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

Restricted computational power, memory limitations, narrow bandwidth and energy supplied present strong limits in sensor nodes are the important points should be considered during the real time transmission of data using wireless sensor networks. Therefore, maximizing network lifetime and minimizing energy consumption are always optimization goals. To reduce the energy consumption of the sensor network during image transmission, an energy efficient image compression scheme is proposed. The image compression scheme reduces the required memory. To address the above mentioned concerns, in this paper, an approach of image transmission in WSNs, taking advantage of JPEG2000 still image compression standard and using MATLAB and C from Jasper. The features provided by JPEG2000 were achieved using techniques such as Discrete Wavelet Transform (DWT) and Embedded Block Coding with Optimized Truncation (EBCOT).Image quality and energy consumption are the two performance parameters should be considered during the image compression and transmission. Simulation results are presented and show that the proposed scheme optimizes network lifetime and reduces significantly the amount of required memory by analyzing the functional influence of each parameter of this distributed image compression algorithm. © 2005 - 2013 JATIT & LLS. All rights reserved.

Department of Embedded Technology

School of Electronics Engineering

Vellore Campus

World University root node

Journal of Theoretical and Applied Information Technology

Energy efficient distributed image compression using JPEG2000 in wireless sensor networks (WSNS)

In wireless ad hoc networks (WANets), multihop routing may result in a node knowing the content of transmissions of nearby nodes. This knowledge can be used to improve spatial reuse in the network, thereby enhancing network throughput. This paper is to develop overlapped transmission techniques based on this idea and analyze several factors affecting their performance. Then develop a MAC protocol based on the IEEE 802.11 standard to support overlapped transmission in a WANet. The resulting overlapped carrier-sense multiple access (OCSMA) protocol improves spatial reuse and end-to-end throughput in a random network scenario. © 2005 - 2012 JATIT &amp; LLS. All rights reserved.

Department of Communication Engineering

Department of Micro and Nanoelectronics

Improvement of spatial reuse and throughput using OCSMA protocol in wireless adhoc networks

WiMAX with femto-cells is a cost effective and spectrally efficient next generation broadband wireless communication systems. Femtocells are perceived as having a strong potential to provide high data-rate services with increased coverage at low cost. Femtocells will allow new services and business models to be offered to indoor users. Almost parallely, the WiMAX standard has emerged as a potential candidate technology for the future wireless networks. WiMAX femtocells are currently under development and will therefore play an important role in the world of indoor broadband wireless access. However, several aspects of this new technology, such as the access method and interference avoidance techniques play a crucial role in the amount of interference caused to co-channel deployed macrocells. Cognitive radio is a recent technology which enhances spectrum efficiency by dynamic spectrum sensing. So by the integration of WiMAX with femto-cells and cognitive radio further enhances the spectrum efficiency. The integration faces certain challenges in terms of frequency reuse, power control, interference, complexity etc. So it is required to find the optimum power that is to be transmitted from the base station and also the optimum routes with optimum channel allocation, so that the interference is reduced and frequency reuse is possible. Also by implementing multi-hop cooperative communication, complexity of the problem further increases. The constraints are mathematically modeled using stochastic network model. Three resource allocation policies are introduced and it is proved using Lyapunov theory that these policies leads to the throughput enhancement. It is showed that how relaying and co-operative relaying affect the throughput. At-last an algorithm is presented for resource allocation satisfying the objectives of the policies. © 2005 - 2012 JATIT &amp; LLS.

Throughput utility enhancement of cognitive Wimax with femto-cells

This paper focuses on the selection of cluster head using Neural Networks for optimizing the network lifetime which could be used for energy efficient routing in wireless Sensor Networks. In cluster-based routing, special nodes called cluster heads form a wireless backbone to the sink. Each cluster heads collects data from the sensors belonging to its cluster and forwards it to the sink. In heterogeneous networks, cluster heads have powerful energy devices in contrast to homogeneous networks where all nodes have uniform and limited resource energy. It is essential to avoid quick depletion of cluster heads. Hence, the cluster head role rotates, i.e., each node works as a cluster head for a limited period of time. Energy saving in these approaches can be obtained by cluster formation, cluster-head election, data aggregation at the cluster-head nodes to reduce data redundancy and thus save energy. The first part of this paper discuss the methods for clustering to improve energy efficiency of homogeneous WSN and also proposes a Neural Network (NN) based "Winner takes all" algorithm for cluster head selection for WSN. The simulation results show improved performance of NN based optimization in terms of total energy dissipation and number of alive nodes of the network system over LEACH, Static Clustering and direct methods. © EuroJournals Publishing, Inc. 2012.