2017/12/11 by Ahmed Arafa, Şennur Ulukuş, Arafa, Ahmed +1 · 1 citation
Computer Science · #Age of Information Optimization #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #Networking and Internet Architecture (cs.NI) #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1712.03945
openalex publication_date 2017/12/11 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
We consider an energy harvesting source that is collecting measurements from\na physical phenomenon and sending updates to a destination within a\ncommunication session time. Updates incur transmission delays that are function\nof the energy used in their transmission. The more transmission energy used per\nupdate, the faster it reaches the destination. The goal is to transmit updates\nin a timely manner, namely, such that the total age of information is minimized\nby the end of the communication session, subject to energy causality\nconstraints. We consider two variations of this problem. In the first setting,\nthe source controls the number of measurement updates, their transmission\ntimes, and the amounts of energy used in their transmission (which govern their\ndelays, or service times, incurred). In the second setting, measurement updates\nexternally arrive over time, and therefore the number of updates becomes fixed,\nat the expense of adding data causality constraints to the problem. We\ncharacterize age-minimal policies in the two settings, and discuss the\nrelationship of the age of information metric to other metrics used in the\nenergy harvesting literature.\n