Work

Relay Node Selection Based on Adaptive Neuro- Fuzzy Inference System in Delay Tolerant Networks

Year: 2025

Type: article

Abstract: Delay tolerant networks (DTNs) are a type of mobile ad hoc network without the infrastructure in which a complete path from a source node to a destination does not exist always; so routing is the most important challenge in these networks. In recent years many routing methods in delay tolerant networks have been proposed. In previous methods, the copies were blindly forwarded to mobile nodes; finally, it caused a reduction in delivery rate and wasting of network resources. So it can be said choosing an appropriate relay node is an important challenge. In this paper, a novel Relay Node Selection by Adaptive Neuro-Fuzzy Inference System (SR-ANFIS) is proposed to improve the Delivery Ratio. In order to calculate the Chance of Receiving (CR), the parameters, Encounter Frequent (EF) to the destination, Selfishness Measure(SM), Closeness-Centrality (CC), Reach-Centrality (RC) are used as inputs of Adaptive Neuro-Fuzzy Inference System(ANFIS). Simulation results illustrate that the SR-ANFIS achieves better results in delivery ratio, delivery latency, message drop, overhead ratio and hop count than other exiting DTN routings.

Source: The International journal of networked and distributed computing

DOI: 10.1007/s44227-025-00085-w

Authors: Fatemeh Semsarieh, Nahideh Derakhshanfard

Institution: Islamic Azad University of Tabriz

Language: English

Topic: Opportunistic and Delay-Tolerant Networks

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,390