DARPA ULTRALOG Final Report - Industrial and Manufacturing ...

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Technology, Cambridge, MA, 1995. [21] T. D. Braun, H. J. Siegel, N. Beck, L. L. Bölöni, M. Maheswaran, A. I. Reuther, J. P. Robertson, M. D. Theys, B. Yao, D. Hensgen, and R. F. Freund, “A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems,” Journal of Parallel and Distributed Computing, vol. 61, pp. 810-837, 2001. [22] M. O. McCracken, A. Snavely, and A. Malony, “Performance modeling for dynamic algorithm selection,” in Proc. Int. Conf. Computational Science, 2003, pp. 749-758. [23] P. Oreizy, M. M. Gorlick, R. N. Taylor, D. Heimbigner, G. Johnson, N. Medvidovic, A. Quilici, D. S. Rosenblum, and A. L. Wolf, “An architecture-based approach to self-adaptive software,” IEEE Intelligent Systems, vol. 14, no. 3, pp. 54-62, 1999. 20
Manuscript for IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 1 MARKET-BASED MODEL PREDICTIVE CONTROL FOR LARGE-SCALE INFORMATION NETWORKS: COMPLETION TIME AND VALUE OF SOLUTION Seokcheon Lee, Soundar Kumara, and Natarajan Gautam Department of Industrial and Manufacturing Engineering The Pennsylvania State University University Park, PA 16802 {stonesky, skumara, ngautam}@psu.edu ABSTRACT There are several important properties of modern software systems. They tend to be largescale with distributed and component-based architectures. Also, dynamic nature of operating environments leads them to utilize alternative algorithms. However, on the other hand, these properties make it hard to provide appropriate control mechanisms due to the increased complexity. Components are sharing resources and each component can have alternative algorithms. As a result, the behavior of a software system can be controlled through resource allocation as well as algorithm selection. This novel control problem is worthy of investigation in order to double the benefits of those properties. In this paper we design a scalable control mechanism for such systems. The quality of service we are considering is a product of the value of solution and the time for generating solution for a given problem. We build a mathematical programming model that trade off these two conflicting objectives and decentralize the model through an auction market. By periodically opening the auction market for each existing system state, a closed-loop policy is formed. We verify the designed control mechanism empirically. Index Terms: Distributed applications, modeling and prediction, optimization, scalability
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Ultra*Log PSU/IAI Final Report for
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Contents Contents .................
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Executive Summary Ultra*Log is a De
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2.3 Gnanasambandam, N., Lee, S., Ku
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6 Characterization and analysis of
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timizing simultaneously the link de
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where ∆ 1 (j) ≥ 0 and ∆ 2 (i,
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Table 2. GA Results Agent N A D max
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connected component, in which a pat
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Random Small-world Scale-free with
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Growth mechanisms Start with a smal
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Table 2. The proposed network’s c
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DMAS Controller. The functional uni
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1000 500 0 -500 -1000 0.2 0.4 0.6 0
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tems. Proceedings of the Second Joi
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Proceedings of the 1st Open Cougaar
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1 SITUATION IDENTIFICATION USING DY
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3 3.2 Behavior In SSC society an ag
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5 All the behavior parameters may n
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Estimating Global Stress Environmen
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chaotic deterministic time series.
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100% 1 95% 2 14 15 64% TAO 4 64% 62
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interactions as a dynamical system
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ehavior states under varying system
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Extensive testing and validation of
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5 Conclusions and Future Research T
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2 to function critically even under
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4 points into a corresponding inner
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6 stresses well. The Warehouse 1 ag
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Table 1: Notation Symbol Descriptio
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4 Conclusions and Future Work 4.1 C
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O, U Stresses Physical/Infrastructu
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Manuscript for IEEE Transactions on
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Manuscript for IEEE Transactions on
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Page 106 and 107: 2 discuss problem domain and in Sec
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Page 110 and 111: 6 S UB i ∑ = P LI / LI . (16) i p
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Page 118 and 119: component is a member of one of the
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Page 122 and 123: limit of large number of tasks. If
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Page 126 and 127: We set up eight different experimen
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Page 130 and 131: pp. 191-200. [3] I. Foster, C. Kess
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Page 156 and 157: Coordinating Control Decisions of S
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Page 160 and 161: Understanding Agent Societies Using
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Page 168 and 169: Figure 1. Agent Hierarchy in CPE So
Page 170 and 171: Figure 3. The World Model CPY Agent
Page 172 and 173: Table 2. TechSpecs: Infrastructure
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Page 176 and 177: Acknowledgements The work described
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sustained oscillations. If the inst
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solved by biological systems for li
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non-linear and non-stationarity. Ne
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D k : Outflow from high priority qu
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the system starts to perform self-s
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sustained in a supply chain. Resour
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which are necessary to make good mo
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focusing on the computational compl
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line of research that deals with ne
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ealizable. But the inherent complex
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Min, H. and Zhou, G., 2002, Supply
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In the rest of this paper we report
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shows relatively irregular behavior
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