Fairness, stability and optimality of adaptive multiagent systems: Interaction through resource sharing

IEEE Transactions on Automation Science and Engineering

Volumn 7, Issue 3, 2010, Pages 427-439

  Lee, Seokcheon ^a  

^a SCHOOL OF INDUSTRIAL ENGINEERING   (United States)

Author keywords

Adaptive multiagent systems; algorithm selection; fairness; optimality; resource sharing; stability

Indexed keywords

ADAPTIVE MULTIAGENT SYSTEMS; ALGORITHM SELECTION; INDIVIDUAL AGENT; OPTIMALITY; RESOURCE SHARING; SOURCE OF INSTABILITY;

ALGORITHMS; MULTI AGENT SYSTEMS; OPTIMIZATION; RESOURCE VALUATION;

SYSTEM STABILITY;

EID: 77954424927     PISSN: 15455955     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASE.2009.2035520     Document Type: Article

References (53)

1. B. A. Huberman and T. Hogg, "The behavior of computational ecologies," in The Ecology of Computation, B. A. Huberman, Ed. Amsterdam, The Netherlands: North-Holland, 1988, pp. 77-115.
2. J. O. Kephart, T. Hogg, and B. A. Huberman, "Dynamics of computational ecosystems," Phys. Rev. A, vol.40, no.1, pp. 404-421, 1989.
3. N. Glance, T. Hogg, and B. A. Huberman, "Computational ecosystems in a changing environment," Int. J. Mod. Phys., vol.2, no.3, pp. 735-753, 1991.
4. T. Hogg and B. A. Huberman, "Controlling chaos in distributed systems," IEEE Trans. Syst., Man, Cybern., vol.21, pp. 1325-1332, 1991.
5. B. A. Huberman and T. Hogg, "The emergence of computational ecologies," in 1992 Lectures in Complex Systems, L. Nadel and D. L. Stein, Eds. Reading, MA: Addison-Wesley, 1993, pp. 185-205.
6. J. Thomas and K. Sycara, "Heterogeneity, stability, and efficiency in distributed systems," in Proc. 3rd Int. Conf. Multi Agent Syst., 1998, pp. 293-300.
7. H. Lee, V. Padmanabhan, and S. Whang, "Information distortion in a supply chain: The bullwhip effect," Manage. Sci., vol.43, no.4, pp. 546-558, 1997.
8. F. Chen, Z. Drezner, J. K. Ryan, and D. Simchi-Levi, "Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information," Manage. Sci., vol.46, no.3, pp. 436-443, 2000.
9. H. Lee and S. Whang, "Information sharing in supply chain," Int. Technol. Manage., vol. 20, no. 3/4, pp. 373-387, 2000.
10. M. L. Fisher, "What is the right supply chain for your product?," Harvard Business Rev., vol.75, no.2, pp. 105-116, 1997.
11. G. W. Tan and B. Wang, "The relationship between product nature, demand patterns and information sharing strategies," in Proc. 22nd Int. Conf. Inf. Syst., 2001, pp. 938-947.
12. Y. Li and G. W. Tan, "Information sharing in a supply chain with dynamic consumer demand pattern," in Proc. 37th Annu. Hawaii Int. Conf. Syst. Sci., 2004, pp. 1-9.
13. I. Foster and C. Kesselman, The Grid: Blueprint for a New Computing Infrastructure. San Francisco, CA: Morgan Kaufmann, 1999.
14. I. Foster, C. Kesselman, and S. Tuecke, "The anatomy of the grid: Enabling scalable virtual organizations," Int. J. High Performance Comput. Appl., vol.15, no.3, pp. 200-222, 2001. (Pubitemid 33099013)
15. I. Foster, "The grid: A new infrastructure for 21st century science," Physics Today, vol.55, no.2, pp. 2-47, 2002.
16. I. Foster, C. Kesselman, J. M. Nick, and S. Tuecke, "Grid services for distributed system integration," IEEE Computer, vol.35, no.6, pp. 37-46, 2002.
17. I. Foster, "Globus toolkit version 4: Software for service-oriented systems," J. Comput. Sci. Technol., vol.21, no.4, pp. 513-520, 2006.
18. J. Liu, K. Lin, W. Shih, A. Yu, J. Z. Chung, and W. Zhao, "Algorithms for scheduling imprecise computations," in Foundations of Real-Time Computing: Scheduling and Resource Management, A. Tilborg and G. Koob, Eds. Reading, MA: Kluwer-Academic, 1991, pp. 203-250.
19. H. El-Rewini, H. H. Ali, and T. Lewis, "Task scheduling in multiprocessor systems," Computer, vol.28, no.12, pp. 27-37, 1995.
20. Y. K. Kwok and I. Ahmad, "Static scheduling algorithms for allocating directed task graphs to multiprocessors," ACMComputing Surveys, vol.31, no.4, pp. 406-471, 1999.
21. C. Lu, J. Stankovic, G. Tao, and S. H. Son, "Feedback control real-time scheduling: Framework, modeling, and algorithms," Real-Time Systems J., vol. 23, no. 1/2, pp. 85-126, 2002.
22. V. S. Adve and M. K. Vernon, "Parallel program performance prediction using deterministic task graph analysis," ACM Trans. Comput. Syst., vol.22, no.1, pp. 94-136, 2004.
23. T. Hagras and J. Janecek, "A high performance, low complexity algorithm for compile-time task scheduling in heterogeneous systems," Parallel Comput., vol.31, no.7, pp. 653-670, 2005.
24. J. Yu and R. Buyya, "A taxonomy of scientific workflow systems for grid computing," SIGMOD Record, vol.34, no.3, pp. 44-49, 2005. (Pubitemid 43152531)
