Adaptive duty cycling in sensor networks with energy harvesting using continuous-time markov chain and fluid models

• Main Authors: Chan, Ronald Wai Hong, Zhang, Pengfei, Nevat, Ido, Nagarajan, Sai Ganesh, VALERA, Alvin Cerdena, TAN, Hwee Xian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Wireless sensor networks; adaptive duty cycle; continuous-time Markov chain; Markov decision process; reinforcement learning; fluid model; Computer Sciences; Databases and Information Systems; Digital Communications and Networking
• Online Access: https://ink.library.smu.edu.sg/sis_research/3808; https://ink.library.smu.edu.sg/context/sis_research/article/4810/viewcontent/Adaptive_duty_cycling_in_sensor_networks_with_energy_harvesting_using_continuous_time_markov_chain_and_fluid_models.pdf
• Institution: Singapore Management University

The dynamic and unpredictable nature of energy harvesting sources available for wireless sensor networks, and the time variation in network statistics like packet transmission rates and link qualities, necessitate the use of adaptive duty cycling techniques. Such adaptive control allows sensor nodes...