As part of the #ALLEGRO project , we developed an intelligent Greedy Resource Allocation Mechanism for efficient microservice placement across edge/cloud infrastructure. 🌐⚙️
🔍 What does it do?
Our heuristic approach balances performance and resource efficiency by assigning application microservices to infrastructure nodes using a best-fit, cost-aware, and latency-sensitive methodology.
🧩 How it works:
- Takes infrastructure graph G(V, E) and application demand graphs Gₐ(Vₐ, Eₐ) as input.
- Processes applications sequentially, assigning microservices one at a time.
- Each microservice is placed on a node that:
✅ Meets CPU & memory requirements
✅ Minimizes deployment cost & latency
✅ Respects inter-service latency constraints - If no viable node is found, the mechanism retries alternative placements in a backtracking manner.
- Resource utilization is updated dynamically after each assignment.
📊 The result?
A practical, sub-optimal yet efficient placement strategy that significantly simplifies complex resource orchestration problems in distributed computing environments.
This mechanism is a crucial part of our broader efforts in optimizing compute placement for next-gen edge applications. 🌍🖥️
💬 Interested in edge orchestration, resource management, or large-scale systems optimization? Let’s connect and discuss!
#HorizonEurope #EdgeComputing #AI #ResourceAllocation #Cloud #Microservices #ALLEGROProject #DistributedSystems #Optimization #GreedyAlgorithm #Innovation #TechResearch
