Latency-Sensitive and Resource-Efficient Parallel VNF Placement in Mobile Edge Networks: A Dynamic Graph Weighting Approach

Abstract

Mobile edge networks delivers low-latency, high-quality services by deploying Virtual Network Functions (VNFs) on resource-constrained edge nodes. However, sequential VNF processing incurs significant latency, while reusing existing VNFs under heavy demand may force requests onto longer paths, increasing bandwidth consumption. Parallelization combined with efficient VNF placement is therefore essential, yet these decisions are inherently coupled and may lead to suboptimal deployments if optimized separately. To address this challenge, this paper proposes a unified framework that jointly optimizes VNF parallelization and placement to minimize latency and resource consumption. The framework constructs a Dependency-Deployment Graph (DPG) that integrates VNF functional dependencies with Mobile Edge Networks topology. By assigning latency and resource weights to DPG nodes and edges, the framework captures the interplay between transmission delay, resource usage, parallelization, and deployment decisions. To efficiently explore the solution space, iterative algorithms progressively refine candidate configurations by pruning inferior solutions and focusing on promising regions of the search space. Experimental evaluations across diverse network configurations demonstrate that the proposed framework achieves promising improvements in reducing service latency and resource consumption compared with representative baseline methods. The results further indicate the effectiveness and robustness of the proposed joint parallelization and placement strategy under the tested heterogeneous edge computing scenarios.