The Community for Technology Leaders
RSS Icon
Issue No.07 - July (2009 vol.20)
pp: 953-967
Nirmalya Roy , University of Texas at Austin, Austin
Sajal K. Das , University of Texas at Arlington, Arlington
The Grid is an integrated infrastructure that can play the dual roles of a coordinated resource consumer as well as a donator in distributed computing environments. The enormous growth in the use of mobile and embedded devices in ubiquitous computing environment and their interaction with human beings produces a huge amount of data that need to be processed efficiently anytime anywhere. However, such devices often have limited resources in terms of CPU, storage, battery power, and communication bandwidth. Thus, there is a need to transfer ubiquitous computing application services to more powerful computational resources. In this paper, we investigate the use of the Grid as a candidate for provisioning computational services to applications in ubiquitous computing environments. In particular, we present a competitive model that describes the possible interaction between the competing resources in the Grid Infrastructure as service providers and ubiquitous applications as subscribers. The competition takes place in terms of quality of service (QoS) and cost offered by different Grid Service Providers (GSPs). We also investigate the job allocation of different GSPs by exploiting the noncooperativeness among the strategies. We present the equilibrium behavior of our model facing global competition under stochastic demand and estimate guaranteed QoS assurance level by efficiently satisfying the requirement of ubiquitous application. We have also performed extensive experiments over Distributed Parallel Computing Cluster (DPCC) and studied overall job execution performance of different GSPs under a wide range of QoS parameters using different strategies. Our model and performance evaluation results can serve as a valuable reference for designing appropriate strategies in a practical grid environment.
Ubiquitous computing, grid computing, pervasive devices, price elasticity, stochastic demand, Nash-Equilibrium, Mahalanobis distance, game theory.
Nirmalya Roy, Sajal K. Das, "Enhancing Availability of Grid Computational Services to Ubiquitous Computing Applications", IEEE Transactions on Parallel & Distributed Systems, vol.20, no. 7, pp. 953-967, July 2009, doi:10.1109/TPDS.2009.15
[1] R. El Azouzi , E. Altman , and L. Wynter , “Telecommunications Network Equilibrium with Price and Quality-of-Service Characteristics,” Proc. Int'l Teletraffic Congress (ITC), Sept. 2003.
[2] Y. Amir , B. Awerbuch , A. Barak , R.S. Borgstrom , and A. Keren , “An Opportunity Cost Approach for Job Assignment in a Scalable Computing Cluster,” IEEE Trans. Parallel and Distributed Systems, vol. 11, no. 7, pp.760-768, July 2000.
[3] P. Bellavista , A. Corradi , and C. Stefanelli , “The Ubiquitous Provisioning of Internet Services to Portable Devices,” IEEE Pervasive Computing, vol. 1, no. 3, pp.81-87, July-Sept. 2002.
[4] F. Bernstein and A. Federgruen , “A General Equilibrium Model for Decentralized Supply Chains with Price- and Service-Competition,” /, 2007.
[5] M. Butler , M. Leuschel , S.L. Presti , D. Allsopp , P. Beautement , C. Booth , M. Cusack , and M. Kirton , “Towards a Trust Analysis Framework for Pervasive Computing Scenarios,” Proc. Sixth Int'l Workshop Trust, Privacy, Deception, and Fraud in Agent Societies (AAMAS), 2003.
[6] R. Buyya , “Economic-Based Distributed Resource Management and Scheduling for Grid Computing,” PhD thesis, Monash Univ., Australia,, Apr. 2002.
[7] M. Cannataro and D. Talia , “Towards the Next-Generation Grid: A Pervasive Environment for Knowledge-Based Computing,” Proc. Int'l Conf. Information Technology: Computers and Comm., Apr. 2003.
[8] B. Chun , “Market-Based Cluster Resource Management,” PhD dissertation, Univ. of California at Berkeley, Oct. 2001.
[9] K. Czajkowski , I. Foster , N. Karonis , C. Kesselman , S. Martin , W. Smith , and S. Tuecke , “A Resource Management Architecture for Metacomputing Systems,” Proc. Fourth Int'l Workshop Job Scheduling Strategies for Parallel Processing, Mar. 1998.
[10] I. Foster , C. Kesselman , and S. Tueke , “The Anatomy of the Grid: Enabling Scalable Virtual Organizations,” Int'l J. Supercomputing Applications, 2001.
[11] I. Foster , “The Grid: A New Infrastructure for 21st Century Science,” Physics Today, vol. 55, no. 22, p.42, 2002.
[12] P. Ghosh , N. Roy , S.K. Das , and K. Basu , “A Game Theory Based Pricing Strategy for Job Allocation in Mobile Grids,” Proc. 18th Int'l Parallel and Distributed Processing Symp., Apr. 2004.
[13] P. Ghosh , N. Roy , S.K. Das , and K. Basu , “A Pricing Strategy for Job Allocation in Mobile Grids Using a Non-Cooperative Bargaining Theory Framework,” J. Parallel and Distributed Computing, special issue on design and performance of networks for super, cluster, and grid-computing, A. Zomaya, M. Ould-Khaoua, and H.Sarbazi-Azad, eds., vol.65, no. 11, pp.1366-1383, Nov. 2005.
[14] P. Ghosh , K. Basu , and S.K. Das , “A Game Theory Based Pricing Strategy to Support Single/Multi-Class Job Allocation Schemes for Bandwidth Constrained Distributed Systems,” IEEE Trans. Parallel and Distributed Systems, vol. 18, no. 3, pp.289-306, Mar. 2007.
