CRAFT: Latency and Cost-Aware Genetic-Based Framework for Node Placement in Edge-Fog Environments

TL;DR

This paper introduces CRAFT, a genetic algorithm-based framework for optimizing node placement in edge-fog environments to reduce latency and costs in IoT systems.

Contribution

It proposes a novel, tunable node placement strategy using genetic algorithms to improve latency and cost efficiency in edge-fog computing.

Findings

Achieves up to 2.77% latency reduction

Achieves up to 31.15% cost reduction

Effective in simulation environments

Abstract

Reducing latency in the Internet of Things (IoT) is a critical concern. While cloud computing facilitates communication, it falls short of meeting real-time requirements reliably. Edge and fog computing have emerged as viable solutions by positioning computing nodes closer to end users, offering lower latency and increased processing power. An edge-fog framework comprises various components, including edge and fog nodes, whose strategic placement is crucial as it directly impacts latency and system cost. This paper presents an effective and tunable node placement strategy based on a genetic algorithm to address the optimization problem of deploying edge and fog nodes. The main objective is to minimize latency and cost through optimal node placement. Simulation results demonstrate that the proposed framework achieves up to 2.77% latency and 31.15% cost reduction.