Reliability-Aware SFC Scheduling in Container Environment via Priority-Based Node Selection

Advances in containerization technology and edge device performance enable applications to run on a wide range of devices through virtualization, enhancing service quality in decentralized edge networks. However, edge devices often lack the computational power of cloud infrastructure and may experience connection fluctuations, which makes node reliability crucial when providing Virtual Network Functions (VNFs). To provide Service Function Chain (SFC) which combines a series of ordered VNFs, it is necessary to determine the redundancy of VNFs to meet reliability requirement and decide whether to deal with these VNF requests immediately or defer them. Therefore, this paper addresses this problem and formulates it as a reliability-aware SFC scheduling problem in container environment (RASCE) and prove it to be NP-hard. To solve this problem, we propose a reliability-aware scheduling algorithm via priority-based node selection (SSAP) using Deep Reinforcement Learning (DRL), which consists of long-task prioritization redundancy strategy considering dynamic node reliability, priority-based node selection, and SFC scheduling based on DRL. The simulation demonstrates that our approach can enhance the success rate by a minimum of 5.78% in comparison to the state-of-the-art algorithm.