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Issue No.11 - November (2011 vol.22)
pp: 1780-1787
Luis Diego Briceño , Colorado State University, Fort Collins
Howard Jay Siegel , Colorado State University, Fort Collins
Anthony A. Maciejewski , Colorado State University, Fort Collins
Mohana Oltikar , Colorado State University, Fort Collins and Hughes Network Systems, LLC.
Jeff Brateman , Colorado State University, Fort Collins and IBM, Austin
Joe White , Colorado State University, Fort Collins and Recondo Technology, Castle Rock
Jonathan R. Martin , Colorado State University, Fort Collins and R.L. Martin & Associates
Keith Knapp , Colorado State University, Fort Collins
This work considers the satellite data processing portion of a space-based weather monitoring system. It uses a heterogeneous distributed processing platform. There is uncertainty in the arrival time of new data sets to be processed, and resource allocation must be robust with respect to this uncertainty. The tasks to be executed by the platform are classified into two broad categories: high priority (e.g., telemetry, tracking, and control), and revenue generating (e.g., data processing and data research). In this environment, the resource allocation of the high-priority tasks must be done before the resource allocation of the revenue generating tasks. A two-part allocation scheme is presented in this research. The goal of first part is to find a resource allocation that minimizes makespan of the high-priority tasks. The robustness for the first part of the mapping is defined as the difference between this time and the expected arrival of the next data set. For the second part, the robustness of the mapping is the difference between the expected arrival time and the time at which the revenue earned is equal to the operating cost. Thus, the heuristics for the second part find a mapping that minimizes the time for the revenue (gained by completing revenue generating tasks) to be equal to the cost. Different resource allocation heuristics are designed and evaluated using simulations, and their performance is compared to a mathematical bound.
Heterogeneous computing, satellite system, robustness, makespan, revenue, and two-part resource allocation.
Luis Diego Briceño, Howard Jay Siegel, Anthony A. Maciejewski, Mohana Oltikar, Jeff Brateman, Joe White, Jonathan R. Martin, Keith Knapp, "Heuristics for Robust Resource Allocation of Satellite Weather Data Processing on a Heterogeneous Parallel System", IEEE Transactions on Parallel & Distributed Systems, vol.22, no. 11, pp. 1780-1787, November 2011, doi:10.1109/TPDS.2011.44
[1] S. Ali, T.D. Braun, H.J. Siegel, A.A. Maciejewski, N. Beck, L. Boloni, M. Maheswaran, A.I. Reuther, J.P. Robertson, M.D. Theys, and B. Yao, "Characterizing Resource Allocation Heuristics for Heterogeneous Computing Systems," Advances in Computers: Parallel, Distributed, and Pervasive Computing, vol. 63, pp. 91-128, Academic Press, 2005.
[2] S. Ali, H.J. Siegel, M. Maheswaran, D. Hensgen, and S. Ali, "Representing Task and Machine Heterogeneities for Heterogeneous Computing Systems," Tamkang J. Science and Eng., special 50th anniversary issue, vol. 3, no. 3, pp. 195-207, Nov. 2000.
[3] S. Ali, A.A. Maciejewski, and H.J. Siegel, "Perspectives on Robust Resource Allocation for Heterogeneous Parallel Systems," Handbook of Parallel Computing: Models, Algorithms, and Applications, S. Rajasekaran and J. Reif, eds., pp. 1-30, Chapman & Hall/CRC Press, 2008.
[4] S. Ali, A.A. Maciejewski, H.J. Siegel, and J.-K. Kim, "Measuring the Robustness of a Resource Allocation," IEEE Trans. Parallel and Distributed Systems, vol. 15, no. 7, pp. 630-641, July 2004.
[5] C. Artigues, J. Billaut, and C. Esswein, "Maximization of Solution Flexibility for Robust Shop Scheduling," European J. Operational Research, vol. 165, no. 2, pp. 314-328, 2005.
[6] L. Barbulescu, A.E. Howe, L.D. Whitley, and M. Roberts, "Trading Places: How to Schedule More in a Multi-Resource Oversubscribed Scheduling Problem System," Proc. Int'l Conf. Automated Planning and Scheduling (ICAPS '04), June 2004.
[7] T.D. Braun, H.J. Siegel, N. Beck, L. Boloni, R.F. Freund, D. Hensgen, M. Maheswaran, A.I. Reuther, J.P. Robertson, M.D. Theys, and B. Yao, "A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems," J. Parallel and Distributed Computing, vol. 61, no. 6, pp. 810-837, June 2001.
[8] R. Cheng, M. Gen, and Y. Tsujimura, "A Tutorial Survey of Job-Shop Scheduling Problems Using Genetic Algorithms—I. Representation," Computers and Industrial Eng., vol. 30, no. 4, pp. 983-997, 1996.
[9] E.G. Coffman, Computer and Job-Shop Scheduling Theory. John Wiley and Sons, 1976.
[10] F.D. Croce, R. Tadei, and G. Volta, "A Genetic Algorithm for the Job Shop Problem," Computers and Operations Research, vol. 22, no. 1, pp. 15-24, 1995.
