A New Method to Find a High Reliable Route in IoT by Using Reinforcement Learning and Fuzzy Logic
- 11 Downloads
Recently, Internet is moving quickly toward the interaction of objects, computing devices, sensors, and which are usually indicated as the Internet of things (IoT). The main monitoring infrastructure of IoT systems main monitoring infrastructure of IoT systems is wireless sensor networks. A wireless sensor network is composed of a large number of sensor nodes. Each sensor node has sensing, computing, and wireless communication capability. The sensor nodes send the data to a sink or a base station by using wireless transmission techniques However, sensor network systems require suitable routing structure to optimizing the lifetime. For providing reasonable energy consumption and optimizing the lifetime of WSNs, novel, efficient and economical schemes should be developed. In this paper, for enhancing network lifetime, a novel energy-efficient mechanism is proposed based on fuzzy logic and reinforcement learning. The fuzzy logic system and reinforcement learning is based on the remained energies of the nodes on the routes, the available bandwidth and the distance to the sink. This study also compares the performance of the proposed method with the fuzzy logic method and IEEE 802.15.4 protocol. The simulations of the proposed method which were carried out by OPNET (Optimum Network performance) indicated that the proposed method performed better than other protocols such as fuzzy logic and IEEE802.15.4 in terms of power consumption and network lifetime.
KeywordsIoT Energy consumption Wireless sensor networks (WSNs) Fuzzy logic IEEE802.15.4 Reinforcement learning
- 1.Skarmeta, A. F., Hernandez-Ramos, J. L., & Moreno, M. (2014). A decentralized approach for security and privacy challenges in the internet of things. In IEEE World Forum on Internet of Things (WF-IoT) (pp. 67–72).Google Scholar
- 10.L. M. S. Committee. (2003). Part 15.4: wireless medium access control (MAC) and phsical layer (PHY) specifications for low-rate wireless personal area networks (LR-WPANs). IEEE Computer Society.Google Scholar
- 12.Koubaa, A., Alves, M., & Tovar, E. (2006). GTS allocation analysis in IEEE 802.15. 4 for real-time wireless sensor networks. In Proceedings 20th IEEE international parallel & distributed processing symposium (p. 8). IEEE.Google Scholar