Paramart: Parallel Resource Allocation Based on Blockchain Sharding for Edge-Cloud Services

Edge computing has evolved to enable mobile applications to run in an efficient and cost-effective manner at explosive-growing edge nodes. Under this paradigm, a new business resource trading market has emerged to provide edge-cloud services, offering a convenient way for mobile users to obtain resources from distributed computing power providers (CPPs). Blockchain, as a promising technology, provides a reliable platform for multi-party resource transactions (TXs), enabling secure and reliable computing services. Notably, the distributed CPPs not only offer mobile services but also act as blockchain nodes to maintain the stability of TXs. In this case, there exist certain bottlenecks in the blockchain-enabled edge-cloud resource market, such as limited scalability, inefficient resource allocation, and large system cost. In this paper, assisted by the permissioned blockchain, we study the fundamental problem of resource allocation by minimizing the system cost to handle mobile services and blockchain TXs in parallel. We first partition the Practical Byzantine Fault Tolerant (PBFT) consensus by hierarchical sharding to improve the scalability and ensure the security of the blockchain system. Next, based on the optimal sharding strategies, we formulate the parallel resource allocation as a multi-scale Lyapunov optimization problem, and develop a dual-alternation actor-critic with an attention mechanism (DA3C) algorithm to solve it. We evaluate the performance of the
Paramart
using trace-driven experiments. Simulation results demonstrate the superiority of our proposed framework as compared with the benchmark algorithms.