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 have been acquisition interest as a raised area that changes how interact with the physical world. Sensor networks are scattered event-based systems that differ from traditional communication networks in several methods: Clustering is one of the key techniques which reduce energy consumption in WSN. A large class of Wireless Sensor Networks applications involves a set of isolated urban areas (e.g. building blocks) covered by sensor nodes (SNs) monitoring environmental parameters. Mobile sinks (MSs) mounted upon urban vehicles with fixed paths provide the ideal infrastructure to effectively retrieve sensory data from such isolated WSN fields. The main objective is to reduce the overall network overhead and energy expenditure associated with the multihop data retrieval process while also ensuring balanced energy consumption among SNs and prolonged network lifetime. The various algorithms are used to partition the neighboring nodes, which will sense similar sensor nodes into one cluster and wireless sensor nodes autonomously adjust control parameters after observing its environments. This is achieved through building cluster structures consisted of member nodes that route their measured data to their assigned cluster head (CH). It does can efficiently reduce redundant data transmission of cluster Head. In this paper various method has been reported and compared. © Research India Publications.

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International Journal of Applied Engineering Research

A review on cluster based data collection in wireless sensor networks

The idea of using mobile objects to gather samples from a sensor field has been proposed and it can be used to collect models from a sensor field. The civilian cars and the humans equipped with wireless communication devices can be used as mobile sinks to retrieve the gathered data from sampling points within a large sensor field. A basic task is how to gather data from the sensor nodes which serves as source for the sensor data should be energy efficient for each nodes. Juzheng Li et al 2011, implementing a method termed Band-based Directional Transmit [1] to organize the path connected with broadcasts which trigger coming from sensor nodes. The path of broadcasting the sensed data is proficiently recognized nevertheless consumes more cost for forwarding data packet. Various techniques have been discussed for mobile sampling and broadcast scheduling procedure to express a sensed data from each node at a given time period. This paper analyzes the performance of the mobile sampling and broadcasting scheduling in sensor network on the basis of transmission speed, Query result precision and Deliverability. © Research India Publications.

A survey on mobile sampling and broadcast scheduling in wireless sensor networks

Power consumption plays a vital role in modern nanometer IC design. Clocking takes a foremost part of total chip power. Clock power can reduce by replacing a number of flip-flops with Multi-bit flip-flops. This paper proposes a efficient technique for designing a multi-bit flip-flop. It has main three approaches. After identifying the mergeable flip-flops, the combination of flip-flop table provided by a library has been build. Finally the possible flip-flops can be merged. The performance has been compared with existing scheme and it can reduce 21% of clock power. © 2014 IEEE.

2014 International Conference on Electronics and Communication Systems, ICECS 2014

Effective and efficient technique for power reduction by Multi-bit flip-flops

Energy efficient and mobility information is a key problem in wireless sensor networks. Save more energy in network processing such as mobility, data aggregation and gateway deployment is a widely used technique. The large-scale deployment of wireless sensor networks and the need for data aggregation, mobility controlling and also necessitate to deploying the gateways among the network, for the purpose of balancing the load and prolonging the lifetime. In this paper, a new approximation algorithm named as Mobile Sink Clustering Algorithm (MSCA) to propose approach the mobility control of sensor nodes. The controlling methods of gateway deployment and handing over the path for mobile sink travel and collect the data from different gateways are aggregated by exploit redundancy with the objective of minimizing energy consumption in transmission. According to the recent study, it has been proved that the sink mobility along a constrained path, can improve energy effectiveness in wireless sensor networks. Due to path constrained the mobile sink has collected the data from the gateways, which are placed at random. The performance of proposed system also has been discussed. Also extend the analysis to improve the energy calculating and show the data aggregation. © 2014 IEEE.

2nd International Conference on Current Trends in Engineering and Technology, ICCTET 2014

Effective data assortment in gateways with mobile sink in sensor network

With the continuous increase of power demand, the capacities of renewable energy generation systems are being expanded. With the increased penetration of wind energy as a renewable energy source, there is a need to keep wind turbines connected to the grid during grid faults. The ability of WTGS (Wind Turbine Generation System) to remain connected to the grid during faults is termed as Fault-Ride Through capability (FRT) of the system. In this paper, the use of superconducting fault current limiter (SFCL) is proposed to improve the FRT capability of WTGS thus improving reliability of the system. A Doubly-Fed Induction Generator (DFIG) is considered as a wind-turbine generator for analysis. Detailed simulation results are obtained with and without SFCL considering the stator and rotor currents. Also, the voltage profile, real and reactive power magnitudes are analyzed. The computed results ensure that SFCL is effective in mitigating the fault current magnitude which would enhance the reliability and stability of the system as a whole.

