An autonomic provisioning framework for outsourcing data center based on virtual appliances

As outsourcing data centers emerge to host applications and services from many different organizations, it is critical for data center owners to isolate different applications while dynamically and optimally allocate sharable resources among them. To address this issue, we propose a virtual-appliance-based autonomic resource provisioning framework for large virtualized data centers. We present the architecture of the data center with enriched autonomic features. We define a non-linear constrained optimization model for dynamic resource provisioning and present a novel analytic solution. Key factors, including virtualization overhead and reconfiguration delay, are incorporated into the model. Experimental results based on a prototype demonstrate that the system-level performance has been greatly improved by taking advantage of fine-grained server consolidation, and the whole system exhibits flexible adaptation in failure scenarios. Experiments with the impact of switching delay also show the efficiency of the framework due to significantly reduced provisioning time.

[1]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[2]  Rajarshi Das,et al.  Towards Commercialization of Utility-based Resource Allocation , 2006, 2006 IEEE International Conference on Autonomic Computing.

[3]  Dongyan Xu,et al.  Autonomic Live Adaptation of Virtual Computational Environments in a Multi-Domain Infrastructure , 2006, 2006 IEEE International Conference on Autonomic Computing.

[4]  Segev Wasserkrug,et al.  Autonomic self-optimization according to business objectives , 2004 .

[5]  Gerald Tesauro,et al.  Online Resource Allocation Using Decompositional Reinforcement Learning , 2005, AAAI.

[6]  Virgílio A. F. Almeida,et al.  Resource Management in the Autonomic Service-Oriented Architecture , 2006, 2006 IEEE International Conference on Autonomic Computing.

[7]  Jeffrey O. Kephart,et al.  An architectural approach to autonomic computing , 2004 .

[8]  Jin Chen,et al.  Autonomic Provisioning of Backend Databases in Dynamic Content Web Servers , 2006, 2006 IEEE International Conference on Autonomic Computing.

[9]  Rajarshi Das,et al.  Utility-Function-Driven Resource Allocation in Autonomic Systems , 2005, Second International Conference on Autonomic Computing (ICAC'05).

[10]  Franck Cappello,et al.  Scalability Comparison of Four Host Virtualization Tools , 2007, Journal of Grid Computing.

[11]  Asser N. Tantawi,et al.  Dynamic placement for clustered web applications , 2006, WWW '06.

[12]  Asser N. Tantawi,et al.  Experience with Collaborating Managers: Node Group Manager and Provisioning Manager , 2005, ICAC.

[13]  Wei Jin,et al.  USENIX Association Proceedings of USITS ’ 03 : 4 th USENIX Symposium on Internet Technologies and Systems , 2003 .

[14]  Cristian Lumezanu,et al.  Utility Optimization for Event-Driven Distributed Infrastructures , 2006, 26th IEEE International Conference on Distributed Computing Systems (ICDCS'06).

[15]  Natarajan Gautam,et al.  Dynamic resource allocation of shared data centers supporting multiclass requests , 2004, International Conference on Autonomic Computing, 2004. Proceedings..

[16]  Carl A. Waldspurger,et al.  Memory resource management in VMware ESX server , 2002, OSDI '02.

[17]  Tal Garfinkel,et al.  Virtual machine monitors: current technology and future trends , 2005, Computer.

[18]  Yves Crama,et al.  Local Search in Combinatorial Optimization , 2018, Artificial Neural Networks.

[19]  Daniel A. Menascé,et al.  Resource Allocation for Autonomic Data Centers using Analytic Performance Models , 2005, Second International Conference on Autonomic Computing (ICAC'05).

[20]  Suresh K. Nair,et al.  Near optimal solutions for product line design and selection: beam search heuristics , 1995 .

[21]  Segev Wasserkrug,et al.  Autonomic self-optimization according to business objectives , 2004, International Conference on Autonomic Computing, 2004. Proceedings..

[22]  Rajarshi Das,et al.  A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation , 2006, 2006 IEEE International Conference on Autonomic Computing.

[23]  Martin Arlitt,et al.  A workload characterization study of the 1998 World Cup Web site , 2000, IEEE Netw..

[24]  Steve R. White,et al.  Unity: experiences with a prototype autonomic computing system , 2004 .

[25]  Prashant J. Shenoy,et al.  Agile dynamic provisioning of multi-tier Internet applications , 2008, TAAS.

[26]  Gang Wang,et al.  Appliance-Based Autonomic Provisioning Framework for Virtualized Outsourcing Data Center , 2007, Fourth International Conference on Autonomic Computing (ICAC'07).

[27]  Prashant J. Shenoy,et al.  Dynamic Provisioning of Multi-tier Internet Applications , 2005, Second International Conference on Autonomic Computing (ICAC'05).

[28]  J. McKenna A generalization of little's law to moments of queue lengths and waiting times in closed, product-form queueing networks , 1988, Journal of Applied Probability.

[29]  Rajarshi Das,et al.  Utility functions in autonomic systems , 2004, International Conference on Autonomic Computing, 2004. Proceedings..

[30]  Franck Cappello,et al.  Selecting A Virtualization System For Grid/P2P Large Scale Emulation , 2006 .

[31]  S. Ranjan,et al.  QoS-driven server migration for Internet data centers , 2002, IEEE 2002 Tenth IEEE International Workshop on Quality of Service (Cat. No.02EX564).

[32]  James McKenna OF QUEUE LENGTHS AND WAITING TIMES IN CLOSED, PRODUCT-FORM QUEUEING NETWORKS , 1989 .

[33]  Prashant J. Shenoy,et al.  Dynamic resource allocation for shared data centers using online measurements , 2003, IWQoS'03.

[34]  Michael D. Vose,et al.  The simple genetic algorithm - foundations and theory , 1999, Complex adaptive systems.

[35]  Daniel A. Menascé,et al.  Autonomic Virtualized Environments , 2006, International Conference on Autonomic and Autonomous Systems (ICAS'06).