Title: Probabilistic routing protocol with firefly particle swarm optimisation for delay tolerant networks enhanced with chaos theory
Authors: Siddhant Banyal; Kartik Krishna Bhardwaj; Deepak Kumar Sharma
Addresses: Department of Instrumentation and Control, Netaji Subhas University of Technology, New Delhi, India; Formerly: Netaji Subhas Institute of Technology, India ' Department of Instrumentation and Control, Netaji Subhas University of Technology, New Delhi, India; Formerly: Netaji Subhas Institute of Technology, India ' Department of Information Technology, Netaji Subhas University of Technology, New Delhi, India; Formerly: Netaji Subhas Institute of Technology, India
Abstract: In this paper, we propose a proactive routing paradigm for delay tolerant networks (DTN) using probabilistic routing implemented via firefly particle swarm optimisation and optimised by chaos maps. DTN is a specific class of networks where there is absence of an end to end connectivity among nodes and are characterised by long or variable delays, asymmetric data rates and high error rates. The routing scheme considers the constrained environment of DTN nodes and implements a meta-heuristic paradigm to facilitate data transfer. The chaos maps further enhance the probabilistic routing parameters controlling brightness and ageing by randomising them. The protocol is implemented on ONE simulator and its performance is compared with traditional DTN routing schemes across delivery probability, average latency, overhead ratio and buffer utilisation. The simulation results show that our proposed protocol performs better than its contemporary ant PRoPHET protocol across the various performance metrics.
Keywords: chaotic mapping; delay tolerant network; DTN; firefly algorithm; nature inspired algorithm; NIA; networks; opportunistic networks; probabilistic routing; routing; store; forward.
International Journal of Innovative Computing and Applications, 2021 Vol.12 No.2/3, pp.123 - 133
Received: 30 Nov 2019
Accepted: 24 Feb 2020
Published online: 18 Mar 2021 *