DARPA ULTRALOG Final Report - Industrial and Manufacturing ...

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Manuscript for IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2 1. Introduction The growth in complexity and size of software systems due to automation or organizational integration is leading to the increasing importance of distributed and component-based architectures. Distributed computing aims at using computing power of machines connected by a network. When a task requires intensive computation, it becomes natural choice to achieve high performance. A component is a reusable program element. Component technology utilizes the components so that developers can build systems needed by simply defining their specific roles and wiring them together [1][2]. In networks with component-based architecture, each component is highly specialized for specific tasks. Another emerging technology is adaptive software [3][4]. Adaptive software has alternative algorithms for the same numerical problem and a switching function for selecting the best algorithm in response to environmental changes. As modern operating environments are highly dynamic, adaptive software becomes an important tool to achieve portable high performance. We study a large-scale information network (with respect to the number of components as well as machines) comprising of distributed software components linked together through a task flow structure. A problem given to the network is decomposed in terms of root tasks for some components and those tasks are propagated through a task flow structure to other components. As a problem can be decomposed with respect to space, time, or both, a component can have multiple root tasks that can be considered independent and identical in their nature. The service provided by the network is to produce a global solution to a given problem, which is an aggregate of partial solutions of individual tasks. Each component can have alternative algorithms to process a task which trade off processing time and value of partial solution. Quality of Service (QoS) of the network is determined by the value of global solution and the time for
Manuscript for IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 3 generating global solution (i.e., completion time). For a given topology, the network can control its behavior by utilizing two different kinds of control actions: algorithm selection and resource allocation. While resource allocation tries to efficiently utilize limited resources, algorithm selection can change the amount of required resources. The resource allocation we are addressing here, is allocating resources of each machine to the residing components for a given topology. As problems are decomposed in various ways depending on their nature and size, and their QoS functions are context-dependent, the network needs to provide adaptive solutions to given problems by utilizing such control actions. One can imagine wide range of scientific and engineering problems that can be solved by such a network. UltraLog (http://www.ultralog.net) networks, implemented in Cougaar (Cognitive Agent Architecture: http://www.cougaar.org) developed by DARPA (Defense Advanced Research Project Agency), are the instances [5]-[9]. Each agent in these networks represents an organization of military supply chain and has a set of components specialized for each functionality (allocation, expansion, inventory management, etc) and class (ammunition, water, fuel, etc). The objective of an UltraLog network is to provide an appropriate logistics plan for a given military operational plan. A logistics plan is a global solution which is an aggregate of individual schedules built by components. An operational plan is decomposed into logistics requirements of each thread for each agent, and a requirement is further decomposed into root tasks (one task per day) for a designated component. As a result, a component can have hundreds of root tasks depending on the horizon of an operation and thousands of tasks to process as the root tasks are propagated. As the scale of operation increases there can be thousands of agents (tens of thousands of components) in hundreds of machines working together to generate a logistics plan. QoS of these networks is determined by the quality of logistics plan (value of
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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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Page 106 and 107: 2 discuss problem domain and in Sec
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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 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
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Page 172 and 173: Table 2. TechSpecs: Infrastructure
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Page 176 and 177: Acknowledgements The work described
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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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