A virtual resource placement service

Server, storage, and network virtualization and the growing adoption of cloud computing has expanded both the complexity and the value of intelligent allocation and management of data center resources. Resource allocation in a cloud environment is of fundamental importance. There are many competing goals, with differing priorities, that contribute to optimizing virtual resource allocation and placement including performance, reliability, security, energy, etc. We have developed an open extensible architecture to provide placement recommendations which allows for different independently developed Domain Managers to provide input/advice on placement. We have further developed the means to orchestrate the placement, ensuring that the required configuration actions be enacted both before and after the migration of the virtual machine. This paper explores the topic of providing a core placement calculation and orchestration architecture to facilitate management of workload demands in a cloud environment. We describe this architecture for placement services and orchestration, and present some results from a prototype implementation.

[1]  Eli M. Dow,et al.  Leveraging virtualization to optimize high-availability system configurations , 2008, IBM Syst. J..

[2]  Fumio Machida,et al.  Redundant virtual machine placement for fault-tolerant consolidated server clusters , 2010, 2010 IEEE Network Operations and Management Symposium - NOMS 2010.

[3]  Jeffrey O. Kephart,et al.  Runtime Demand Estimation for effective dynamic resource management , 2010, 2010 IEEE Network Operations and Management Symposium - NOMS 2010.

[4]  Nagarajan Kandasamy,et al.  Power and performance management of virtualized computing environments via lookahead control , 2008, 2008 International Conference on Autonomic Computing.

[5]  Aniruddha S. Gokhale,et al.  Middleware for Resource-Aware Deployment and Configuration of Fault-Tolerant Real-time Systems , 2010, 2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium.

[6]  Borja Sotomayor,et al.  Virtual Infrastructure Management in Private and Hybrid Clouds , 2009, IEEE Internet Computing.

[7]  Jean-Marc Menaud,et al.  Autonomic virtual resource management for service hosting platforms , 2009, 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing.

[8]  Jeffrey O. Kephart,et al.  Coordinated management of power usage and runtime performance , 2008, NOMS 2008 - 2008 IEEE Network Operations and Management Symposium.

[9]  Jordi Torres,et al.  Enabling Resource Sharing between Transactional and Batch Workloads Using Dynamic Application Placement , 2008, Middleware.

[10]  Liana L. Fong,et al.  Duality of virtualization: simplification and complexity , 2008, OPSR.

[11]  Jeffrey O. Kephart,et al.  Multi-aspect hardware management in enterprise server consolidation , 2010, 2010 IEEE Network Operations and Management Symposium - NOMS 2010.

[12]  Malgorzata Steinder,et al.  Server virtualization in autonomic management of heterogeneous workloads , 2007, 2007 10th IFIP/IEEE International Symposium on Integrated Network Management.