Secure Computation Offloading for Marine IoT: An Energy-Efficient Design via Cooperative Jamming

Abstract

In smart ocean, the Marine Internet of Things (M-IoT) is ubiquitously used for data acquisition, communication connections, task computation, and so on. However, high-efficient energy consumption and secure yet low-latency transmission are subject to IoT devices' computation capacity and transmit power limitation, as well as wireless communication's broadcast characteristics. In this paper, we investigate the secure computation offloading in M-IoT with the assistance of unmanned surface vehicles (USVs) subject to the eavesdropping attack. In particular, we consider a scenario in which USVs are firstly scheduled to set up a high-quality communication link to the high altitude platform (HAP) and then exploited to provide cooperative jamming for the communication security at the physical layer when the HAP is performing computation offloading. We jointly optimize the USVs' positions, the duration of data uploading, the workload offloaded by HAP, the HAP's transmission power, and each USV's jamming signal power to minimize the system-wise energy consumption for completing the total workloads under the latency constraint. Despite the non-convexity, we decompose the problem vertically into a top problem that optimizes the USVs' positions and a bottom problem that optimizes the other variables. The Polyblock outer Approximation and bisection Search based algorithm (PAS-Algorithm) is proposed to alternatively optimize the variables in the bottom problem. And the Code bAsed croSs Entropy algorithm (CASE-Algorithm) is proposed to obtain the suboptimal solution to the formulated joint optimization problem. Numerical results validate the accuracy and effectiveness of our algorithms as well as the performance of optimizing the total energy consumption compared with the benchmark algorithms