Dissertation · Nazarbayev University Repository · May 1, 2025
ENERGY-EFFICIENT SYNCHRONIZATION USING TRANSFER OF KNOWLEDGE
Zhansaya Talaptan, Ardak Alipova
Abstract
The project tackles the problem of one-to-many Internet of Things (IoT) synchronization with the goal of energy efficiency optimization. It builds upon the previous work done by Assylbek et al. (2024) that implemented a Reinforcement Learning based solution to synchronize receiver end-devices with a central transmitter device that broadcasts beacons in a constant interval. Our solution adds a component of Transfer Learning to further enhance the energy efficiency by eliminating the need to learn from scratch. Devices that newly join the system can request and use the knowledge from the experienced devices, therefore decreasing their learning time and enabling them to start with closer to optimal behaviour. We refer to this process as Transfer of Knowledge (ToK). Since the energy consumption of IoT devices is tied to their sleep times and radio-on times, our goal and expectation in implementing ToK is to maximize the sleep time and minimize radio-on time on end-devices.
Related publications
- Integrating Multi-Source Feedback in Computational DesignACM Transactions on Interactive Intelligent Systems · 2026 · Same author: Ardak Alipova
- One-to-Many Synchronization in High-Drift IoT Devices Using Reinforcement LearningIEEE Transactions on Instrumentation and Measurement · 2025 · Citations: 1 · Same author: Ardak Alipova
- A SIMULATION-DRIVEN FRAMEWORK FOR NETWORK-AWARE PERFORMANCE EVALUATION OF IOT SYSTEMSVestnik of M Kozybayev North Kazakhstan University · 2026 · Shared topic: Energy Efficient Wireless Sensor Networks
- A BREAKPOINT MODEL FOR DATA VOLUME AND NETWORK CAPACITY IN INTERNET OF THINGSScientific Journal of Astana IT University · 2026 · Shared topic: IoT and Edge/Fog Computing
