2019/12/12 by Caglar Tunc, Tunc, Caglar, Shivendra S. Panwar +1
Computer Science · Engineering · #Age of Information Optimization #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #IoT Networks and Protocols #IoT and Edge/Fog Computing #Networking and Internet Architecture (cs.NI) #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1912.06119
openalex publication_date 2019/12/12 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
We consider an energy harvesting information update system where a sensor is\nallowed to choose a transmission mode for each transmission, where each mode\nconsists of a transmission power-error pair. We also incorporate the battery\nphenomenon called battery recovery effect where a battery replenishes the\ndeliverable energy if kept idle after discharge. For an energy-limited age of\ninformation (AoI) system, this phenomenon gives rise to the interesting\ntrade-off of recovering energy after transmissions, at the cost of increased\nAoI. Considering two metrics, namely peak-age hitting probability and average\nage as the worst-case and average performance indicators, respectively, we\npropose a framework that formulates the optimal transmission scheme selection\nproblem as a Markov Decision Process (MDP). We show that the gains obtained by\nconsidering both battery dynamics and adjustable transmission power together\nare much higher than the sum gain achieved if they are considered separately.\nWe also propose a simple methodology to optimize the system performance taking\ninto account worst-case and average performances jointly.\n