[15] V. Hingne , A. Joshi , T. Finin , H. Kargupta , and E. Houstis , “Towards a Pervasive Grid,” Proc. 17th Int'l Parallel and Distributed Processing Symp., Apr. 2003.
[16] G. Heiser , F. Lam , and S. Russell , “Resource Management in the Mungi Single-Address-Space Operating System,” Proc. Australasian Computer Science Conf., Feb. 1998.
[17] M. Kumar , B. Shirazi , S.K. Das , M. Singhal , B. Sung , and D. Levine , “Pervasive Information Communities Organization PICO: A Middleware Framework for Pervasive Computing,” IEEE Pervasive Computing, vol. 2, no. 3, pp.72-79, July-Sept. 2003.
[18] Y. Kwok , K. Hwang , and S. Song , “Selfish Grids: Game-Theoretic Modeling and NAS/PSA Benchmark Evaluation,” IEEE Trans. Parallel and Distributed Systems, vol. 18, no. 5, pp.621-636, May 2007.
[19] IEEE 802.11 Technical Report, http://www.ieee802.org11, 2009.
[20] G.V. Laszewski , “Grid Computing: Enabling a Vision for Collaborative Research,” Proc. Conf. Applied Parallel Computing, Third CSC Scientific Meeting, June 2002.
[21] D. Mitra , K.G. Ramakrishnan , and Q. Wang , “Combined Economic Modeling and Traffic Engineering: Joint Optimization of Pricing and Routing in Multi-Service Networks,” Proc. 17th Int'l Teletraffic Congress, 2001.
[22] Mojo-Nation, http:/, June 2001.
[23] G. Owen , Game Theory. second ed., Academic Press, 1982.
[24] N. Nisan , S. London , O. Regev , and N. Camiel , “Globally Distributed Computation over the Internet: The POPCORN Project,” Proc. Int'l Conf. Distributed Computing Systems (ICDCS '98), May 1998.
[25] T. Phan , L. Huang , and C. Dulan , “Challenge: Integrating Mobile Wireless Devices into the Computational Grid,” Proc. Eighth Int'l Conf. Mobile Computing and Networking, Sept. 2002.
[26] J. Rolia , X. Zhu , M. Arlitt , and A. Andrzejak , “Statistical Service Assurances for Applications in Utility Grid Environments,” Proc. Int'l Symp. Modeling, Analysis and Simulation of Computer and Telecomm. Systems, 2002.
[27] N. Roy , S.K. Das , K. Basu , and M. Kumar , “Enhancing Availability of Grid Computational Services to Ubiquitous Computing Applications,” Proc. 19th IEEE Int'l Parallel and Distributed Processing Symp. (IPDPS '05), Apr. 2005.
[28] N. Roy , “Providing Better QoS Assurance to Next Generation Ubiquitous Grid Users,” MS thesis, Univ. of Texas at Arlington, Apr. 2004.
[29] M. Schneps-Schneppe and V.B. Iverson , “Service Level Agreement as an Issue of Teletraffic,” Proc. Int'l Teletraffic Congress (ITC), Sept. 2003.
[30] SETI@home homepage,, 2007.
[31] M. Stonebraker , R. Devine , M. Kornacker , W. Litwin , A. Pfeffer , A. Sah , and C. Staelin , “An Economic Paradigm for Query Processing and Data Migration in Mariposa,” Proc. Third Int'l Conf. Parallel and Distributed Information Systems, Sept. 1994.
[32] C. Waldspurger , T. Hogg , B. Huberman , J. Kephart , and W. Stornetta , “Spawn: A Distributed Computational Economy,” IEEE Trans. Software Eng., vol. 18, no. 2, pp.103-117, Feb. 1992.
[33] T. Simunic , L. Benini , P. Glynn , and G. De Micheli , “Dynamic Power Management for Portable Systems,” Proc. ACM Mobicom, 2000.
[34] L. Benini and G. De Micheli , Dynamic Power Management: Design Techniques and CAD Tools. Kluwer, 1997.
[35] Q. Han , S. Mehrotra , and N. Venkatasubramanian , “Energy Efficient Data Collection in Distributed Sensor Environments,” Proc. 24th IEEE Int'l Conf. Distributed Computing Systems (ICDCS '04), pp.590-597, 2004.
[36] W. Hu , A. Misra , and R. Shorey , “CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks,” Proc. Fourth IEEE Int'l Conf. Pervasive Computing and Comm. (PerCom), pp.190-199, 2006.
[37] S. Jang , D. Park , and J. Lee , “Grid Resource Trade Network: Effective Resource Management Model in Grid Computing,” Proc. Grid and Cooperative Computing Conf. (GCC), 2005.
[38] J.F. Nash, Jr. , “The Bargaining Problem,” Econometrica, vol. 18, no. 2, pp.155-162, Apr. 1950.
[39] J.F. Nash, Jr. , “Non-Cooperative Games,” The Annals of Math., vol. 54, no. 2, pp.286-295, Sept. 1951.
[40] R. Wolski , J.S. Plank , T. Bryan , and J. Brevik , “G-Commerce: Market Formulations Controlling Resource Allocation on the Computational Grid,” Proc. Int'l Parallel and Distributed Processing Symp. (IPDPS), 2001.
40 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool