Age-Aware Dynamic Frame Slotted ALOHA for Machine-Type Communications
Moradian M. Dadlani A. Khonsari A. Tabassum H.
1 May 2024Institute of Electrical and Electronics Engineers Inc.
IEEE Transactions on Communications
2024#72Issue 52639 - 2654 pp.
Information aging has gained prominence in characterizing communication protocols for timely remote estimation and control applications. This work proposes an Age of Information (AoI)-aware threshold-based dynamic frame slotted ALOHA (T-DFSA) for contention resolution in random access machine-type communication networks. Unlike conventional DFSA that maximizes the throughput in each frame, the frame length and age-gain threshold in T-DFSA are determined to minimize the normalized average AoI reduction of the network in each frame. At the start of each frame in the proposed protocol, the common Access Point (AP) stores an estimate of the age-gain distribution of a typical node. Depending on the observedstatus of the slots, age-gains of successful nodes, and maximum available AoI, the AP adjusts its estimation in each frame. The maximum available AoI is exploited to derive the maximum possible age-gain at each frame and thus, to avoid overestimating the age-gain threshold, which may render T-DFSA unstable. Numerical results validate our theoretical analysis and demonstrate the effectiveness of the proposed T-DFSA compared to the existing optimal frame slotted ALOHA, threshold-ALOHA, and age-based thinning protocols in a considerable range of update generation rates.
Age of information , dynamic frame slotted ALOHA , Internet of Things , random access , stochastic arrivals
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K. N. Toosi University of Technology, School of Computer Engineering, Tehran, 15418-49611, Iran
Institute for Research in Fundamental Sciences, School of Computer Science, Tehran, 19538-33511, Iran
University of Alberta, Department of Computing Science, Edmonton, T6G 2E8, AB, Canada
Nazarbayev University, Department of Electrical and Computer Engineering, Astana, 010000, Kazakhstan
University of Tehran, School of Electrical and Computer Engineering, Tehran, 14155, Iran
York University, Department of Electrical Engineering and Computer Science, Toronto, M3J 1P3, ON, Canada
K. N. Toosi University of Technology
Institute for Research in Fundamental Sciences
University of Alberta
Nazarbayev University
University of Tehran
York University
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