CERLA-SFC: hierarchical orchestration of cost-efficient, reliable and low-latency SFCs in multi-access edge computing

Abstract

Ultra-Reliable Low-Latency Communication (URLLC) services in forthcoming 5G/6G networks require millisecond responsiveness and very high continuity. Multi-Access Edge Computing (MEC) combined with Network Function Virtualization (NFV) offers the needed proximity, yet orchestrating Service Function Chains (SFCs) at the edge must meet strict latency and reliability targets while limiting Operational Expenditure (OPEX). We introduce CERLA-SFC, a hierarchical, multi-objective orchestrator that unifies learning-based placement, topology-aware routing and event-driven resource allocation in a single control loop. An Advantage Actor–Critic (A2C) plane selects Virtual Network Function (VNF) locations, a shortest-path mapper embeds the inter-function links, and a Karush–Kuhn–Tucker (KKT) resource plane retunes CPU, memory and bandwidth slices on demand. A redundancy module adds selective replication, instance sharing, increasing fault tolerance at marginal cost. Instance reuse and proactive VNF redeployment reduces initialization latency and instance overhead. Trace-driven experiments on twenty heterogeneous edge servers plus one cloud node, with chains of three to six functions, validate the design. Compared with six representative baselines, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Greedy, and Proximal Policy Optimization (PPO), CERLA-SFC cuts OPEX by 10% to 53% under fixed loads of five to twenty requests per slot and by 15% to 53% when the load fluctuates between ten and twenty requests. Event-driven slicing alone lowers average cost by 51.46%, and selective redundancy trims backup expense by 22.1%. The framework maintains near-zero latency violations across all urgency classes while keeping end-to-end delay in the millisecond range.

Graphical abstract

Keywords

cost-efficient / edge computing / hierarchical orchestration / low-latency / reliability / service function chains

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