Heterogeneous Event-driven Scheduling for Blockchain-based Serverless Edge Computing
Wanqing Long, Hancheng Lu, Baolin Chong, Cheng Guo · 2024
Serverless computing is gaining popularity due to its "pay-per-use" model and simplified management. Benefiting from the common features of Internet of Things (IoT), the adaptation of serverless in edge computing is extensively researched. To protect nodes in serverless edge computing from potential attacks, blockchain technology plays a crucial role. Considering that the computing time of a single serverless function can be less than the time for a blockchain to generate a block, the blockchain component requires significant computing and bandwidth resources to ensure the generation efficiency of blocks matches the execution efficiency of serverless functions. However, existing studies on minimizing the completion time (a.k.a. makespan) of application workflows in serverless edge computing have never considered the impact brought by blockchain, leading to an imbalance in the resource allocation between the computing and blockchain components. To address this, we propose a Heterogeneous Event-driven Scheduling (HEDS) mechanism, which employs a fine-grained CPU al-location scheme and an event-driven approach, to make the adjustment of resource allocation between the computing and blockchain components more flexible and expeditious, leading to improving the utilization of both computing and bandwidth resources. Meanwhile, a Multi-agent Double Deep Q-network (MADDQN) algorithm is proposed to help agents minimize the makespan while balancing the resource consumption in the computing and blockchain components. Simulation results demonstrate that HEDS with MADDQN outperforms existing algorithms in terms of average makespan over different numbers of functions and nodes while satisfying the latency requirements of block generation.