Online Age-of-Information Scheduling

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“Classical network scheduling problems have primarily focused on optimizing metrics such as delay, which pertain to the service provided to individual packets in the network. However, in modern applications like tele-robotics and networked cars, the emphasis is on metrics that capture the freshness of information, specifically, how up to date the information is at the receiver (monitor) compared to the transmitter (source). Thus, several metrics have been introduced to quantify information freshness, the most widely used one being the age-of-information (AoI). The AoI for a source at any given time is equal to the difference between the current time and the generation time of the most recent packet (update) received at the monitor. For modern applications, the scheduling objective is to minimize the AoI for the sources in an online environment, where at any time, only causal information is available. In this talk, I will introduce the AoI metric, and its distinguishing features and scheduling challenges compared to the classical packet-based metrics. Subsequently, I will present some of our recent results on AoI scheduling with multiple sources and energy constraints.”

Kumar Saurav, PhD student at TIFR Mumbai

“Kumar Saurav is a PhD candidate in the School of Technology and Computer Science at the Tata Institute of Fundamental Research, Mumbai. His research spans online scheduling and resource allocation problems in networks and computer systems. His PhD results on online age-of-information (AoI) scheduling have appeared in reputed conferences and journals including IEEE JSAC, IEEE JSAIT, Performance Evaluation, and IEEE INFOCOM, and were showcased at Graduation Day Forum (IEEE SPCOM) 2022, and ACM ARCS 2023. He has also been a finalist at Swachhathon 1.0, a contest organized by the Ministry of Drinking Water and Sanitation (MoDWS), for his solution for monitoring the usage and societal impact of public sanitation infrastructure in rural India.”