource management system with aggressive virtual machine (VM) relocation among physical nodes in a data center. Existing live migration technology, however, requires a long time to change the execution host of a VM, it ...
Resource-aware virtual machine placement algorithm for IaaS cloud
Cloud computing is an on-demand Internet-based computing service, where computing resources are shared among the users via the Internet and its usage based on the pay-for-use model. Virtualization of computing resources allows the system to use the ...
Comments