부산대학교 도서관

Marine Internet of Things (Marine IoT) has garnered increasing interest in monitoring oceanic environments. But establishing a Marine IoT system for observing and processing marine environmental data presents various challenges. These include limited underwater communication bandwidth, and uneven distribution of tasks among data-sensing devices. This paper proposes an Edge Computing-RESTful (ECR) architecture to efficiently integrate and process the substantial volume of data gathered through marine observations. 1) The ECR method is introduced for task collaborative migration, aiming to schedule and manage the tasks within the Marine IoT system. 2) Through unified scheduling and management of tasks, the edge gateway can facilitate migration, scheduling, and interaction of task loads among various edge sensing devices. The proposed dynamic and adaptive approach matches computing tasks with edge sensing devices, minimizing energy consumption and migration delay within the Marine IoT system. Simulation results validate the superiority of the proposed method for Marine IoT, showcasing improved performance metrics such as reduced time delays and lower energy consumption during task collaborative migration.