[11] A.J. Davenport, C. Gefflot, and J.C. Beck, "Slack-Based Techniques for Robust Schedules," Proc. Sixth European Conf. Planning, pp. 7-18, Sept. 2001.
[12] M.K. Dhodi, I. Ahmad, and I. Ahmad, "A Multiprocessor Scheduling Scheme Using Problem-Space Genetic Algorithms," Proc. IEEE Int'l Conf. Evolutionary Computation, pp. 214-219, 1995.
[13] M.M. Eshaghian, Heterogeneous Computing. Artech House, 1996.
[14] D. Fernandez-Baca, "Allocating Modules to Processors in a Distributed System," IEEE Trans. Software Eng., vol. SE-15, no. 11, pp. 1427-1436, Nov. 1989.
[15] I. Foster and C. Kesselman, The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, 1999.
[16] A. Ghafoor and J. Yang, "A Distributed Heterogeneous Supercomputing Management System," Computer, vol. 26, no. 6, pp. 78-86, June 1993.
[17] O.H. Ibarra and C.E. Kim, "Heuristic Algorithms for Scheduling Independent Tasks on Non-Identical Processors," J. ACM, vol. 24, no. 2, pp. 280-289, Apr. 1977.
[18] M. Kafil and I. Ahmad, "Optimal Task Assignment in Heterogeneous Distributed Computing Systems," IEEE Concurrency, vol. 6, no. 3, pp. 42-51, July 1998.
[19] S. Khan and I. Ahmad, "A Cooperative Game Theoretical Technique for Joint Optimization of Energy Consumption and Response Time in Computational Grids," IEEE Trans. Parallel and Distributed Systems, vol. 20, no. 3, pp. 346-360, Mar. 2009.
[20] A. Khokhar, V.K. Prasanna, M.E. Shaaban, and C. Wang, "Heterogeneous Computing: Challenges and Opportunities," Computer, vol. 26, no. 6, pp. 18-27, June 1993.
[21] L.A. Kramer and S.L. Smith, "Maximizing Flexibility: A Retraction Heuristic for Oversubscribed Scheduling Problems," Proc. 18th Int'l Joint Conf. Artificial Intelligence, Aug. 2003.
[22] Y.-K. Kwok and I. Ahmad, "Efficient Scheduling of Arbitrary Task Graphs to Multi-Processors Using a Parallel Genetic Algorithm," J. Parallel and Distributed Computing, vol. 47, no. 1, pp. 58-77, Nov. 1997.
[23] C. Leangsuksun, J. Potter, and S. Scott, "Dynamic Task Mapping Algorithms for a Distributed Heterogeneous Computing Environment," Proc. Fourth IEEE Heterogeneous Computing Workshop (HCW '95), pp. 30-34, Apr. 1995.
[24] M. Maheswaran, S. Ali, H.J. Siegel, D. Hensgen, and R.F. Freund, "Dynamic Mapping of a Class of Independent Tasks onto Heterogeneous Computing Systems," J. Parallel and Distributed Computing, vol. 59, no. 2, pp. 107-121, Nov. 1999.
[25] A.M. Mehta, J. Smith, H.J. Siegel, A.A. Maciejewski, A. Jayaseelan, and B. Ye, "Dynamic Resource Allocation Heuristics that Manage Tradeoff between Makespan and Robustness," J. Supercomputing, Special Issue on Grid Technology, vol. 42, no. 1, pp. 33-58, Jan. 2007.
[26] NESDIS, Nat'l Environmental Satellite Data Information Service (Nesdis), , Mar. 2006.
[27] M. Oltikar, J. Brateman, J. White, J. Martin, K. Knapp, A.A. Maciejewski, and H.J. Siegel, "Robust Resource Allocation in Weather Data Processing Systems," Proc. Eighth Workshop High Performance Scientific and Eng. Computing, pp. 445-454, 2006.
[28] V. Shestak, J. Smith, H.J. Siegel, and A. Maciejewski, "Stochastic Robustness Metric and Its Use for Static Resource Allocations," J. Parallel and Distributed Computing, vol. 68, no. 8, pp. 1157-1173, Aug. 2008.
[29] S. Smith and C.-C. Cheng, "Slack-Based Heuristics for Constraint Satisfaction Scheduling," Proc. 11th Nat'l Conf. Artificial Intelligence, pp. 139-144, 1993.
[30] D. Whitley, "The GENITOR Algorithm and Selective Pressure: Why Rank Based Allocation of Reproductive Trials is Best," Proc. Third Int'l Conf. Genetic Algorithms, pp. 116-121, June 1989.
[31] M. Wu and W. Shu, "Segmented Min-Min: A Static Mapping Algorithm for Meta-Tasks on Heterogeneous Computing Systems," Proc. Ninth Heterogeneous Computing Workshop (HCW '00), pp. 375-385, Mar. 2000.
[32] D. Xu, K. Nahrstedt, and D. Wichadakul, "QoS and Contention-Aware Multi-Resource Reservation," Cluster Computing, vol. 4, no. 2, pp. 95-107, Apr. 2001.
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