Notice Board :

Call for Paper
Vol. 13 Issue 6

Submission Start Date:
June 01, 2026

Acceptence Notification Start:
June 10, 2026

Submission End:
June 30, 2026

Final MenuScript Due:
July 05, 2026

Publication Date:
July 10, 2026
                         Notice Board: Call for PaperVol. 13 Issue 6      Submission Start Date: June 01, 2026      Acceptence Notification Start: June 10, 2026      Submission End: June 30, 2026      Final MenuScript Due: July 05, 2026      Publication Date: July 10, 2026




Volume XIII Issue VI

Author Name
Darshana, Mohit Jain
Year Of Publication
2026
Volume and Issue
Volume 13 Issue 6
Abstract
Wireless Sensor Networks are essential for real-time monitoring applications, but their performance is often constrained by limited energy resources and inefficient routing techniques. This study proposes an improved hybrid clustering approach that integrates the Seagull Optimization Algorithm, Whale Optimization Algorithm, and the Low-Energy Adaptive Clustering Hierarchy protocol to improve energy efficiency and increase the operational lifetime of WSNs. While LEACH supports balanced energy consumption through periodic rotation of Cluster Heads (CHs), it often suffers from uneven CH distribution and workload imbalance. To overcome these limitations, the proposed LEACH-SOA-WOA model selects CHs by considering parameters such as residual energy, intra-cluster communication distance, and proximity to the base station. The SOA contributes strong global exploration inspired by seagull migration behavior, whereas the WOA enhances local search refinement using the bubble-net hunting mechanis
PaperID
2026/IJTRM/06/2026/46402

Author Name
Harsh, Mohit Jain
Year Of Publication
2026
Volume and Issue
Volume 13 Issue 6
Abstract
The Ad hoc On-Demand Distance Vector (AODV) routing protocol can be hurt by blackhole attacks and flooding attacks. Most of the time, these two types of routing attacks are linked to two major bad behaviors: flooding with fake Route Replies (RREPs) and fake Route Requests (RREQs). In this paper, we come up with a new way to use dynamic machine learning to find attacks in the AODV system. By looking at the Hello, RREQ, and RREP packets in the AODV routing protocol, the proposed solution mostly figures out three different things. Then, a mathematical model for the dynamic learning algorithm is made based on these features. After that, we make the training set of data and use these features to set a threshold for our machine learning model. This set of training data only works for N time slots, which is considered one iteration. In the next iterations, it will update the most recent valid results from the dynamic learning model and figure out a new threshold for the model.
PaperID
2026/IJTRM/06/2026/46407

Author Name
Sheetal Jariya, Mohit Jain
Year Of Publication
2026
Volume and Issue
Volume 13 Issue 6
Abstract
The emergence of the Internet of Things (IoT) and other innovative technologies has enabled the interconnection of devices worldwide, earning them the moniker "smart gadgets" due to their capabilities to send, receive, and process data. This technology is experiencing rapid growth, with a continually increasing user base. The success of IoT hinges on factors such as data transmission rates, quality of service (QoS) maintenance, and management of energy constraints in battery-operated devices. At the network level, QoS is evaluated based on metrics including end-to-end delay, throughput, jitter, and packet delivery ratio. With the proliferation of IoT devices, ensuring both device and data security in network communications becomes paramount. This paper delves into algorithms employed to safeguard the locations of source and sink nodes from potential breaches. Additionally, it investigates the impact of AODV protocols on the QoS offered by IoT networks. Malware poses significant threats
PaperID
2026/IJTRM/06/2026/46412

Author Name
Deepika Khuswah, Mohit Jain
Year Of Publication
2026
Volume and Issue
Volume 13 Issue 6
Abstract
Digital watermarking is a process used to embed a digital signal into digital media, primarily for purposes such as copyright protection and authentication. In the era of digital technology, ensuring the trustworthiness of digital images has become a significant challenge due to the ease of image manipulation. Researchers have been actively addressing this concern over the past three decades, developing various watermarking techniques tailored to specific applications. Nevertheless, creating a watermarking system that simultaneously achieves robustness and security remains a formidable task. In this dissertation, a novel digital watermarking approach is proposed, employing a combination of the Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Error Correction Codes (ECC) algorithms. This approach is complemented by the use of the random spread technique, known to enhance the quality of the resulting output images.
PaperID
2026/IJTRM/06/2026/46415