Task offloading and resource allocation for blockchain-enabled mobile edge computing

Mobile edge computing (MEC) has risen as an effective approach to support ubiquitous and prosperous mobile applications. Due to the strict delay requirements and the increasingly complex application environments, the computation efficiency and security have become the bottleneck that restricts the MEC system. Here, a blockchain-enabled task offloading scheme is proposed, where the sensitive computation tasks of user terminals (UTs) can be offloaded to a blockchain-assisted base station (BS). The MEC-assisted BS helps UTs compute tasks while the blockchain consensus protocol ensures the security of the task offloading and computing process. To manage the allocation of computing resources between task offloading and blockchain consensus, the task offloading and resource allocation are formulated as a joint optimization problem. The aim of the problem is to minimize the energy consumption of UTs while guaranteeing the delay requirement. By transforming the original problem into a Markov decision process, a collective reinforcement learning algorithm is proposed to solve the problem in an online fashion. In the simulations, the convergence and the performance of the proposed scheme are evaluated. The simulation results show the effectiveness of the scheme.