International Journal of Engineering and Technology

Implementation of an effective fault current limiter for 1.5 MW DFIG in wind power systems

Development of mass construction, the charge of sensor nodes has reduced significantly and resource-rich sensor nodes are organized with high-technology events, for example GPS. However energy is used to measure the capability of the battery for all sensor nodes, the energy attenuation of sensor node fallout in a dull mode that is not able to communicate with other nodes, this regulates a bottleneck in a WSN. To conquer the issue, a new data collection algorithm using a mobile robot from a wireless sensor networks, this is used to collect the sensed data. It observes the present sensed data collection techniques and provides a summary of the using mobile robot in wireless sensor networks and associated research work on this area. Also comparisons are done between the various schemes to explain the advantages and restrictions. The experimental evaluation is conducted with various aspects to show the enhancement and deployment of the sensed data collecting process in wireless sensor networks. © 2005 -2014 JATIT & LLS. All rights reserved.

Journal of Theoretical and Applied Information Technology

Data collection using mobile robot in wsn:A review

In Chemical and process industries modeling of non linear systems posses a major challenging task to design engineers due to multivariable process interactions. Innovative technology for process identification is on high demand. A model identification using Neural Networks and ANFIS for the nonlinear systems in series is proposed and designed using conductivity as a measured parameter and flow rate as manipulated variable. Real time experimental data of the non linear system is used to train the neural network by back propagation training algorithm and ANFIS using Matlab. The identified model using various estimators is compared with the actual process model. The error analysis was also performed. Neural Model Predictive Controller controller (NMPC) is designed to control the level. Performance of NMPC compared with traditional PID controller © 2014 IEEE.

Souvenir of the 2014 IEEE International Advance Computing Conference, IACC 2014

Model identification of non linear systems using soft computing technique

Today cryptography is an integral part of our lives. PRNG's are used in modern cryptography. The maximal length PN-sequence (m-sequence) is the best known best-described PN-sequence whose length is equal to its period. Various PN-codes can be generated using Linear Feedback Shift Register (LFSR). The generator polynomial provides the necessary feedback taps for the LFSR circuit. The implementation of the LFSR circuit with VLSI technology makes it useful in low-power communication system design. This paper presents the performance comparison of 4 bit LFSR method with BBS and the reported results show that LFSR is more suitable for cryptographic application. © 2014 IEEE.

Performance analysis of maximum length LFSR and BBS method for cryptographic application

Recently, owing to the improvement of mass construction, the charge of sensor nodes has reduced considerably, and resource-rich sensor nodes can be prepared with high-technology procedures, for instance GPS. Nevertheless, the capability of the battery for all sensor nodes is measured inadequate in terms of energy. When energy diminution of sensor node fallout in a dead mode that is not capable to correspond with other nodes, this generates a bottleneck in a WSN. The data collection algorithm efficiently retrieved the sensed data from the dead node. Collecting sensed data using this approach will consume more time. Various techniques to approach the process of collecting sensed data using mobile robot in wireless sensor networks. In this paper, observed the latest sensed data collection methods and supply a summary in the applying automatic mobile robot with wireless sensor networks and also associated investigation work with that place. In addition side by side evaluations usually are done between various techniques to explain the advantages along with limitations. In this paper, experimental analysis has been conducted along with various factors to demonstrate the development as well as deployment of the sensed information collecting procedure inside wireless sensor networks. © IEEE 2013.

2013 International Conference on Current Trends in Engineering and Technology, ICCTET 2013

Analysis on data collection using mobile robot in wireless sensor networks

The concept of using mobile objects to gather samples from a sensor field has been not long ago proposed. Mobile objects can be used to collect models from a sensor field. Inhabitant cars and even humans geared up along with appropriate instant connection units may be used because cell basins that will reclaim sensor-data by various factors within a huge sensor subject. An essential will be the way to set up your sensor data in a fashion that will be electricity adept intended for your sensor nodes. The path of sending the sensor data is efficiently identified but consumes more cost to forward sensor data packet. Various techniques have discussed the mobile sampling and broadcast scheduling procedure for expressing a sensor node proficiently to a preferred data at a given point of time period. In this paper, the performance of the mobile sampling and broadcasting scheduling in sensor network on the basis of transmission speed, Query result precision and Deliverability is analyzed. © IEEE 2013.

Prformance analysis of mobile sampling and broadcast scheduling in wireless sensor networks

The control of smart structures is a challenging task. This paper deals with model identification and control of vibration for a cantilever beam embedded with piezoelectric patches. Model identification of the beam was done using ARMAX technique. An observer based state feedback controller and neural network predictive controller were designed for the identified model. The performance of the controllers was evaluated using MATLAB simulation. The percentage suppression of vibration varied from 85 % to 99 % for state feedback and neural network controller respectively. © 2012 IFSA.

