Balwinder Singh Dhaliwal

Design of fault tolearnt full Adder/Subtarctor using reversible gates

Reversible logic gates are in demand for the upcoming future computing technologies. Reversible logic is emerging as an important research area having its application in diverse fields such as low power CMOS design. The paper proposes the design of full Adder/Subtractor circuit using fault tolerant reversible logic gates. The design can work singly as a reversible Full Adder/Subtractor unit. It is a parity preserving reversible adder cell, that is, the parity of the inputs matches the parity of the outputs. The proposed parity preserving reversible adder can be used to synthesize any arbitrary Boolean function. It allows any fault that affects no more than a single signal readily detectable at the circuits primary outputs. The proposed design offers less hardware complexity and is efficient in terms of gate count, garbage outputs and constant inputs than the existing counterparts.

Secure Trust Based Key Management Routing Framework for Wireless Sensor Networks

Security is always a major concern in wireless sensor networks (WSNs). Several trust based routing protocols are designed that play an important role in enhancing the performance of a wireless network. However they still have some disadvantages like limited energy resources, susceptibility to physical capture, and little protection against various attacks due to insecure wireless communication channels. This paper presents a secure trust based key management (STKF) routing framework that establishes a secure trustworthy route depending upon the present and past node to node interactions. This route is then updated by isolating the malicious or compromised nodes from the route, if any, and a dedicated link is created between every pair of nodes in the selected route with the help of “” composite random key predistribution scheme (RKPS) to ensure data delivery from source to destination. The performance of trust aware secure routing framework (TSRF) is compared with the proposed routing scheme. The results indicate that STKF provides an effective mechanism for finding out a secure route with better trustworthiness than TSRF which avoids the data dropping, thereby increasing the data delivery ratio. Also the distance required to reach the destination in the proposed protocol is less hence effectively utilizing the resources.

Performance comparison of bio-inspired optimization algorithms for Sierpinski gasket fractal antenna design

The Sierpinski gasket fractal antenna is most popular structure in the domain of fractal antennas. This fractal antenna has multi-band performance, and hence, the design of this antenna for the desired frequencies is a challenging problem. The artificial intelligence tools like artificial neural networks, fuzzy logic systems, bio-inspired optimization techniques are appropriate to provide accurate design solution in such cases. In this paper, three most popular bio-inspired optimization algorithms: genetic algorithms, particle swarm optimization (PSO), and bacterial foraging optimization, have been proposed to solve the design issues of Sierpinski gasket pre-fractal antenna. Their performances are analyzed and are compared with the experimental results. A simplified expression for calculation of resonant frequency of Sierpinski gasket pre-fractal antenna is proposed and is used as the objective function. Finally, the effectiveness is compared on the basis of three different measures: mean absolute percentage error, the average time taken by the models to evaluate the results, and the coefficient of correlation. The results indicate that the PSO algorithm is most suitable for this type of antenna.

Sensor node deployment using Bacterial Foraging Optimization

The prime objective behind optimized sensor deployment is to reduce sensing range of a sensor node. Proper positioning of sensor nodes leads to increased lifetime, better coverage and more connectivity among nodes. In this paper, the sensor deployment problem has been considered as a clustered approach and the solution to the optimal co-ordinates of the sensor deployment has been obtained using Bacterial Foraging Optimization.

Artificial neural network analysis of sierpinski gasket fractal antenna: a low cost alternative to experimentation

Artificial neural networks due to their general-purpose nature are used to solve problems in diverse fields. Artificial neural networks (ANNs) are very useful for fractal antenna analysis as the development of mathematical models of such antennas is very difficult due to complex shapes and geometries. As such empirical approach doing experiments is costly and time consuming, in this paper, application of artificial neural networks analysis is presented taking the Sierpinski gasket fractal antenna as an example. The performance of three different types of networks is evaluated and the best network for this type of applications has been proposed. The comparison of ANN results with experimental results validates that this technique is an alternative to experimental analysis. This low cost method of antenna analysis will be very useful to understand various aspects of fractal antennas.

Performance evaluation of Artificial Neural Networks in microstrip fractal antenna parameter estimation

Artificial Neural Networks have been recently used for the design and analysis of fractal antennas. The performance of various types of networks has not been yet explored for these antennas. This paper evaluates the performance of three types of neural networks: Back Propagation Neural Network (BPNN), Radial Basis Function Neural Network (RBFNN), and Generalized Regression Neural Networks (GRNN) for parameter estimation of Microstrip Fractal Antenna. Depending on the values of mean percentage error and time taken for training of each type, it has been concluded that the GRNN has best performance among these three networks.

Implementation of modified variable step size least mean square algorithm in LabVIEW

This paper presents implementation of modified variable step size least mean square adaptive algorithm using adaptive filter toolkit of LabVIEW software. User interface is designed using LabVIEW to obtain learning curve for adaptive algorithm. Simulation results are presented to compare the performance of the modified algorithm with the standard least mean square algorithms, Kwongs variable step size algorithm and robust variable step size algorithm. The results show that modified algorithm has good speed of convergence over the existing algorithms.

A new triple band hybrid fractal boundary antenna

Fractal structures have greatly advantageous properties of self-similarity and space filling which enhance the radiation efficiency and play a pivotal role in the achievement of multiple frequency resonance. A new triple band hybrid fractal boundary antenna has been proposed in this paper having size 39.4×48.4 mm2. The fractal boundary shape has been designed using the combination of Koch and Minkowski curve. The proposed antenna has been simulated using IE3D electromagnetic software and the radiation characteristics obtained henceforth are studied in detail. The proposed antenna is designed by applying the Minkowski curve and Koch curve on the boundary of the patch and it gives triple band response with sufficient gain and high radiation efficiency. The simulation results are verified experimentally.

Small size dual-band fractal boundary split ring planar antenna

In last decade, a number of microstrip patch antennas based on fractal geometry have been proposed. Recently, some applications employing the fractal geometry as boundary of microstrip antennas are also proposed. In this paper, Minkowski curve has been used as boundary of a square split ring antenna. The simulated and experimental results of the proposed antenna have shown dual band behavior. Also a size reduction of more than 65% is achieved by using the proposed fractal boundary split ring geometry.

Compact crown circular pre-fractal antenna and its analysis using GA based selective ANN ensemble

The design of miniaturized antennas using the fractal geometry concept is a latest trend. A new compact size circular based fractal antenna is presented in this paper. As the mathematical formulas are not available for the analysis of fractal antennas, so the development of a genetic algorithm based ANN ensemble for proposed antenna is also described. The comparison of the results of the proposed approach with the simulation and measured results shows a good agreement. A size miniaturization of 24.34% is achieved in the presented work.