CRII: CIF: Models, Theories and Algorithms for Timeliness Optimization in Information-update Systems

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The last two decades have witnessed significant advances in the development of theoretical foundations and control mechanisms for network resource allocation. These newly developed theories and mechanisms have substantially improved network performance in terms of throughput and delay. However, optimizing throughput and delay is insufficient for networked systems that require real-time information update. The state-of-the-art theoretical foundations need to be largely expanded to integrate timeliness of information into the design of network control mechanisms. The research on timeliness optimization is still at its nascent stage. New theoretical results and practical solutions coming out of this project are expected to have a significant impact not only on information theory and networking community, but also on databases and machine learning community. This project will focus on providing research experiences to undergraduate and K-12 students, recruiting and advising underrepresented students, and engaging in curriculum development activities. The goal of this research is to develop new models, theories, and algorithms for optimizing timeliness performance in information-update systems. A recently proposed metric called age-of-information or simply "age", will be employed as a key metric to study timeliness performance. First, this research investigates the impact of channel coding on timeliness of information transmitted over a lossy channel. Second, this research studies the problem of age minimization under a bounded staleness constraint in a new setting where information can be partitioned into multiple disjoint units with partial updates. Finally, this research introduces a new Pull model where the destination sends queries to the sources to pull information of interest and proposes using replication schemes to optimize timeliness performance.