Near Optimal Locality-Aware Task Allocation towards Stable Blockchain-Based MEC System: A Potential Game Approach

Blockchain-based mobile edge computing (BMEC), a promising distributed computing paradigm by intergrating the mobile edge computing and blockchain, is to enable to secure latency-sensitive mobile applications. Due to limited resources of mobile devices, the efficient task allocation is a key to realize various BMEC applications. In such task allocation process, it is a significant challenge to guarantee incentive-compatibility with satisfactory system stability while enabling flexible task offloading under the locality constraints. To conquer this challenge, we propose a near optimal locality-aware task allocation mechanism over smart contract to enable automatic and efficient transactions in MEC system. First, we perform a preference-based selection of smart contracts to obtain the highest estimated utility. Second, we develop the minimum delay task graph partitioning algorithm to determine the optimal task offloading solution under different resource bundles. Then, we propose a multi-stage task matching game with the second lowest cost strategy to determine the edge server selection and decide the price for the implemented task. Moreover, we propose a social welfare-driven consensus mechanism to enable verified transaction and fair block allocation in a reward-free way. Strict theoretical analysis demonstrates that our mechanism guarantees incentive compatibility, Nash Equilibrium, and stable near optimal solution. Extensive simulation results demonstrate the effectiveness and efficiency of our mechanism.