Abstract
The wireless sensor network is the core of the Internet of Things. However, wireless sensors have some limitations and challenges, such as limited power and computing power, data storage, and network bandwidth, especially power requirements. How to find a way to program more flexible and faster according to the state of each sensing node in the network becomes an important issue. The software-defined network separates the control functions from the hardware devices, such as switches or routers, so that these hardware devices only have the data forwarding function, and the control software dynamically controls the flow of the network and data packets according to the network state and application requirements. In order to provide flexibility and adaptability, software-defined networks require a dynamic approach to solving and optimizing routing planning problems. This study will use the artificial bee colony algorithm to monitor the state of the sensor nodes in the software-defined network through the controller and take the best decision dynamically. Artificial bee colony algorithms are used to optimize wireless sensor networks and improve sensor node energy usage and data packets routing issues. The contribution of this research is to dynamically find the optimal routing path for the sensing nodes through the artificial bee colony algorithm, and improve the overall practicability and reliability of the wireless sensor network.
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This research was supported in part by the Ministry of Science and Technology, R.O.C. with a MOST grant 107-2221-E-025-005.
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Ke, CK., Wu, MY., Hsu, WH., Chen, CY. (2020). Discover the Optimal IoT Packets Routing Path of Software-Defined Network via Artificial Bee Colony Algorithm. In: Deng, DJ., Pang, AC., Lin, CC. (eds) Wireless Internet. WiCON 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 317. Springer, Cham. https://doi.org/10.1007/978-3-030-52988-8_13
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DOI: https://doi.org/10.1007/978-3-030-52988-8_13
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