Overview
Edge computing architectures propose placing software services closer to end users. This distributed placement can enable super-low latency, data-intensive applications that can benefit domains as diverse as virtual reality, gaming, and healthcare. The decision of what services to deploy in which edge is an optimisation problem called service placement. Solutions to the service placement problem must consider latency requirements and resource constraints while assigning services to edge servers in an automatic fashion. Exact, approximation, heuristics, and meta-heuristic algorithms are traditional approaches to solving such an optimisation problem. This project proposes to explore the capabilities of Large Language Models (LLMs) to make the placement decisions. The main idea is to replace current algorithms with a LLM-based agent.
