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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.12962 |
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| _version_ | 1866908510944493568 |
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| author | Zakeri, Abolfazl Moltafet, Mohammad Codreanu, Marian |
| author_facet | Zakeri, Abolfazl Moltafet, Mohammad Codreanu, Marian |
| contents | We address the real-time remote tracking problem in a status update system comprising two sensors, two independent information sources, and a remote monitor. The status updating follows a pull-based communication, where the monitor commands/pulls the sensors for status updates, i.e., the actual state of the sources. We consider that the observations are \textit{correlated}, meaning that each sensor's sent data could also include the state of the other source due to, e.g., inter-sensor communications or overlapping monitoring regions. The effectiveness of data communication is measured by a generic distortion, capturing the underlying application goal. We provide optimal command/pulling policies for the monitor that minimize the average weighted sum distortion and transmission cost. Since the monitor cannot fully observe the exact state of each source, we propose a partially observable Markov decision process (POMDP) and reformulate it as a belief MDP problem. We then effectively truncate the infinite belief space and transform it into a finite-state MDP problem, which is solved via relative value iteration. Simulation results show the effectiveness of the derived policy over age-based and deep-Q network baseline policies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_12962 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Goal-Oriented Remote Tracking Through Correlated Observations in Pull-based Communications Zakeri, Abolfazl Moltafet, Mohammad Codreanu, Marian Signal Processing We address the real-time remote tracking problem in a status update system comprising two sensors, two independent information sources, and a remote monitor. The status updating follows a pull-based communication, where the monitor commands/pulls the sensors for status updates, i.e., the actual state of the sources. We consider that the observations are \textit{correlated}, meaning that each sensor's sent data could also include the state of the other source due to, e.g., inter-sensor communications or overlapping monitoring regions. The effectiveness of data communication is measured by a generic distortion, capturing the underlying application goal. We provide optimal command/pulling policies for the monitor that minimize the average weighted sum distortion and transmission cost. Since the monitor cannot fully observe the exact state of each source, we propose a partially observable Markov decision process (POMDP) and reformulate it as a belief MDP problem. We then effectively truncate the infinite belief space and transform it into a finite-state MDP problem, which is solved via relative value iteration. Simulation results show the effectiveness of the derived policy over age-based and deep-Q network baseline policies. |
| title | Goal-Oriented Remote Tracking Through Correlated Observations in Pull-based Communications |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2503.12962 |