Open Access

ARTICLE

Quantum Firefly Secure Routing for Fog Based Wireless Sensor Networks

by R. Dayana^1,*, G. Maria Kalavathy²

1 Department of Computer Science and Engineering, Jeppiaar Institute of Technology, Chennai, 631604, Tamil Nadu, India
2 Department of Computer Science and Engineering, St. Joseph’s College of Engineering, Chennai, 600119, Tamil Nadu, India

* Corresponding Author: R. Dayana. Email:

Intelligent Automation & Soft Computing 2022, 31(3), 1511-1528. https://doi.org/10.32604/iasc.2022.020551

Received 29 May 2021; Accepted 20 July 2021; Issue published 09 October 2021

Abstract

Wireless Sensor Networks (WSNs) become an integral part of Internet of Things (IoT) and finds their applicability in several domains. As classical WSN faces several issues in service-based IoT applications, fog computing has been introduced in real-time, enabling local data processing and avoid raw data transmission to cloud servers. The Fog-based WSN generally involves advanced nodes, normal nodes, and some Fog Nodes (FN). Though the Fog-based WSN offers several benefits, there is a need to develop an effective trust-based secure routing protocol for data transmission among Cluster Heads (CHs) and FNs. In this view, this paper presents a Quantum Firefly Optimization based Multi-Objective Secure Routing (QFO-MOSR) protocol for Fog-based WSN. The main intention of the QFO-MOSR technique is to derive an optimal selection of routes between CHs and FNs in the network. The QFO-MOSR technique has incorporated the concepts of quantum computing and Firefly (FF) optimization algorithm inspired by the flashing behaviour of FFs. In addition, a multi-objective fitness function is derived by the QFO-MOSR technique using seven objectives: distance, inter-cluster distance, energy, delay, intra-cluster distance, link lifetime, and trust. The proposed routing technique derives a fitness function including trust factor from ensuring security. The design of the QFO-MOSR technique with a multi-objective fitness function shows the novelty of the work. To validate the performance of the QFO-MOSR technique, a series of experiments were carried out, and the results are investigated in terms of different measures. The experimental analysis ensured that the QFO-MOSR technique is superior to other methods in terms of different measures.

---

Keywords

---