Joint Computation Offloading and Resource Management for Cooperative Satellite-Aerial-Marine Internet of Things Networks
Shuang Qi, Bin Lin, Yiqin Deng, Hongyang Pan, Xu Hu

TL;DR
This paper proposes a joint optimization algorithm for satellite-aerial-MIoT networks that enhances data collection and reduces computation time, effectively supporting low-latency maritime IoT applications.
Contribution
It introduces a novel joint computation offloading and resource management algorithm tailored for cooperative satellite-aerial-MIoT networks, addressing delay constraints and system efficiency.
Findings
Data collection volume increased by up to 41.5%
Computational time reduced from 318.21s to 0.16s
Effective support for real-time maritime IoT applications
Abstract
Devices within the marine Internet of Things (MIoT) can connect to low Earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs) to facilitate low-latency data transmission and execution, as well as enhanced-capacity data storage. However, without proper traffic handling strategy, it is still difficult to effectively meet the low-latency requirements. In this paper, we consider a cooperative satellite-aerial-MIoT network (CSAMN) for maritime edge computing and maritime data storage to prioritize delay-sensitive (DS) tasks by employing mobile edge computing, while handling delay-tolerant (DT) tasks via the store-carry-forward method. Considering the delay constraints of DS tasks, we formulate a constrained joint optimization problem of maximizing satellite-collected data volume while minimizing system energy consumption by controlling four interdependent variables, including the…
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