Q-Learning Enabled Green Communication in Internet of Things
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JITM-14-6_008
تاریخ نمایه سازی: 22 تیر 1401
Abstract:
Limited energy capacity, physical distance between two nodes and the stochastic link quality are the major parameters in the selection of routing path in the internet of things network. To alleviate the problem of stochastic link quality as channel gain reinforcement based Q-learning energy balanced routing is presented in this paper. Using above mentioned parameter an optimization problem has been formulated termed as reward or utility of network. Further, formulated optimization problem converted into Markov decision problem (MDP) and their state, value, action and reward function are described. Finally, a QRL algorithm is presented and their time complexity is analyses. To show the effectiveness of proposed QRL algorithm extensive simulation is performed in terms of convergence property, energy consumption, residual energy and reward with respect to state-of-art-algorithms.
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Authors
Kumar
Ph.D. Scholar, School of Computer & Systems Sciences, Jawaharlal Nehru University, New Delhi-۱۱۰۰۶۷,
Kumar
Assistant Professor, School of Computer & Systems Sciences, Jawaharlal Nehru University, New Delhi-۱۱۰۰۶۷.
Jaiswal
Ph.D. Scholar, School of Computer & Systems Sciences, Jawaharlal Nehru University, New Delhi-۱۱۰۰۶۷.
Kashyap
Ph.D., School of Computer & Systems Sciences, Jawaharlal Nehru University, New Delhi-۱۱۰۰۶۷.
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