Trust aware fuzzy clustering based reliable routing in Manet

Autor: C Edwin Singh, S Sharon Priya, B Muthu Kumar, K Saravanan, A Neelima, B Gireesha
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Measurement: Sensors, Vol 33, Iss , Pp 101142- (2024)
Druh dokumentu: article
ISSN: 2665-9174
DOI: 10.1016/j.measen.2024.101142
Popis: Mobile Ad Hoc Network (MANET) is a wireless ad hoc network that can be routed over a Link Layer Ad Hoc network. In a MANET, nodes are able to freely and adaptably communicate with one another. Despite this, MANET remains vulnerable to serious security threats that are difficult to address with existing security measures. A MANET routing protocol must consider network dynamics and energy constraints, which makes it an optimization problem. Therefore, the security of MANETs must be strengthened through the development of secure routing protocols. In this research, an Optimal Fuzzy Clustering and Trust-based Routing (OFC-TR) can reduce consumption of energy, latency, and enhance network security and longevity. The proposed OFC-TR technique is achieved in three steps. The initial phase is to organize and select cluster heads using the improved Fuzzy C-means (IFCM) method, which solves the issue of unequal distribution by assigning each sensor a level of cluster membership. The nodes will be effectively clustered using this set of rules, and the best cluster head will be selected. The second segment includes Trust value calculation using a Fuzzy Cognitive Medium (FCM) which considers the values of direct and indirect trust. The third section includes the ideal routing using a Bacteria Foraging Algorithm (BFA) which is implemented for successful optimal control, harmonic estimation and the transmission loss reduction. The proposed approach is implemented in MATLAB. The efficacy of the proposed OFC-TR strategy is determined by using the assessment metrics such as network lifetime, packet delivery, and energy efficiency. The proposed method achieves a better network lifetime of 52.88 %, 44.34%, and 9.42%, than E-TDGO [32], S2ALBR [33], and 3LWT-GWO [35] respectively.
Databáze: Directory of Open Access Journals