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

Department of Database Systems

An autonomous vehicle needs a lot of smoothly running tasks to keep it on the road without interfering with other vehicles. Lane detection and object detection are some of the most important tasks which needs to be handled by the vehicle. There are many such works in the field to perform them. Instead, this paper focuses on the real time detection of emergency vehicles such as ambulances and fire engines. This would make roads safer and more convenient for such vehicles by allowing the vehicles to make way. In the future of autonomous vehicles, this would streamline traffic as well as give priority to the vehicles that need it. The proposed solution uses a camera which will capture a live video stream, process it and detect vehicles simultaneously alerting nearby vehicles and providing a means for them to make way. © 2020 IJSTR.

World University root node

School of Computer Science and Engineering

Vellore Campus

International Journal of Scientific and Technology Research

Edge computing solution for smart city - Emergency vehicle detection

Efficient task scheduling plays a critical role in cloud computing environment. In this paper, we proposed a novel trust-based fruit fly optimisation algorithm (TFOA) for task scheduling. Even though traditional scheduling algorithms, namely first come first serve, round robin, ant colony optimisation and so on are used broadly in cloud computing process but still efficient scheduling is not achieved. In general cloud service provider desires to receive the customer task in a faster rate allocated on the most trustworthy resource by using TFOA. Simulation outcomes show that the proposed algorithm performs better than the existing transitional algorithms like round robin and particle swarm optimisation (PSO) in terms of reduced makespan and turnaround time and efficient resource utilisation. © 2020 Inderscience Enterprises Ltd.

Department of Software Systems

International Journal of Internet Manufacturing and Services

Trust-based fruit fly optimisation algorithm for task scheduling in a cloud environment

In the present paper, the contributions of dislocations and grain boundaries to the broadening of diffraction line profile have been delineated. Contribution of each factor is studied on single as well as poly crystalline ‘virtual samples’ containing different dislocation configurations generated by molecular dynamics and evaluating the simulated X-ray diffraction line profiles of these samples. Individual contributions to diffraction line profiles by different sample features, such as domain size, dislocations, grain boundaries, have been isolated by deconvoluting the evaluated diffraction line profiles. The diffraction line profiles exhibited significant asymmetry and peak splitting in the case of dislocations with predominantly edge character. It has been shown that splitting of diffraction peaks carries information about the magnitude of Burger's vectors of the dislocations. Application of the variance method based on single peak fitting and Wilkens method based on whole powder pattern fitting of line profile analysis on the computed diffraction line profiles, showed that while accurate domain size estimation was possible, there was an under estimation of dislocation density at the high dislocation density and small grain size regime considered in the present study. © 2019 Elsevier B.V.

Computational Materials Science

Influence of dislocations and grain boundaries on diffraction line profiles of nano-crystalline materials: A numerical study

In the Wireless Sensor Networks the nodes’ energy efficiency is a primary concern that has to be addressed for enhancing network lifetime. If nodes are mobile in nature, its energy consumption goes high and node lifetime gets more vulnerable with the localization adding up on the energy constraint of the battery. This is the main reason behind location estimation algorithms in WSN gaining popularity. Precision in node’s location identification assists in minimizing energy consumed by nodes which would improve network lifetime and balances load across nodes. In this paper the authors intend to propose an estimation algorithm Redefined Vector Based Glowworm Swarm Optimization (R-VBGSO) that would identify the location of nodes with minimum error rate. In this algorithm, anchor node’s location with respect to unknown nodes is identified with help of passing few signals in the form of messages that are exchanged to locate the nodes position in the network. With the simulation results it is evident that proposed algorithm enhances network lifetime significantly with reduced location estimation error. Furthermore, area of coverage through the sensor nodes is enhanced as the static nodes of such a region would approach the region in the network where the network activity is reduced. Simulation results also demonstrate that R-VBGSO based sensor placement approach will enhance the coverage with less mobility given to the sensors. © Alpha Publishers. All rights reserved.

Journal of Green Engineering

Redefined vector based glowworm swarm optimization (R-vbgso) to improve the nodes’ energy efficiency in wireless sensor networks (wsn)

Large volumes of raw data are created from the digital world every day. Acquiring useful information from these data is challenging, and it turned into a prime zone of momentum explore. More research is done in this direction. Further, in disease diagnosis, many uncertainties are involved in the information system. To handle such uncertainties, intelligent techniques are employed. In this paper, we present an integrated scheme for heart disease diagnosis. The proposed model integrates cuckoo search and rough set for inferencing decision rules. At the underlying phase, we employ a cuckoo search to discover the main features. Further, these main features are analyzed using rough set generating rules. An empirical analysis is carried out on heart disease. Besides, a comparative study is also presented. The comparative study demonstrates the feasibility of the proposed model.

