DARPA ULTRALOG Final Report - Industrial and Manufacturing ...

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Manuscript for IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 18 CPU is allocated using a weighted round-robin scheduling in which CPU time received by each component in a round is equal to its assigned weight. N 1 N 2 N 3 N 4 A 1 A 2 A 3 A 4 N 5 A 5 A 6 N 6 A 7 A 8 A 9 A 10 A 11 A 12 A 13 A 14 A 15 A 16 200 200 200 200 400 400 400 400 N 7 Fig. 2. Experimental network configuration We set up six different experimental conditions as shown in Table 1. We vary the cost of completion time and the distribution of CPU time can be deterministic or exponential. While using stochastic value function we repeat 5 experiments. QoS UB is calculated from (14) with t=0 for each condition as shown in the table. Table 1. Experimental conditions Condition CCT(T) f i (v i ) QoS UB Con1-1 0.5T Deterministic 30000 Con1-2 0.5T Exponential 30000 Con2-1 1.5T Deterministic 19200 Con2-2 1.5T Exponential 19200 Con3-1 2.5T Deterministic 12000 Con3-2 2.5T Exponential 12000 We use ten different control policies for each experimental condition as shown in Table 2. First eight control policies (FX-XX) use fixed value modes over time. In predictive control policies (PC-XX) components selects value modes by solving the optimization model in (14). In round-robin resource allocation (XX-RR) the components in each node are assigned equal
Manuscript for IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 19 weights and in proportional allocation (XX-PA) proportional to the components’ load indices as in (15). PC-PA is the control policy corresponding to the programming model we have developed. The system makes decision every 100 time units. Table 2. Control policies used for experimentation Control policy F2-RR F2-PA F3-RR F3-PA F4-RR F4-PA F5-RR F5-PA PC-RR PC-PA Description v i = 2 for all i with round-robin allocation v i = 2 for all i with proportional allocation v i = 3 for all i with round-robin allocation v i = 3 for all i with proportional allocation v i = 4 for all i with round-robin allocation v i = 4 for all i with proportional allocation v i = 5 for all i with round-robin allocation v i = 5 for all i with proportional allocation Predictive control with round-robin allocation Predictive control with proportional allocation 5.2 Results Numerical results from the experimentation are shown in Table 3. PC-PA gives the best performance close to QoS UB in all different conditions. As the cost of completion time increases the system under PC-PA completes earlier as a result of trading off between the value of solution and the cost of completion time. There can be seen many cases in which the value of solution under PC-PA is even larger in spite of less completion time. It is because the programming model gives the maximal value of solution for a given completion time. Though both PC-PA and PC-RR choose value modes by solving the optimization model in (14), PC-RR gives worse performance because the optimization model is built presuming proportional resource allocation. Proportional allocation shows significant advantages compared to round-robin allocation in all thirty instances of comparison. The superiority supports the optimality of proportional resource allocation and consequently the effectiveness of the programming model.
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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 100 and 101: Manuscript for IEEE Transactions on
Page 106 and 107: 2 discuss problem domain and in Sec
Page 108 and 109: 4 t Si t ∫ + ( ) i ) t When RA i
Page 110 and 111: 6 S UB i ∑ = P LI / LI . (16) i p
Page 112 and 113: 8 policies while underutilizing in
Page 114 and 115: architecture based on both the Grid
Page 116 and 117: to machines (network topology) and
Page 118 and 119: component is a member of one of the
Page 120 and 121: denotes the immediate predecessors
Page 122 and 123: limit of large number of tasks. If
Page 124 and 125: Min-min heuristic algorithm Step 1:
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
Page 132 and 133: Technology, Cambridge, MA, 1995. [2
Page 134 and 135: Manuscript for IEEE TRANSACTIONS ON
Page 156 and 157: Coordinating Control Decisions of S
Page 158 and 159: directly. It has coarser scale. It
Page 160 and 161: Understanding Agent Societies Using
Page 162 and 163: • For tasks, the UID of the direc
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Page 166 and 167: within the monitored enclave. With
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
Page 174 and 175: terms of the average waiting times
Page 176 and 177: Acknowledgements The work described
Page 178 and 179: key realization to tackle this prob
Page 180 and 181: are or ignored perturbations. The e
Page 182 and 183: sustained oscillations. If the inst
Page 184 and 185: solved by biological systems for li
Page 186 and 187: non-linear and non-stationarity. Ne
Page 188 and 189: D k : Outflow from high priority qu
Page 190 and 191: the system starts to perform self-s
Page 192 and 193: sustained in a supply chain. Resour
Page 194 and 195: which are necessary to make good mo
Page 196 and 197: focusing on the computational compl
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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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