Type II fuzzy-based clustering with improved ant colony optimization-based routing (t2fcatr) protocol for secured data transmission in manet

Mobile ad hoc networks (MANETs) include a collection of distinct and autonomous nodes that move independently and send data using wireless channels. Clustering and secure routing are treated as proficient techniques to achieve energy efficiency and network stability. Different methods have been pres...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Journal of supercomputing 2022-05, Vol.78 (7), p.9102-9120
Hauptverfasser: Nagendranth, M. V. S. S., Khanna, M. Rajesh, Krishnaraj, N., Sikkandar, Mohamed Yacin, Aboamer, Mohamed Abdelkader, Surendran, R.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Mobile ad hoc networks (MANETs) include a collection of distinct and autonomous nodes that move independently and send data using wireless channels. Clustering and secure routing are treated as proficient techniques to achieve energy efficiency and network stability. Different methods have been presented for addressing the issues of mobility and battery limited characteristics of mobile nodes in MANETs. This paper aims to develop new cluster-based secure routing protocols in MANETs. This paper presents a new Type II fuzzy-based clustering with improved ant colony optimization-based routing (T2FCATR) protocol for secured data transmission in MANETs. Initially, a new type II fuzzy-based clustering process takes place to construct the clusters. Then, the routing issue is addressed by ACO with the Tumbling technique, which offers intercluster routing from CHs to BS. In addition, a hybrid data transmission mechanism is also involved to reduce the number of data transmissions and thereby achieve energy efficiency. The performance of the T2FCATR model has been validated against several aspects. The simulation outcome implied that the T2FCATR model achieves minimum clustering overhead, minimum variations in CHs and CMs. As a whole, it can be concluded that the T2FCATR model is superior to all the compared methods under several aspects.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-021-04262-w