Minimizing the AoI in multi-source two-hop systems under an average resource constraint
Zakeri, Abolfazl; Moltafet, Mohammad; Leinonen, Markus; Codreanu, Marian (2022-07-28)
A. Zakeri, M. Moltafet, M. Leinonen and M. Codreanu, "Minimizing the AoI in Multi-Source Two-Hop Systems under an Average Resource Constraint," 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC), 2022, pp. 1-5, doi: 10.1109/SPAWC51304.2022.9834029.
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https://urn.fi/URN:NBN:fi-fe202301041411
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Abstract
We develop online scheduling policies to minimize the sum average age of information (AoI) subject to transmission capacity and long-run average resource constraints in a multisource two-hop system, where independent sources randomly generate status update packets which are sent to the destination via a relay through error-prone links. A stochastic optimization problem is formulated and solved in known and unknown environments. For the known environment, an online nearoptimal low-complexity policy is developed using the driftplus-penalty method. For the unknown environment, a deep reinforcement learning policy is developed by employing the Lyapunov optimization theory and a dueling double deep Qnetwork. Simulation results show up to 136% performance improvement of the proposed policy compared to a greedy-based baseline policy.
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