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مدیریت فناوری اطلاعات، جلد ۱۴، شماره Special Issue: Security and Resource Management challenges for Internet of Things، صفحات ۱۰۳-۱۱۷
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عنوان انگلیسی Q-Learning Enabled Green Communication in Internet of Things
چکیده انگلیسی مقاله 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.
کلیدواژه‌های انگلیسی مقاله Energy balancing,QRL,Link Quality,Learning rate,Internet of Things
نویسندگان مقاله Mukesh Kumar |
Ph.D. Scholar, School of Computer & Systems Sciences, Jawaharlal Nehru University, New Delhi-110067,

Sushil Kumar |
Assistant Professor, School of Computer & Systems Sciences, Jawaharlal Nehru University, New Delhi-110067.

Ankita Jaiswal |
Ph.D. Scholar, School of Computer & Systems Sciences, Jawaharlal Nehru University, New Delhi-110067.

Pankaj Kumar Kashyap |
Ph.D., School of Computer & Systems Sciences, Jawaharlal Nehru University, New Delhi-110067.

نشانی اینترنتی https://jitm.ut.ac.ir/article_86486_aecb312b47cc34d72adb686ae1fd659f.pdf
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