Optimizations in Blockchain-enabeld Integrated Sensing, Communications, and Computing Low-altitude Networks

In this paper, we investigate the secure task offloading and computation resource allocation issues in a blockchain-enabeld integrated sensing, communications, and computing low-altitude network. Specifically, edge servers and a cloud center provides Internet of Things (IoT) devices with augmented computing power for task processing, while consortium blockchain can provide trust and secure guarantee to IoT devices in task offloading. Within the multi-access edge computing (MEC) system, we intend to minimize the task processing cost of all IoT devices by jointly optimizing the binary task offloading decision and the computation resource block allocation. Meanwhile, in the blockchain system, we first enhance the consensus procedure by proposing an advanced practical Byzantine fault tolerance (APBFT) consensus algorithm, and then conduct consensus client and primary nodes selection, thus to minimize consensus delay and fail ratio. The two systems are jointly optimized, subjecting to the computation power of edge nodes, the node number limitation of APBFT, the task processing and blockchain consensus delay, etc. To address the problem effectively, we reform it into a Markov decision process and use proximal policy optimization to dynamically learn the optimal joint solution. Simulation results demonstrate that our proposed algorithm converges fast, and performs well in total reward maximization, and IoT devices' cost, consensus delay and fail ratio minimization.