25. F. Dong and S. G. Akl, "Scheduling algorithms for grid computing: State of the art and open problems," School of Computing, Queen's University, Kingston, ON, Canada, Tech. Rep. 2006-504, 2006.
26. S. Lee, S. Kumara, and N. Gautam, "Efficient scheduling algorithm for component-based networks," Future Generation Comput.Syst., vol.23, no.4, pp. 558-568, 2007.
27. R. J. Paul, "Challenges to information systems: Time to change," Eur. J. Inf. Syst., vol.16, no.3, pp. 193-195, 2007.
28. C. M. Krishna and K. G. Shin, Real-Time Syst.. : Mcgraw-Hill, 1997.
29. W.-K. Chen, M. Hiltunen, and R. Schlichting, "Constructing adaptive software in distributed systems," in Proc. Int. Conf. Distrib. Comput. Syst., 2001, pp. 635-643.
30. M. O. McCracken, A. Snavely, and A. Malony, "Performance modeling for dynamic algorithm selection," in Proc. Int. Conf. Comput. Sci., 2003, pp. 749-758.
31. K. Y. Cai, B. Gu, H. Hu, and Y. C. Li, "Adaptive software testing with fixed-memory feedback," J. Syst. Softw., vol.80, no.8, pp. 1328-1348, 2007.
32. Q. Wang, "MASS: Middleware-based adaptive software system," in Proc. 31st Annu. Int. Comput. Softw. Appl. Conf., 2007, pp. 204-210.
33. M. Brinn, J. Berliner, A. Helsinger, T. Wright, M. Dyson, S. Rho, and D. Wells, "Extending the limits of DMAS survivability: The UltraLog project," IEEE Intell. Syst., vol.19, no.5, pp. 53-61, 2004.
34. D. Moore, W. Wright, and R. Kilmer, "Control surfaces for cougaar," in Proc. 1st Open Cougaar Conf., 2004, pp. 37-44.
35. D. Moore, A. Helsinger, and D. Wells, "Deconfliction in ultra-large MAS: Issues and a potential architecture," in Proc. 1st Open Cougaar Conf., 2004, pp. 125-133.
36. R. D. Snyder and D. C. Mackenzie, "Cougaar agent communities," in Proc. 1st Open Cougaar Conf., 2004, pp. 143-147.
37. S. Lee and S. Kumara, "Estimating global stress environment by observing local behavior in a multiagent system," in Proc. IEEE Int. Conf. Autom. Sci. Eng., 2005, pp. 215-219.
38. S. Lee, S. Kumara, and N. Gautam, "Market-Based model predictive control for large-scale information networks: Completion time and value of solution," IEEE Trans. Autom. Sci. Eng., vol.5, no.4, pp. 630-640, 2008.
39. M. Morari and J. H. Lee, "Model predictive control: Past, present and future," Comput. Chem. Eng., vol.23, no.4, pp. 667-682, 1999.
40. J. B. Rawlings, "Tutorial overview of model predictive control," IEEE Control Syst., vol.20, no.3, pp. 38-52, 2000.
41. S. J. Qin and T. A. Badgwell, "A survey of industrial model predictive technology," Control Engineering Practice, vol.11, no.7, pp. 733-764, 2003.
42. E. Camponogara, D. Jia, B. H. Krogh, and S. Talukdar, "Distributed model predictive control," IEEE Control Syst. Mag., vol.22, no.1, pp. 44-52, 2002.
43. R. Negenborn, B. D. Schutter, and H. Hellendoorn, "Multi-agent model predictive control: A survey," Delft Center for Systems and Control, Delft Univ. Technology, Delft, The Netherlands, Tech. Rep. 04-010, 2004.
44. A. N.Venkat, J. B. Rawlings, and S. J. Wright, "Stability and optimality of distributed model predictive control," in Proc. 44th IEEE Conf. Decision and Control, 2005, pp. 6680-6685.
45. C. A.Waldspurger and W. E.Weihl, "Lottery scheduling: flexible proportional- share resource management," in Proc. 1st Symp. Oper. Syst. Design Implementation, 1994, pp. 1-11.
46. I. Stoica, H. Abdel-Wahab, J. Gehrke, K. Jeffay, S. K. Baruah, and C. G. Plexton, "A proportional share resource allocation algorithm for real-time, time-shared systems," in Proc. 17th IEEE Real-Time Syst. Symp., 1996, pp. 288-299.
47. B. Caprita, W. C. Chan, J. Nieh, C. Stein, and H. Zheng, "Group ratio round-robin: proportional share scheduling for uniprocessor and multiprocessor systems," in Proc. 2005 USENIX Annu. Tech. Conf., 2005, pp. 337-352.
48. Y. Chevaleyre, P. E. Dunne, U. Endriss, J. Lang, M. Lemaître, N. Maudet, J. Padget, S. Phelps, J. A. Rodríguez-aguilar, and P. Sousa, "Issues in multiagent resource allocation," Informatica, vol.30, pp. 3-31, 2006.
49. S. D. Jong, K. Tuyls, and K. Verbeeck, "Fairness in multi-agent systems," Knowl. Eng. Rev., vol.23, no.2, pp. 153-180, 2008.
50. O. F. Rana and K. Stout, "What is scalability in multi-agent systems?," in Proc. 4th Int. Conf. Auton. Agents, 2000, pp. 56-63.
51. P. Milgrom, "Auctions and bidding: A primer," J. Econ. Perspectives, vol.3, pp. 3-22, 1989.
52. W. Vickrey, "Counterspeculation, auction, and competitive sealed tenders," J. Finance, vol.16, pp. 8-37, 1961.
53. H. R. Varian, "Economic mechanism design for computerized agents," in Proc. First USENIX Workshop on Electronic Commerce, 1995.