Neela Narayanan V

Computer Science

School of Computer Science and Engineering

Chennai Campus

Varadarajan V

Doyle R

Al-Shaikhli I.F

Groppe S.

Fulltext

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

Mobile Networks and Applications

The original version of this article unfortunately contained a mistake in the author group section. Author “V. Varadarajan” should be expanded to “Vijayakumar Varadarajan”. The original article has been corrected. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Correction to: Efficient Algorithm for Identification and Cache Based Discovery of Cloud Services

Vehicular Ad hoc NETworks (VANETs) possess a dominant role in the development of Intelligent Transport Systems (ITS). VANETs, due to the rapid mobility of vehicles are a highly dynamic network. In order to make the network topology suitable for effective communication, clustering algorithms are widely used. Clustering algorithms enable VANET to efficiently handle the changing topology for Medium Access Control (MAC), routing and several other applications. In this work we put forward a Reputation based Weighted Clustering protocol (RWCP) for VANETs. The RWCP is framed by taking the direction of vehicles, position, velocity, number of nearby vehicles, lane ID, and the reputation of each node into consideration for stabilizing the VANET topology. On the other hand, dealing with diverse control parameters of RWCP makes optimizing a challenging task. The work employs a multi-objective problem which takes the RWCP’s parameters as the input and aims at providing enhanced cluster lifetime, Improved packet delivery ratio and reduced cluster overhead. Multi Objective Firefly Algorithm (MOFA), an evolutionary approach is used for optimizing the RWCP’s parameters. Simulations were done using the TETCOS NetSim simulator and MOEA framework for optimization. The results are evaluated with similar evolutionary optimization techniques. Experiments were conducted with realistic maps from OpenStreet Maps and its results were compared with other multi-objective optimization techniques: Multi-objective Particle Swarm Optimization (MOPSO) and Comprehensive learning Particle Swarm Optimization (CL-PSO). The investigation proposes that, the proposed methodology performs well concerning the Mean Cluster Lifetime, Packet Delivery Ratio and Control Packer Overhead. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

A Reputation based Weighted Clustering Protocol in VANET: A Multi-objective Firefly Approach

Packet Encryption for Securing Real-Time Mobile Cloud Applications

In this paper we present an extension of existing Nearest-Neighbor heuristics to an algorithm called k-Repetitive-Nearest-Neighbor. The idea is to start with a tour of k nodes and then perform a Nearest-Neighbor search from there on. After doing this for all permutations of k nodes the result gets selected as the shortest tour found. Experimental results show that for 2-RNN the solutions quality remains relatively stable between about 10% to 40% above the optimum. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

k-RNN: Extending NN-heuristics for the TSP

Basically, the Synthetic Aperture Radar (SAR) images are often degraded due to three factors namely noise, blur and artifact. The noise is the undesirable fluctuation in a random portion of the image and is often detracts from the image. The blur will reduce the object visibility. According to the recent literatures the most dangerous effect which appear in real time images are artifacts. The shadowing effect is the best example to depict the image artifact. The presence of shadows mostly affects the vital information of an image. In the shadowing effect, the portion of the object is totally obscured or hidden from the image. In this paper, we focus the impact of image artifact such as shadow in real time images and we focus how to detect the shadowing effect. Further, this paper is devoted to removal of shadows from very high resolution (VHR) SAR images and aerial view Images. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Journal	Data powered by TypesetMobile Networks and Applications
Publisher	Data powered by TypesetSpringer Science and Business Media LLC
ISSN	1383-469X
Open Access	Yes