Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Wireless Sensor Networks are developed as a vital tool for monitoring diverse real time applications such as environmental monitoring factors, health care, wide area surveillance, and many more. Though the advantages of WSNs are plenty, the present challenge is to gain effective control over the depleting battery power and the network lifetime. Recent researches have proved that the energy consumption can be minimized if effective clustering mechanisms are incorporated. This paper proposes HOCK and HECK - novel energy efficient clustering algorithms to increase the network lifetime for homogeneous and heterogeneous environments, respectively. Both these algorithms are built using Krill herd and Cuckoo search. While the optimal cluster centroid positions are computed using the Krill herd algorithm, and the Cuckoo search is applied to select the optimal cluster heads. The performance of the HOCK algorithm is evaluated by varying base station locations and node density. To evaluate the HECK algorithm, two and three level heterogeneity are considered. The simulation results show that the proposed protocol is more effective in improving the network lifetime of WSNs compared to other existing methods such as GAECH, Hybrid HSAPSO, and ESO-LEACH. © 2021, Springer-Verlag GmbH Germany, part of Springer Nature.

Department of Software Systems

School of Computer Science and Engineering

Vellore Campus

Department of Analytics

Evolutionary Intelligence

A hybrid approach to energy efficient clustering and routing in wireless sensor networks

In recent years, Heterogeneous Wireless Sensor Networks are widely used to perform a variety of real-time applications. Since sensor nodes are battery powered, developing an energy efficient algorithm to increase the network life time is challenging. This paper proposes a cluster based mechanism, namely, Augmented EDEEC, to improve the network life time. This algorithm is obtained by modifying the distance metric and level of heterogeneity in the existing Protocol. This new protocol exhibits 1.25 times more network lifetime than the existing Distributed Energy Efficient Clustering algorithms. The results are benchmarked with the energy efficient clustering protocols like DEEC, DDEEC and EDEEC. © 2020, Springer Nature Switzerland AG.

Advances in Intelligent Systems and Computing Intelligent Systems Design and Applications

An Augmented Algorithm for Energy Efficient Clustering

Heterogeneous Wireless Sensor Networks are widely used to perform real-time applications like military surveillance, environmental monitoring and health care systems. Since sensor nodes are battery powered, developing an energy efficient algorithm to increase the network life time is a challenging problem. This paper proposes a multilevel energy efficient protocol, namely EM-AEDEEC, in which we extend the heterogeneity up to k-level. The protocol is analyzed for network life time and network stability. The experiments are carried out in a simulated grid of size 100 100 with varying number of sensor nodes. The simulation results demonstrate that with the increase in initial energy from 0.25 to 0.5 to 1.0 Joules, the stability of the network is almost doubled in the case of Euclidean distance measure and an increase of 7% network life time with Manhattan distance. © 2019 MIR Labs.

International Journal of Computer Information Systems and Industrial Management Applications

Analysis of EM-AEDEEC protocol at various levels of heterogeneity

In Scientific field, the data collection resulted into large scale growth by continuous additions of data. The characteristics such as velocity, variety, volume, etc. make the collected data as Big data. Analysis of such data uses various data mining techniques. Clustering is one among them and it is an unsupervised learning technique used for statistical data in bioinformatics, social networks, etc. Among various clustering techniques the K -means clustering is a common and predominant algorithm. However, the accuracy of original K-means algorithm heavily depends on centroids at the beginning and it has high computational complexity. In this paper we present an empirical study on enhanced k-means algorithm for high accuracy clustering with the initial centroids selection in an improved manner. © Research India Publications.

Department of Information Security

Department of Computational Intelligence

World University root node

International Journal of Applied Engineering Research

Case study on enhanced K-means algorithm for bioinformatics data clustering

Background: Cryptanalytic attacks like Brute Force and Dictionary Attacks over password-only remote login services are widespread now-a-days. The major challenge is to allow the genuine users to login by preventing such attacks. Method: PGRP (Password Guessing Resistant Protocol) and PCCP (Persuasive Cued Click Points). Results: It gives a security mechanism for preventing the fraudulent user from using the system and also tries to identify the details of fake user. Application: User Authentication Based Systems

Department of Software and Systems Engineering

School of Information Technology and Engineering

Indian Journal of Science and Technology

Online Guessing Attacks – A Prevention using PGRP and PCCP

The Next generation Wireless Networks(NGN) is envisage to integrate various heterogeneous wireless networks. The major challenging issue of the next generation wireless networks is to provide a quality of service(QOS) which is guaranteed and quality of experience(QOE).This specifies the QOS provided by the network & the QOS experienced by the user. The efficiency of the next generation wireless networks mainly depends upon the architecture and design of the future wireless networks. The most challenging task is to design various algorithms which provide best quality of service (QOS) and to efficiently support the mechanism of vertical handoff so as to provide seamless continuity of the calls even when the user is moving from one network to the other. This paper elucidates a comprehensive survey of the performance of various vertical handoff algorithms to decide the mechanism of selecting the best network among several available networks is discussed. A new algorithm Maximum Network Utility-Vertical Hand Off (MNU-VHO)algorithm is proposed. The investigation and results suggests that the proposed algorithm has better performance than other algorithms because it is more efficient, simple to implement and more dynamic (application oriented). © Research India Publications.