Sensors and Transducers

Modeling and control of smart structure using soft computing method

Conductivity as a measured parameter has been used to evaluate the model of a non-linear process (spherical tank) at three different levels. The model was generated using a neural network backed propagation technique. These model parameters were used to design a neural- model predictive controller. For closed loop control of the process the algorithm were simulated in MATLAB. The performance of NMPC controller was compared with Smith Predictor controller and IMC controller based on rise time, settling time, overshoot and ISE and it was found that the NMPC controller is better suited for this process. The experimental and the model value were subjected to error analysis and the error was found to vary from 4.8 to 5.1 percent as flow rates varied from 2LPM to 5LPM. © 2012 IFSA.

Model identification and control of non linear spherical tank process using soft computing method

This paper proposes a neural network (NN) based intelligent decision making system for digital modulation classification using wavelet transform, histogram peak and higher order statistical moments. The decision making system is developed to classify the modulation schemes buried in additive white Gaussian noise and channel interference utilizing NN classifier. The performance is verified and validated for M-ary PSK, M-ary FSK, M-ary QAM and GMSK modulation schemes by examining the receiver operating characteristics, confusion matrix and probability of correct identification for various signal-to-noise ratios (SNR) and also for various decision parameters. The performance of the proposed system also has been compared with existing methods and found that this method can be considered as reliable classification method for Digital Modulation Scheme with lower SNR upto - 5 dB. © 2008 Springer Science+Business Media, LLC.

Wireless Personal Communications

Intelligent decision making system for digital modulation scheme classification in software radio using wavelet transform and higher order statistical moments

A generalized Digital Modulation Identification algorithm for adaptive demodulator has been developed and presented in this paper. The algorithm developed is verified using wavelet Transform and histogram computation to identify QPSK and QAM with GMSK and M-ary FSK modulations. It has been found that the histogram peaks simplifies the procedure for identification. The simulated results show that the correct modulation identification is possible to a lower bound of 5 dB and 12 dB for GMSK and QPSK respectively. When SNR is above 5 dB the throughput of the proposed algorithm is more than 97.8%. The receiver operating characteristics (ROC) has been computed to measure the performance of the proposed algorithm and the analysis shows that the probability of detection (Pd) drops rapidly when SNR is 5 dB and probability of false alarm (Pf) is smaller than 0.3. The performance of the proposed algorithm has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.

World Academy of Science, Engineering and Technology

Modulation identification algorithm for adaptive demodulator in software defined radios using wavelet transform

In this study, a modulation identification algorithm for identifying M-ary Shift Keying is developed and described using wavelet Transform to examine histogram peak and 8th order statistical moment. The simulated results show that the exact modulation scheme can be identified for lower SNR. The performance was examined for Additive White Gaussian Noise (AWGN) channel based on the confusion matrix, throughput of the algorithm and the Receiver Operating Characteristics (ROC). When SNR is above 3 dB, the probability of detection is proved to be more than 0.984. The parameters of the developed algorithm has been compared with existing algorithms and found that the proposed algorithm can be considered to be the suitable identification method for M-ary Shift Keying with lower SNR (signal-to-noise ratio). © 2008 Asian Network for Scientific Information.

Journal of Applied Sciences

M-ary shift keying modulation scheme identification algorithm using wavelet transform and higher order statistical moment

This paper presents an Automatic Modulation Identification (AMI) algorithm using Wavelet transform for distinguishing QPSK and GMSK in adaptive demodulator. The developed algorithm has been tested by introducing Additive White Gaussian Noise (AWGN) in the modulated signal. It has been found that the identification of QPSK and GMSK using histogram peaks simplifies the procedure. The performance of the proposed AMI algorithm has been computed by estimating the Bit Error Rate (BER) and reconstruction efficiency. This shows that the correct modulation identification is possible to a lower bound of 15 dB and 6 dB for GMSK and QPSK respectively. © 2007 IEEE.

Proceedings of ICSCN 2007: International Conference on Signal Processing Communications and Networking

Automatic modulation identification of QPSK and GMSK using wavelet transform for adaptive demodulator in SDR

This paper presents a new adaptive algorithm for speech Compression using Cosine Packet Transform. The proposed algorithm uses packet decomposition, which reduces a computational complexity of a system. This paper compare the compression ratio of methods using Wavelet Transform, Cosine Transform, Wavelet Packet Transform and proposed adaptive algorithm using Cosine Packet Transform for different speech signal samples. The mean compression ratio is calculated for all the methods and compared. The implemented results show that the proposed compression algorithm gives the better performance for speech signals. ©2007 IEEE.