Intelligent Ocean Convergence Platform Based on IoT Empowered with Edge Computing
Mingzhou Liang, Xin Su, Xiaofeng Liu, Xuewu Zhang · 網際網路技術學刊 · 2020
The ocean is currently crowded with vessels, including but not limited to commercial ships and submarines used for military operations or scientific investigations. Each of these vessels and their on-board equipment produce a massive amount of data that need to be shared with potential destinations. The current popular Intelligent Ocean Convergence Platform is suggested to support oceanic services by taking advantage of the novel concepts of the Internet of Things and 5G communications. However, the processing activities are not always centrally performed within the cloud but are sometimes shifted to the edge of the network according to edge computing. In this paper, we propose a combination of software-defined networking and edge computing, where software technology is used to support interoperability of heterogeneous network technologies, as well as edge computing enables ultra-reliability, scalability, and low latency in ocean networks. This will meet the rapid growth of marine vessels’ demand for rapid computing and communication capabilities. Through the simulation of the average end-to-end delay, the efficiency of the proposed architecture based edge computing is evaluated.