| 1. |
- Vilni, Saeid Sadeghi, et al.
(författare)
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AoI Analysis and Optimization in Systems with Computations-Intensive Updates
- 2023
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Ingår i: Journal of Communications and Networks. - : KOREAN INST COMMUNICATIONS SCIENCES (K I C S). - 1229-2370 .- 1976-5541. ; 25:5, s. 585-597
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Tidskriftsartikel (refereegranskat)abstract
- consider a status update system consisting of a sampler, a controller, a processing unit, a transmitter, and a sink. The sampler generates a sample upon receiving a request from the controller and the sample requires further processing before transmission, hence is computation-intensive. This is mathematically modeled by a server called process server. After processing the sample, the status update packet is generated and sent to the transmitter for delivery to the sink. This is mathematically modeled by a server called transmit server. The service time of each packet at the transmit and process servers follow geometric distributions. Moreover, we consider that the servers serve packets under the blocking policy, i.e., whenever a server is busy at the arrival time of a new packet, the new arriving packet is blocked and discarded. We analyze the average age of information (AoI) for two fixed policies, namely, 1) zero-wait-one policy and 2) zero-wait-blocking policy. According to the former policy, the controller requests sampling when there is no packet in the system. According to the zero-waitblocking policy, the controller requests a sample whenever the process server is idle. Furthermore, we develop an optimal control policy to minimize the average AoI using the tools of Markov decision process (MDP). In numerical results, we evaluate the performance of the policies under different system parameters. Moreover, we analyze the structure of the optimal policy.
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| 2. |
- Vilni, Saeid Sadeghi, et al.
(författare)
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Multi-Source AoI-Constrained Resource Minimization Under HARQ: Heterogeneous Sampling Processes
- 2024
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Ingår i: IEEE Transactions on Vehicular Technology. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0018-9545 .- 1939-9359. ; 73:1, s. 1084-1099
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Tidskriftsartikel (refereegranskat)abstract
- We consider a multi-source hybrid automatic repeat request (HARQ) based system, where a transmitter sends status update packets of random arrival (i.e., uncontrollable sampling) and generate-at-will (i.e., controllable sampling) sources to a destination through an error-prone channel. We develop transmission scheduling policies to minimize the average number of transmissions subject to an average age of information (AoI) constraint. First, we consider known environment (i.e., known system statistics) and develop a near-optimal deterministic transmission policy and a low-complexity dynamic transmission (LC-DT) policy. The former policy is derived by casting the main problem into a constrained Markov decision process (CMDP) problem, which is then solved using the Lagrangian relaxation, relative value iteration algorithm, and bisection. The LC-DT policy is developed via the drift-plus-penalty (DPP) method by transforming the main problem into a sequence of per-slot problems. Finally, we consider unknown environment and devise a learning-based transmission policy by relaxing the CMDP problem into an MDP problem using the DPP method and then adopting the deep Q-learning algorithm. Numerical results show that the proposed policies achieve near-optimal performance and illustrate the benefits of HARQ in status updating.
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