Technology Requirements - COS301-SE-2025/Swift-Signals GitHub Wiki

๐Ÿ› ๏ธ Swift Signals Technology Requirements

This document outlines the required technologies, tools, and environments used in the development and deployment of the Swift Signals traffic optimization system.

๐Ÿงฉ System Overview

Swift Signals is a web-based traffic simulation and optimization platform that helps traffic planners configure and optimize intersection parameters using simulations and AI. The system is designed using a microservices architecture with modern technologies to ensure scalability, maintainability, and performance.

โš™๏ธ Technology Stack

๐Ÿ–ฅ๏ธ Frontend

  • Framework: React
  • Build Tool: Vite
  • Language: TypeScript
  • Styling: Tailwind CSS

๐ŸŒ API Gateway

  • Language: Go
  • Function: Request routing, load balancing, authentication validation, and service aggregation
  • Communication: HTTP/gRPC

๐Ÿ‘ค User Authentication Service

  • Language: Go
  • Authentication: JWT-based login and signup
  • Database: MongoDB

๐Ÿšฆ Simulation Service

  • Language: Go + Python (via SUMO integration)
  • Simulation Engine: SUMO (Simulation of Urban MObility)
  • Function: Run traffic scenarios with configurable intersection parameters

โฑ๏ธ Optimization Service

  • Language: Go
  • Techniques: Swarm Optimisation Algorithms
  • Function: Optimise signal timing based on traffic flow, intersection type, etc.

๐Ÿ“Š Metrics Service

  • Language: Go
  • Function: Collect statistics (simulation duration, optimization success rate, resource usage)
  • Database: Prometheus + local time-series DB

๐Ÿง  Controller Service

  • Language: Go
  • Function: Orchestrates flow between simulation and AI services

๐Ÿ”— Communication

  • Protocol: gRPC for inter-service communication
  • Gateway Interface: REST (user-facing) with JSON
  • API Documentation: Protobuf definitions (.proto) for all services, linked in the Service Contracts

๐Ÿงช Development & Deployment

๐Ÿ–ฅ๏ธ Local Development

  • Platform: Minikube
  • Containerization: Docker
  • Orchestration: Kubernetes
  • Dev Tools: Tilt, Skaffold (optional for hot-reload / sync)

โ˜๏ธ Target Deployment Environments

  • Option 1: On-premises server at client location
  • Option 2: Cloud-hosted (e.g., GCP, AWS, DigitalOcean)
  • Must support:
    • Kubernetes
    • Docker Registry
    • Load balancing and ingress controllers

๐Ÿ“‹ Observability

๐Ÿž Logging

  • In-Service Logging: Zap (Go), Logrus (Go), or Python logging
  • Log Aggregation: Grafana Loki
  • Log Collection: Promtail or Fluent Bit

๐Ÿ“ˆ Monitoring & Dashboards

  • Monitoring: Prometheus
  • Dashboards: Grafana
  • Metrics Exporters: prometheus/client_golang for Go services

๐Ÿงฑ Design Principles

  • Open Source Compliance: All core components are based on open-source libraries (e.g., SUMO, Prometheus, Grafana)
  • Portability: Easily deployable on any compliant Kubernetes cluster
  • Extensibility: Easily add support for new intersection types, AI models, or metrics
  • Security: JWT authentication, RBAC support, secure gRPC with optional TLS