Fuzzy-Based Hybrid Control Algorithm of Wireless Sensor Network System
A hybrid control algorithm, which combines channel selection and transmission power control for Sub-1GHz wireless sensor network systems, is proposed in this paper. By measuring and evaluating the status of candidate channels, the hybrid control algorithm can identify a channel with minimal interference for transmission. Moreover, by analyzing link quality estimators and employing a fuzzy controller, the system can adaptively adjust transmission power based on the surrounding environment of nodes. Unstable frequencies can be avoided through frequency hopping, either. The proposed algorithm helps nodes reduce power consumption and prolong the life of system while ensuring communication stability. Long-term experiment results indicate that the hybrid control algorithm meets the stable communication defined by IEEE802.15.4, achieving a packet error rate of less than 1% at various test locations. Additionally, the performance of the hybrid control algorithm is more significant when the environment changes rapidly. According to the estimation of nodes’ power consumption, several nodes employing the proposed algorithm can maintain the battery life of over seven years, demonstrating the efficacy of the hybrid control algorithm presented in this paper.
The manuscript of IEEE Sensor Journal
These datasets are part of Community Resource for Archiving Wireless Data (CRAWDAD). CRAWDAD began in 2004 at Dartmouth College as a place to share wireless network data with the research community. Its purpose was to enable access to data from real networks and real mobile users at a time when collecting such data was challenging and expensive. The archive has continued to grow since its inception, and starting in summer 2022 is being housed on IEEE DataPort.