collaborators

17 papers

cs.IT2026

Squeezing the Most Out of Preemption for AoI Minimization: Single-source Case

Nail Akar, Mohammad Moltafet, Sennur Ulukus +2

In this work, we study a single-source single-server continuous-time status update system where the updates arrive according to a Poisson process and update service times are gener…

cs.IT2026

Dual-Regime Absorbing Markov Chain Theory in Remote Estimation: Age-Minimizing Push Policies

Ismail Cosandal, Sennur Ulukus, Nail Akar

For a remote estimation system, we study the optimization of age of incorrect information (AoII), which is a recently proposed semantic-aware information freshness metric. In parti…

cs.IT2026

When and Which Sensor to Observe? Timely Tracking of a Joint Markov Source

Ismail Cosandal, Sennur Ulukus, Nail Akar

We investigate the problem of remote estimation (at a monitor) of a discrete-time joint Markov process with individual components which can be observed with dedicated sensors. At a…

cs.IT2026

Preemption Revisited: Multi-Threshold Preemption Policies for AoI Minimization

Sahan Liyanaarachchi, Sennur Ulukus, Nail Akar

The study of optimal preemption policies for status update systems has been a recurring topic in the age of information (AoI) literature, where threshold-based structures have been…

cs.IT2026

Utilizing the Perceived Age to Maximize Freshness in Query-Based Update Systems

Sahan Liyanaarachchi, Sennur Ulukus, Nail Akar

Query-based sampling has become an increasingly popular technique for monitoring Markov sources in pull-based update systems. However, most of the contemporary literature on this a…

cs.IT2026

Beyond Martingale Estimators: Structured Estimators for Maximizing Information Freshness in Query-Based Update Systems

Sahan Liyanaarachchi, Sennur Ulukus, Nail Akar

This paper investigates information freshness in a remote estimation system in which the remote information source is a continuous-time Markov chain (CTMC). For such systems, estim…