MicroFog : A Framework for Scalable Placement of Microservices-based IoT Applications in Federated Fog Environments

MicroFog is a scalable and extensible framework that enables Microservices-based IoT Applications placement within multi-fog multi-cloud environments using Kubernetes (as container orchestrator) and Istio (as Service Mesh)

Features :

• Multi-fog Multi-cloud microservice placement and deployment
• Seamless microservice composition across hybrid environments through automated deployment of Kubernetes and Istio resources to ensure cross-cluster service discovery and load balancing.
• Ability to integrate novel placement algorithms and load balancing policies easily.
• Support for heterogeneous cloud-native application deployment without any application-level changes.
• Compatibility with cutting-edge cloud-native technologies.
• A configurable control engine to support different approaches for application placements
  1. operation modes like centralised or distributed operation
  2. application placement modes such as event-driven or periodic placement request processing and batch or sequential placement request processing
• Distributed storage solutions to store the data required for application placement and deployment
• Rapid prototyping support
• Flexible and scalable for distributed deployment across fog and cloud clusters.

Main Components of the framework:

1. MicrFog-CE : Control Engine of the framework, responsible for executing placement algorithms and deploying the microservices-based application using Kubernetes and Istio resources
2. Data Stores : Contains data required for application placement. Consists of 3 main data sores
   1. MinIO YAML Store
   2. Redis Meta Data Store
   3. Docker Image Registry
3. Monitoring components (Prometheus, Grafana, Kiali)
4. Logging component (Grafana Loki)

Technologies used:

This repository contains three resources for running and configuring MicroFog Framework.

1. ControlEngine : Contains the code for the MicroFog-Control Engine developed as a microservice. Can be extended adn containerised to add novel placement policies, load balancing policies, etc.
2. Prototype_Setup : Contains resources required for deploying MicroFog framework (Example setup containes resources for setting up two Fog clusters and One Cloud cluster)
   1. cluster_setup : Resources required for Fog-Cloud infrastructure setup as Kubernetes and Istio installed clusters
   2. redis_setup : Resources required for setting up Redis Meta Data Store
   3. minio_setup : Resources required for setting up MinIO YAML Store
   4. control-engine-setup : Resources required for setting up MicroFog-CE
   5. kiali_setup : Resources required for setting Kiali for microservice observerbility
   6. grafana-loki-setup : Resources required for configuring Loki for log aggregation and Grafana for visualisation of logs
   7. docs : Contains guidelines explaining each setup
3. Workload_Generator : A tool for creating dummy microservices-based application workloads for evaluating novel placement polcies.
   1. dummy-micro-java : A template microservice using JAVA. It's a configurable microservice which can be as the buidling block for heterogeneous applications with diverse interaction patterns among microservices.
   2. sample-deployment-resources : We provide 5 example applications to demonstrate how to use the workload generator
   3. docs : Explains the design, architecture of the workload generator.

References :

• Samodha Pallewatta, Vassilis Kostakos, Rajkumar Buyya, MicroFog: A framework for scalable placement of microservices-based IoT applications in federated Fog environments, Journal of Systems and Software, Volume 209, 2024, 111910, ISSN 0164-1212, https://doi.org/10.1016/j.jss.2023.111910