QoS-aware SLA-based Advanced Reservation of Infrastructure as a Service

Cloud computing effectively implements the vision of utility computing by employing a pay-as-you-go cost model and allowing on-demand (re-)leasing of IT resources. Small or medium-sized Infrastructure-as-a-Service providers, however, find it challenging to satisfy all requests immediately due to their limited resource capacity. In that situation, both providers and customers may benefit greatly from advanced reservation of virtual resources, i.e. virtual machines. In our work, we assume SLA-based resource requests and introduce an advanced reservation methodology during SLA negotiation by using computational geometry. Thereby, we are able to verify, record and manage the infrastructure resources efficiently. Based on that model, service providers can easily verify the available capacity for satisfying the customer's Quality-of-Service requirements. Furthermore, we introduce flexible alternative counter-offers, when the service provider lacks resources. Therefore, our mechanism increases the utilization of the resources and attempts to satisfy as many customers as possible.

[1]  Raouf Boutaba,et al.  Cloud computing: state-of-the-art and research challenges , 2010, Journal of Internet Services and Applications.

[2]  Borja Sotomayor,et al.  Resource Leasing and the Art of Suspending Virtual Machines , 2009, 2009 11th IEEE International Conference on High Performance Computing and Communications.

[3]  George N. Rouskas,et al.  Efficient resource management using advance reservations for heterogeneous Grids , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[4]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[5]  Chunming Qiao,et al.  Efficient burst scheduling algorithms in optical burst-switched networks using geometric techniques , 2004, IEEE Journal on Selected Areas in Communications.

[6]  Thomas Röblitz,et al.  SLA-based Planning for Multi-domain Infrastructure as a Service , 2011, CLOSER.

[7]  D. M. Hutton,et al.  Cloud Computing: Principles, Systems and Applications , 2011 .

[8]  Mark de Berg,et al.  Computational Geometry: Algorithms and Applications, Second Edition , 2000 .

[9]  F. Frances Yao,et al.  Computational Geometry , 1991, Handbook of Theoretical Computer Science, Volume A: Algorithms and Complexity.

[10]  Rajkumar Buyya,et al.  A Negotiation Mechanism for Advance Resource Reservations Using the Alternate Offers Protocol , 2008, 2008 16th Interntional Workshop on Quality of Service.

[11]  Lars-Olof Burchard,et al.  Analysis of data structures for admission control of advance reservation requests , 2005, IEEE Transactions on Knowledge and Data Engineering.

[12]  Brian J. Watson,et al.  Autonomic Virtual Machine Placement in the Data Center , 2008 .

[13]  Jean-Marc Menaud,et al.  SLA-Aware Virtual Resource Management for Cloud Infrastructures , 2009, 2009 Ninth IEEE International Conference on Computer and Information Technology.

[14]  Rajkumar Buyya,et al.  SLA-Based Advance Reservations with Flexible and Adaptive Time QoS Parameters , 2007, ICSOC.

[15]  Burkhard Stiller,et al.  Investigations of an SLA Support System for Cloud Computing (SLACC) , 2011, Prax. Inf.verarb. Kommun..

[16]  María Blanca Caminero,et al.  Flexible Advance-reservation (FAR) for Clouds , 2011, CLOSER.

[17]  Eduardo Huedo,et al.  Evaluation of a Utility Computing Model Based on the Federation of Grid Infrastructures , 2007, Euro-Par.