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A Unified Methodology for Scheduling in Distributed Cyber-Physical Systems

Published:01 August 2012Publication History
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Abstract

A distributed cyber-physical system (DCPS) may receive and induce energy-based interference to and from its environment. This article presents a model and an associated methodology that can be used to (i) schedule tasks in DCPSs to ensure that the thermal effects of the task execution are within acceptable levels, and (ii) verify that a given schedule meets the constraints. The model uses coarse discretization of space and linearity of interference. The methodology involves characterizing the interference of the task execution and fitting it into the model, then using the fitted model to verify a solution or explore the solution space.

References

  1. Adelstein, F., Gupta, S. K. S., Richard III, G. G., and Schwiebert, L. 2005. Fundamentals of Mobile and Pervasive Computing. McGraw-Hill, New York, NY.Google ScholarGoogle Scholar
  2. Arora, A., Dutta, P., Bapat, S., Kulathumani, V., Zhang, H., Naik, V., Mittal, V., Cao, H., Demirbas, M., Gouda, M., Choi, Y., Herman, T., Kulkarni, S., Arumugam, U., Nesterenko, M., Vora, A., and Miyashita, M. 2004. A line in the sand: A wireless sensor network for target detection, classification, and tracking. Comput. Netw. 46, 5, 605--634. Military Communications Systems and Technologies. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Banerjee, A., Kandula, S., Mukherjee, T., and Gupta, S. K. S. 2010. BAND-AiDe: A tool for cyber-physical oriented analysis and design of body area networks and devices. ACM Trans. Embed. Comput. Syst., Special Issue on Wireless Health Systems. Forthcoming. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Bash, C. and Forman, G. 2007. HPL-2007-62 cool job allocation: Measuring the power savings of placing jobs at cooling-efficient locations in the data center. Tech. rep. HPL-2007-62, HP Laboratories Palo Alto, CA.Google ScholarGoogle Scholar
  5. Bujorianu, M. C., Bujorianu, M. L., and Barringer, H. 2009. A unifying specification logic for cyber-physical systems. In Proceedings of the 17th Mediterranean Conference on Control and Automation (MED’09). IEEE Computer Society, Los Alamitos, CA, 1166--1171. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Donald, J. and Martonosi, M. 2006. Techniques for multicore thermal management: Classification and new exploration. SIGARCH Comput. Archit. News 34, 2, 78--88. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Dutta, P., Grimmer, M., Arora, A., Bibyk, S., and Culler, D. 2005. Design of a wireless sensor network platform for detecting rare, random, and ephemeral events. In Proceedings of the 4th International Conference on Information Processing in Sensor Networks (IPSN’05). Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Fulford-Jones, T. R. F., Wei, G.-Y., and Welsh, M. 2004. A portable, low-power, wireless two-lead ekg system. In Proceedings of the 26th IEEE EMBS Annual International Conference.Google ScholarGoogle Scholar
  9. Gill, C. D. and Niehaus, D. 2006. Towards system software platforms for cyber-physical systems (Position Paper). In Proceedings of the NSF Cyber-Physical Systems Workshop.Google ScholarGoogle Scholar
  10. Ilic, M., Xie, L., Khan, U., and Moura, J. 2008. Modeling future cyber-physical energy systems. In Proceedings of the IEEE Power and Energy Society General Meeting---Conversion and Delivery of Electrical Energy in the 21st Century. 1--9.Google ScholarGoogle Scholar
  11. Jiang, W., Xiong, G., and Ding, X. 2008. Energy-saving service scheduling for low-end cyber-physical systems. In Proceedings of the 9th International Conference for Young Computer Scientists (ICYCS’08). 1064--1069. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Lee, E. A. 2006. Cyber-physical systems: Are computing foundations adequate? (Position Paper). In Proceedings of the NSF Cyber-Physical Systems Workshop.Google ScholarGoogle Scholar
  13. Lee, E. A. 2008. Cyber physical systems: Design challenges. In Proceedings of the 11th IEEE Symposium on Object-Oriented Real-Time Distributed Computing (ISORC’08). IEEE Computer Society, Los Alamitos, CA. 363--369. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Moore, J., Chase, J., and Ranganathan, P. 2006. Weatherman: Automated, online and predictive thermal mapping and management for data centers. In Proceedings of the IEEE International Conference on Autonomic Computing (ICAC’06). 155--164. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Mukherjee, T. and Gupta, S. K. S. 2009. CRET: A crisis response evaluation tool to improve crisis preparednesss. In Proceedings of the International Conference on Technologies for Homeland Security.Google ScholarGoogle Scholar
