Minimizing the Age of Incorrect Information for Unknown Markovian Source

by   Saad Kriouile, et al.

The age of information minimization problems has been extensively studied in Real-time monitoring applications frameworks. In this paper, we consider the problem of monitoring the states of unknown remote source that evolves according to a Markovian Process. A central scheduler decides at each time slot whether to schedule the source or not in order to receive the new status updates in such a way as to minimize the Mean Age of Incorrect Information (MAoII). When the scheduler knows the source parameters, we formulate the minimization problem as an MDP problem. Then, we prove that the optimal solution is a threshold-based policy. When the source's parameters are unknown, the problem's difficulty lies in finding a strategy with a good trade-off between exploitation and exploration. Indeed, we need to provide an algorithm implemented by the scheduler that jointly estimates the unknown parameters (exploration) and minimizes the MAoII (exploitation). However, considering our system model, we can only explore the source if the monitor decides to schedule it. Then, applying the greedy approach, we risk definitively stopping the exploration process in the case where at a specific time, we end up with an estimation of the Markovian source's parameters to which the corresponding optimal solution is never to transmit. In this case, we can no longer improve the estimation of our unknown parameters, which may significantly detract from the performance of the algorithm. For that, we develop a new learning algorithm that gives a good balance between exploration and exploitation to avoid this main problem. Then, we theoretically analyze the performance of our algorithm compared to a genie solution by proving that the regret bound at time T is log(T). Finally, we provide some numerical results to highlight the performance of our derived policy compared to the greedy approach.


page 1

page 2

page 3

page 4


Minimizing the Age of Incorrect Information for Real-time Tracking of Markov Remote Sources

The age of Incorrect Information (AoII) has been introduced recently to ...

When to pull data from sensors for minimum Distance-based Age of incorrect Information metric

The age of Information (AoI) has been introduced to capture the notion o...

Age of Incorrect Information under Delay

This paper investigates the problem of minimizing the Age of Incorrect I...

Preempting to Minimize Age of Incorrect Information under Random Delay

We consider the problem of optimizing the decision of a preemptive trans...

Age of Incorrect Information With Hybrid ARQ Under a Resource Constraint for N-ary Symmetric Markov Sources

The Age of Incorrect Information (AoII) is a recently proposed metric fo...

Remote Estimation in Decentralized Random Access Channels

Efficient sampling and remote estimation is critical for a plethora of w...

Extending the Multiple Traveling Salesman Problem for Scheduling a Fleet of Drones Performing Monitoring Missions

In this paper we schedule the travel path of a set of drones across a gr...

Please sign up or login with your details

Forgot password? Click here to reset