Cost-Efficient Virtual Server Provisioning and Selection in distributed Data Centers

In this paper, we study a Virtual Server Provisioning and Selection (VSPS) problem in distributed Data Centers (DCs) with the objective of minimizing the total operational cost while meeting the service response time requirement.We aim to develop general algorithms for the VSPS problem without assuming a particular queueing model for service processing in each DC. First, we present a Mixed Integer Linear Programming (MILP) formulation. Then we present a 3-step optimization framework, under which we develop a polynomial-time ln(N)-approximation algorithm (where N is the number of clients) along with a post-optimization procedure for performance improvement. We also show this problem is NP-hard to approximate and is not possible to obtain a better approximation ratio unless NP has TIME(nO(log log n)) deterministic time algorithms. In addition, we present an effective heuristic algorithm that jointly obtains the VS provisioning and selection solutions. Extensive simulation results are presented to justify effectiveness of the proposed algorithms.

[1]  Philip S. Yu,et al.  Geographic load balancing for scalable distributed Web systems , 2000, Proceedings 8th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (Cat. No.PR00728).

[2]  T. V. Lakshman,et al.  Network aware resource allocation in distributed clouds , 2012, 2012 Proceedings IEEE INFOCOM.

[3]  Patrick Wendell,et al.  DONAR: decentralized server selection for cloud services , 2010, SIGCOMM '10.

[4]  Hanif D. Sherali,et al.  Linear Programming and Network Flows , 1977 .

[5]  Maria Kihl,et al.  Web server performance modeling using an M/G/1/K*PS queue , 2003, 10th International Conference on Telecommunications, 2003. ICT 2003..

[6]  Carl M. Harris,et al.  Fundamentals of queueing theory , 1975 .

[7]  Enrico Gregori,et al.  Load distribution among replicated Web servers: a QoS-based approach , 2000, PERV.

[8]  Xue Liu,et al.  Minimizing Electricity Cost: Optimization of Distributed Internet Data Centers in a Multi-Electricity-Market Environment , 2010, 2010 Proceedings IEEE INFOCOM.

[9]  Xue Liu,et al.  MEC-IDC: joint load balancing and power control for distributed Internet Data Centers , 2010, ICCPS '10.

[10]  Rajesh Gupta,et al.  Energy Efficient Geographical Load Balancing via Dynamic Deferral of Workload , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[11]  Ralf Steinmetz,et al.  Modelling the Internet Delay Space Based on Geographical Locations , 2009, 2009 17th Euromicro International Conference on Parallel, Distributed and Network-based Processing.