  16. Mukherjee, T., Varsamopoulos, G., Gupta, S. K. S., and Rungta, S. 2007. Measurement-based power profiling of data center equipment. In Proceedings of the IEEE Conference on Clustered and Grid Computing (Cluster’07), Workshop on Green Computing (GreenCom’07). Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Mukherjee, T., Banerjee, A., Varsamopoulos, G., Gupta, S. K. S., and Rungta, S. 2009. Spatio-temporal thermal-aware job scheduling to minimize energy consumption in virtualized heterogeneous data centers. Comput. Netw. 53, 17, 2888--2904. Virtualized Data Centers. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Pinedo, M. L. 2008. Scheduling: Theory, Algorithms, and Systems, 3rd Ed. Springer, Berlin, Chapter 2. Deterministic Models: Preliminaries, 13--19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Porter, J., Karsai, G., and Sztipanovits, J. 2009. Towards a time-triggered schedule calculation tool to support model-based embedded software design. In Proceedings of the 7th ACM International Conference on Embedded Software (EMSOFT’09). ACM, New York, NY, 167--176. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Schwiebert, L., Gupta, S. K. S., and Weinmann, J. 2001. Research challenges in wireless networks of biomedical sensors. In Proceedings of the 7th Annual International Conference on Mobile Computing and Networking (MobiCom’01). ACM, New York, NY, 151--165. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Sentilles, S., Vulgarakis, A., TomášBureš, Carlson, J., and Crnković, I. 2008. A component model for control-intensive distributed embedded systems. In Proceedings of the 11th International Symposium on Component-Based Software Engineering (CBSE’08). 310--317. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Sharma, R. K., Bash, C. E., and Patel, C. D. 2002. Dimensionless parameters for evaluation of thermal design and performance of large scale data centers. In Proceedings of the American Institute of Aeronautics and Astronautics (AIAA). 3091.Google ScholarGoogle Scholar
  23. Springer, R., Lowenthal, D. K., Rountree, B., and Freeh, V. W. 2006. Minimizing execution time in MPI programs on an energy-constrained, power-scalable cluster. In Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP’06). 230--238. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Sun, Y., McMillin, B., Liu, X. F., and Cape, D. 2007. Verifying noninterference in a cyber-physical system the advanced electric power grid. In Proceedings of the 7th International Conference on Quality Software (QSIC’07). IEEE Computer Society, Los Alamitos, CA, 363--369. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Sztipanovits, J. 2007. Composition of cyber-physical systems. In Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS’07). 3--6. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Tan, Y., Vuran, M. C., and Goddard, S. 2009. Spatio-temporal event model for cyber-physical systems. In Proceedings of the 29th IEEE International Conference on Distributed Computing Systems Workshops (ICDCS Workshops’09). IEEE Computer Society, Los Alamitos, CA, 44--50. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Tang, Q., Tummala, N., Gupta, S. K. S., and Schwiebert, L. 2005. Communication scheduling to minimize thermal effects of implanted biosensor networks in homogeneous tissue. IEEE Trans. Biomed. Eng. 52, 7, 1285--1294.Google ScholarGoogle ScholarCross RefCross Ref
  28. Tang, Q., Mukherjee, T., Gupta, S. K. S., and Cayton, P. 2006. Sensor-based fast thermal evaluation model for energy efficient high-performance datacenters. In Proceedings of the International Conference on Intelligent Sensing and Informal Processing (ICISIP’06). 203--208.Google ScholarGoogle Scholar
  29. Tang, Q., Gupta, S. K. S., and Varsamopoulos, G. 2007. Thermal-aware task scheduling for data centers through minimizing heat recirculation. In Proceedings of the IEEE Cluster Conference. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Tang, Q., Varsamopoulos, G., and Gupta, S. K. S. 2008. Thermal-aware task scheduling for data centers through minimizing peak inlet temperature. IEEE Trans. Parallel Distrib. Syst., Special Issue on Power-Aware Parallel and Distributed Systems (TPDS/PAPADS) 19, 11, 1458--1472. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Wolf, W. 2009. Cyber-physical systems. Computer 42, 3, 88--89. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Xue, C., Xing, G., Yuan, Z., Shao, Z., and Sha, E. 2009. Joint sleep scheduling and mode assignment in wireless cyber-physical systems. In Proceedings of the 29th IEEE International Conference on Distributed Computing Systems Workshops (ICDCS Workshops’09). 1--6. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Zhang, F., Szwaykowska, K., Wolf, W., and Mooney, V. 2008. Task scheduling for control oriented requirements for cyber-physical systems. In Proceedings of the Real-Time Systems Symposium. 47--56. Google ScholarGoogle ScholarDigital LibraryDigital Library

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