Anshul Rai
ABSTRACT
Resource allocation is an integral, evolving part of many data center management problems such as virtual machine placement in data centers, network virtualization, and multi-path network routing. Since the problems are inherently NP-Hard, most existing systems use custom-designed heuristics to find a suitable solution. However, such heuristics are often rigid, making it difficult to extend them as requirements change.
In this paper, we present a novel approach to resource allocation that permits the problem specification to evolve with ease. We have built Wrasse, a generic and extensible tool that cloud environments can use to solve their specific allocation problem. Wrasse provides a simple yet expressive specification language that captures a wide range of resource allocation problems. At the back-end, it leverages the power of GPUs to provide solutions to the allocation problems in a fast and timely manner. We show the extensibility of Wrasse by expressing several allocation problems in its specification language. Our experiments show that Wrasse's solution quality is as good as with heuristics, and sometimes even better, while maintaining good performance. In one case, Wrasse packed 71% more instances than a custom heuristic.
- The AMPL modeling language. http://www.ampl.com.Google Scholar
- Windows Azure. http://bit.ly/Nc0UkR.Google Scholar
- M. Al-Fares, A. Loukissas, and A. Vahdat. A Scalable, Commodity Data Center Network Architecture. In Proceedings of the Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM), Seattle, WA, Aug. 2008. Google ScholarDigital Library
- Anatomy of an Amazon EC2 Resource ID. http://bit.ly/Nc0V8B.Google Scholar
- K. R. Apt and M. G. Wallace. Constraint Logic Programming using ECLiPSe. Cambridge University Press, 2007. Google ScholarDigital Library
- H. Ballani, P. Costa, T. Karagiannis, and A. Rowstron. Towards Predictable Data Center Networks. In Proceedings of the Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM), Toronto, Canada, Aug. 2011. Google ScholarDigital Library
- T. Benson, A. Akella, A. Shaikh, and S. Sahu. CloudNaaS: A Cloud Networking Platform for Enterprise Applications. In Proceedings of the ACM Symposium on Cloud Computing (SOCC), 2011. Google ScholarDigital Library
- R. Chandra, S. Karanth, T. Moscibroda, V. Navda, J. Padhye, R. Ramjee, and L. Ravindranath. Dircast: A practical and efficient Wi-Fi multicast system. In Proceedings of the International Conference on Network Protocols (ICNP), Oct. 2008.Google Scholar
- E. G. Coffman, M. R. Garey, and D. S. Johnson. Approximation algorithms for bin packing: a survey". Approximation algorithms for NP-hard problems, 1997. Google ScholarDigital Library
- L. de Moura and N. Bjørner. Z3: An Efficient SMT Solver. In Proceedings of the International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 2008. Google ScholarDigital Library
- L. Epstein and A. Levin. On bin-packing with conflicts. In Proceedings of the 4th International Workshop on Approximation and Online Algorithms, 2006. Google ScholarDigital Library
- M. R. Garey and D. S. Johnson. Computers and Intractability: A guide to the theory of NP completness. W. H. Freeman and Company, 1979. Google ScholarDigital Library
- C. Guo, G. Lu, H. J. Wang, S. Yang, C. Kong, P. Sun, W. Wu, and Y. Zhang. SecondNet: A Data Center Network Virtualization Architecture with Bandwidth Guarantees. In Proceedings of the International Conference on emerging Networking EXperiments and Technologies (CoNEXT), 2010. Google ScholarDigital Library
- Hadoop Rack-Aware Replica Placement. http://bit.ly/Nc0V8F.Google Scholar
- S. Han, K. Jang, K. Park, and S. Moon. PacketShader: a GPU-accelerated Software Router. In Proceedings of the Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM), New Delhi, India, Aug. 2010. Google ScholarDigital Library
