Resource Allocation and Control Co-aware Smart Computation Offloading for Blockchain-Enabled IoT

Under the scenario of big data, the remote cloud server is usually deployed for data processing and value mining, but in the face of delay-sensitive or dynamic and frequent update applications, this processing paradigm appears to be inadequate from reality. As a complement to cloud computing paradigm, fog computing has attracted great attention for which can effectively reduce task processing delay, energy and bandwidth consumptions. At the same time, fog computing based computation offloading mechanism has become a research focus, because it can effectively alleviate the processing burden of nodes and improve the experience of users. Under the fog computing paradigm, in order to better meet the requirements of delay and energy consumption for computation-intensive tasks, based on the blockchain- enabled Internet of Things (IoT) scenario, this paper proposes a resource allocation and control co-aware smart computation offloading scheme. Specifically, an optimization problem is formulated to minimize the total cost of all tasks under the constraints of delay, energy consumption, and communication and computation resources. Based on the comprehensive consideration, the component of the total cost includes the delay, energy consumption and resource mining costs; it can achieve the minimization of the total cost by jointly optimizing the communication resource, computation resource and offloading decision. In order to inspire the active participation of terminals and the fog node in the computation offloading process, and more close to the needs of the real scenario, an incentive mechanism is designed in this paper. That is, to complete the offloading of tasks, the terminal mines (rents) computation resource from the fog node as a miner and the fog node charges a certain fee according to the needed resource of terminal. For the terminals that successfully obtain the resources to complete the tasks efficiently, the system will allocate the corresponding rewards according to the occupation ratios of gained computation resource, which ensures the fairness allocation of the rewards for the successful miners. This mechanism enables that the fog node and terminals both can win benefits in the computation offloading process, which promotes their collaboration. Meanwhile, this blockchain-based incentive mechanism guarantees the security of the transaction process. For the sake of solving the above formulated optimization problem (i.e., a mixed integer nonlinear programming problem), we propose a communication, computation and control co-aware smart computation offloading algorithm (3CC-SCO). By integrating the concept of deep deterministic policy gradient (DDPG) algorithm, our algorithm designs an inverting gradient update based double actor-critic neural networks structure to improve the stable and convergence rate in the training process. At the same time, it is more suitable for solving the mixed integer optimization problem by adopting probabilistic discrete operation of continuous action output. Finally, the simulation results demonstrate that the proposed scheme can converge to the optimal value quickly, and the total cost of the proposed scheme is the lowest compared with other three benchmark schemes, for example, as compared with the best- performing scheme, i.e., deep Q-learning network (DQN) based computation offloading scheme, the total cost can be reduced by an average of 15.2%. © 2022, Science Press. All right reserved.