VIT Unitversity

Department of Computational Intelligence

Fulltext

Journal of Medical Systems

A Hybrid Scheme for Heart Disease Diagnosis Using Rough Set and Cuckoo Search Technique

In the wireless sensor networks energy consumption is broadest and widely explored area of research. The solution for energy optimization encompasses various techniques such as efficient routing protocols, data scheduling, clustering, hardware redesigning, supervised and unsupervised network learning algorithm, and so forth. Compared with all the methods that has been so far discussed, swarm intelligence (SI) is considered to be the optimal way to find solution for reducing energy consumption as it is simple and the network formation is understood by the natural mechanism present in nature. SI approaches include ant colony optimization (ACO), particle swarm optimization, glowworm swarm optimization (GSO), and so forth. In this article, the authors provide the solution for the energy conservation problem through efficient GSO methods combined ACO. The revised beaconing glowworm swarm optimization ant colony optimization algorithm will be applied on the sensor network divided into swarms based on glowworms, the ants are introduced in the network that would parse the network by visiting the swarm heads with the principle of ACO behind it. The algorithm is tested on MATLAB 2015a for performance comparison with the HM-ACOPSO method with depicts energy conservation and efficiency in data collection. © 2020 John Wiley & Sons Ltd

Concurrency Computation

Revised beaconing glowworm swarm optimization ant colony optimization algorithm to localize nodes and optimize the energy consumed by nodes in wireless sensor networks

In wireless sensor networks (WSNs), energy optimization and the provision of security are the major design challenges. Since the wireless sensor devices are energy constrained, the issue of high energy consumption by the malicious nodes must be addressed well in order to enhance the network performance by making increased network lifetime, reduced energy consumption and delay. In the past, many researchers worked in the provision of new techniques for providing improved security to WSN in order to enhance the reliability in the routing process. However, most of the existing routing techniques are not able to achieve the required security through the use of intelligent techniques for safeguarding the sensor nodes from malicious attacks. In order to address these problems, a new fuzzy temporal clustering-based secured communication model with trust analysis and outlier detection has been developed in this research work. For this purpose, a new fuzzy temporal rule-based cluster-based routing algorithm with trust modelling and outlier detection for monitoring the nodes participating in the communication has been proposed. In addition, a fuzzy temporal rule- and distance-based outlier detection algorithm is also proposed in this paper for distinguishing the malicious nodes from other nodes within each cluster of the network and has been used in the secured routing algorithm. The proposed secure routing algorithm uses the temporal reasoning tasks of explanation-based learning and prediction as well as spatial constraints for making efficient routing decisions through the application of trust and key management techniques for performing effective authentication of nodes and thereby isolating the malicious nodes from communication through outlier detection. By applying these two proposed algorithms for communication in the proposed work, it is proved through experiments that the proposed secure routing algorithm and the outlier detection algorithm are able to perform secured and reliable routing through genuine cluster head nodes more effectively. Moreover, these two algorithms provide improved quality of service with respect to the reliability of communication, packet delivery ratio, reduction in end-to-end delay and reduced energy consumption. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Department of Information Technology

School of Information Technology and Engineering

Soft Computing

Intelligent fuzzy rule-based approach with outlier detection for secured routing in WSN

Background: Congestion can happen in WSNs while congregating the information and sending it towards the sink. It leads to increased packet delay, indiscriminate packet loss, severe fidelity degradation and wasted node energy. Objective: The aim of the proposed work is to suppress congestion using a dynamic weight assignment scheme, where each sensor node transmits the data in accordance to the weight assigned to it, thus ensuring priority fairness and minimizing packet loss. The proposed congestion control technique shall boost the overall performance of the system by supporting assured delivery of high importance events to sinks. Methods: Weights are assigned to each record based on two things, the delay in sending and receiving, and the change in value of the variables passed by the nodes. If the difference in timestamp is below a threshold (alpha) and the difference in the values is above a threshold (Beta), it gets a weight of W1, which is like a high priority data record. Similarly, if the difference in timestamp is above a threshold (gamma) and the values passed by the nodes have changed a negligible amount, that record is assigned a weight of W3, which is the least priority. Results: From the analysis, it is inferred that proposed method had a higher throughput and the throughput was equally distributed among all the participating nodes. Conclusion: The proposed method endeavours to avoid congestion by implementing an effective queuing mechanism to reinforce definitive wireless communication. © 2020 Bentham Science Publishers.

Department of Software and Systems Engineering

Recent Advances in Computer Science and Communications

A Weighted Assignment Approach Using Recommendation Routing for Congestion Control in Wireless Sensor Networks-WEAR

Wireless sensor networks are used to monitor physical or environmental conditions such as temperature and pressure as well as to study the quality of certain environmental and natural entities like air and water bodies by collecting data about the various components present in the air/water at a given spot and time. But the complete data generated by the nodes in each iteration is not always useful, as most of them give the redundant information or details which does not provide any essential information, just bulge up the amount of data being transmitted. Therefore, this paper aims to formulate an early prevention method (EPM) which not only gives a way to detect failed nodes, but also increases the overall efficiency of the network by reducing the overhead at the sink. Copyright © 2020 Inderscience Enterprises Ltd.

International Journal of Internet Technology and Secured Transactions

An early prevention method for node failure in wireless sensor networks

In Real-Time Fleet Management, vehicle routes are built dynamically according to travel durations, location of the vehicles and also customer requests which are revealed gradually. To account for such situations, algorithms which are fast and can accommodate the uncertainty are needed. We here highlights the use of parallel computing strategies for solving real-time vehicle routing problems. The vehicle routing problem is related to linear optimisation and falls under the domain of logistics and transport. Vehicle routing problems comprise of determining optimal vehicle routes according to various constraints such as the total demand should not exceed the total capacity, service durations are met The objectives of solving the Vehicle Routing Protocol varies depending upon the dynamically of the system. In general, systems, which are weakly dynamic, focus on optimising or minimising the routing costs. The systems, which are strongly dynamic, focus more on minimising the expected response time. © 2020 IEEE.