Presentation
Where and How to Charge: Effective Charging with Mobile Agent in Wireless Powered CPS
DescriptionWireless power transfer (WPT) techniques provide the possibility for rapid and efficient energy supply to sensors, and mobile charging devices further expand the application scenarios of WPT technology.
Therefore, related modeling and scheduling studies have always been a hot topic.
In this paper, we design a schedule scheme for efficient charging with mobile chargers in wireless-powered sensor networks (WPSN).
We consider beamforming technique and fluctuating channel, which makes scheduling problem more practical and complex for linear analysis unavailable.
We show the analyzability of area discretization and then prove the constant approximation ratio for our scheduling algorithm in offline scenario where the channel state information is known.
In online scenario where the channel state information dynamically changes, a bandit algorithm is further proposed to balance the exploration and exploitation both in stationary and non-stationary environment.
Simulation results validate that the performance of our algorithm in the offline scenario highly approximates the upper bound, and the algorithm in the online scenario can rapidly approach the upper bound while effectively tracking the changes in channel state information for adaptive adjustments.
Therefore, related modeling and scheduling studies have always been a hot topic.
In this paper, we design a schedule scheme for efficient charging with mobile chargers in wireless-powered sensor networks (WPSN).
We consider beamforming technique and fluctuating channel, which makes scheduling problem more practical and complex for linear analysis unavailable.
We show the analyzability of area discretization and then prove the constant approximation ratio for our scheduling algorithm in offline scenario where the channel state information is known.
In online scenario where the channel state information dynamically changes, a bandit algorithm is further proposed to balance the exploration and exploitation both in stationary and non-stationary environment.
Simulation results validate that the performance of our algorithm in the offline scenario highly approximates the upper bound, and the algorithm in the online scenario can rapidly approach the upper bound while effectively tracking the changes in channel state information for adaptive adjustments.
Event Type
Work-in-Progress Poster
TimeTuesday, June 256:00pm - 7:00pm PDT
LocationLevel 2 Lobby
AI
Autonomous Systems
Cloud
Design
EDA
Embedded Systems
IP
Security