- K. Jang, S. Han, S. Han, S. Moon, and K. Park. SSLShader: Cheap SSL Acceleration with Commodity Processors. In Proceedings of the 8th Symposium on Networked Systems Design and Implementation (NSDI), Boston, MA, Mar. 2011. Google ScholarDigital Library
- G. Lee, N. Tolia, P. Ranganathan, and R. H. Katz. Topology-Aware Resource Allocation for Data Intensive Workloads. In Proceedings of the Asia-Pacific Workshop on Systems (APSys), 2010. Google ScholarDigital Library
- S. Lee, R. Panigrahy, V. Prabhakaran, V. Ramasubramanian, K. Talwar, and L. Uyeda. Validating Heuristics for Virtual Machines Consolidation. Technical Report MSR-TR-2011-9, Microsoft Research, 2011.Google Scholar
- C. Liu, L. Ren, B. Loo, Y. Mao, and P. Basu. Cologne: A Declarative Distributed Constraint Optimization Platform. In Proceedings of the International Conference on Very Large Databases (VLDB), 2012. Google ScholarDigital Library
- Microsoft Assessment and Planning Toolkit. http://www.microsoft.com/map/.Google Scholar
- Microsoft System Center Virtual Machine Manager. http://bit.ly/Nc0V8v.Google Scholar
- J. Mudigonda, P. Yalagandula, M. Al-Fares, and J. Mogul. SPAIN: COTS Data-Center Ethernet for Multipathing over Arbitrary Topologies. In Proceedings of the 7th Symposium on Networked Systems Design and Implementation (NSDI), San Jose, CA, Apr. 2010. Google ScholarDigital Library
- S. Narain, G. Levin, S. Malik, and V. Kaul. Declarative Infrastructure Configuration Synthesis and Debugging. Journal of Network Systems Management, 16, Sept. 2008. Google ScholarDigital Library
- R. S. Peterson and E. G. Sirer. Antfarm: Efficient Content Distribution with Managed Swarms. In Proceedings of the 6th Symposium on Networked Systems Design and Implementation (NSDI), Boston, MA, Apr. 2009. Google ScholarDigital Library
- M. Stilwell, D. Schanzenbach, F. Vivien, and H. Casanova. Resource Allocation Algorithms for Virtualized Service Hosting Platforms. Parallel and Distributed Computing, 2010. Google ScholarDigital Library
- Y.-W. E. Sung, S. G. Rao, G. G. Xie, and D. A. Maltz. Towards systematic design of enterprise networks. In Proceedings of the International Conference on emerging Networking EXperiments and Technologies (CoNEXT), 2008. Google ScholarDigital Library
- E. Torlak and D. Jackson. Kodkod: A Relational Model Finder. Tools and Algorithms for Construction and Analysis of Systems. In Proceedings of the International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 2007. Google ScholarDigital Library
- Q. Yin, A. Schuepbach, J. Cappos, A. Baumann, and T. Roscoe. Rhizoma: a runtime for self-deploying, self-managing overlays. In Proceedings of the International Middleware Conference (Middleware), 2009. Google ScholarDigital Library
- M. Yu, Y. Yi, J. Rexford, and M. Chiang. Rethinking Virtual Network Embedding: Substrate Support for Path Splitting and Migration. 2008.Google Scholar
Index Terms
- Generalized resource allocation for the cloud
Recommendations
Policy based resource allocation in IaaS cloud
In present scenario, most of the Infrastructure as a Service (IaaS) clouds use simple resource allocation policies like immediate and best effort. Immediate allocation policy allocates the resources if available, otherwise the request is rejected. Best-...
Cloud resource allocation schemes: review, taxonomy, and opportunities
Cloud computing has emerged as a popular computing model to process data and execute computationally intensive applications in a pay-as-you-go manner. Due to the ever-increasing demand for cloud-based applications, it is becoming difficult to ...
Resource reconstruction algorithms for on-demand allocation in virtual computing resource pool
Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the idea of resource virtualization and ...
Comments