International Journal of Applied Operational Research

en Aggregation aware distributed channel access in internet of things networks using reinforcement learning under partial observability عمومى General پژوهشي Research The rapid growth of Internet of Things (IoT) networks has transformed data aggregation and medium access control into a large-scale sequential decision-making problem under uncertainty, where distributed nodes operate with incomplete and noisy observations. In dense and heterogeneous IoT environments, classical medium access protocols fail to efficiently balance channel utilization, collision avoidance, and aggregation delay. In this paper, aggregation-aware dynamic channel access is formulated as a partially observable Markov decision process, explicitly capturing imperfect sensing and environmental uncertainty. To enable practical distributed learning, the original model is approximated by a surrogate Markov decision process defined over an information state constructed from local observations and past actions. Based on this formulation, a reinforcement learning–based cognitive medium access framework is developed, in which each node autonomously learns an access policy by optimizing a reward function that jointly accounts for successful transmission, collision probability, idle channel usage, and aggregation-related delay. Simulation results obtained in dynamic multi-channel environments demonstrate that the proposed framework significantly outperforms classical schemes. In dense network scenarios, it achieves a channel utilization of up to 85.3%, while reducing the collision probability to approximately 0.08, compared with ALOHA and SDSA. Moreover, the average response delay is reduced to 12.4 ms, confirming the effectiveness of the proposed approach for aggregation-aware and uncertainty-aware IoT networks.   Internet of Things Networks, Data Aggregation under Uncertainty, Partially Observable Markov Decision Process, Surrogate Markov Decision Model, Reinforcement Learning Based Medium Access Control, Distributed Channel Access Optimization, Sequential Decisio 111 123 http://ijorlu.lahijan.iau.ir/browse.php?a_code=A-10-30-6&slc_lang=en&sid=1 A. Rezvani rezvani@iau.ac.ir, 10031947532846002901 10031947532846002901 No Department of Computer, Faculty of Engineering, Qe.C., Islamic Azad University, Qeshm, Iran. A. Mirzaei a.mirzaei@iau.ac.ir 10031947532846002902 10031947532846002902 No Department of Computer Engineering, Ard.C., Islamic Azad University, Ardabil, Iran. N. Mikaeilvand nasser.mikaeilvand@iau.ac.ir 10031947532846002903 10031947532846002903 Yes Department of Computer Science and Mathematics, CT.C., Islamic Azad University, Tehran, Iran B. Nouri-Moghaddam babaknouri@iau.ac.ir 10031947532846002904 10031947532846002904 No Department of Computer Engineering, Ard.C., Islamic Azad University, Ardabil, Iran. S. Jahanbakhsh Gudakahriz sa.jahanbakhsh@iau.ac.ir 10031947532846002905 10031947532846002905 No Department of Computer Engineering, Ge.C., Islamic Azad University, Germi, Iran.