Neeraj Jaggi - Witchita State University - Wichita State University

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Perfect State Information • Markov Decision Process (Finite K) ◦ State Space = {(L, E); 0 ≤ L ≤ K, E є [0, 1]} L – Current Energy Level, E – On/Off period Reward r– one if event detected; zero otherwise Action u є [0, 1]; Transition probabilities p 10 • Optimality equations (average reward criteria) ◦ h* – state variables ◦ λ* – optimal reward Neeraj Jaggi Dept of EECS Wichita State University
Perfect State Information (contd.) • Approximate Solution 11 ◦ Closed form solution for h* does not seem to exist • Value Iteration ◦ Activation Algorithm When L
Page 1 and 2: Rechargeable Sensor Activation unde
Page 3 and 4: • Sensor Nodes ◦ Tiny, low cost
Page 5 and 6: Dynamic Sleep Scheduling 5 • How
Page 7 and 8: Sensor Energy Consumption Model 7
Page 9: Approach/Methodology 9 • Perfect
Page 13 and 14: Optimal Activation Policy • Optim
Page 15 and 16: Structure of Optimal Policy • Opt
Page 17 and 18: EB-CW Policy • Energy balancing C
Page 19 and 20: Summary and Contributions • We co
Page 21: Q & A 21 THANK YOU !! Neeraj Jaggi

Neeraj Jaggi - Witchita State University - Wichita State University

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