Palaniandavar Venkateswaran

An Obstacle Based Realistic Ad-Hoc Mobility Model for Social Networks

An efficient deployment of a mobile ad-hoc network (MANET) requires a realistic approach towards the mobility of the hosts who want to communicate with each other over a wireless channel. Since ad-hoc networks are driven by human requirements, instead of considering the random movement of mobile nodes, we concentrate on the social desire of the nodes for getting connected with one another and provide here a framework for the mobility model of the nodes based on Social Network Theory. In this paper, we capture the preferences in choosing destinations of pedestrian mobility pattern on the basis of Social Factor (Y F ) and try to find out the essential impact of Y F on the Pause Time of the nodes. Also, instead of considering an unobstructed terrain, we carry out our simulations in presence of obstacles which block the node movement. Thus, we present here a more realistic mobility distribution pattern. Further, a relative comparison of the proposed model with the popular Random Way-Point (RWP) Model is also done.

Genetic algorithm based efficient routing scheme for multicast networks

Due to the advent of many new multimedia applications in high speed networks, the issue of multicast routing has become more and more important. The multicast routing problem in computer networks is also known as the Steiner tree problem, which has been shown to be NP-complete. In this paper, we propose a new multicast routing scheme based on genetic algorithms (GA). To apply this algorithm to real networks, we also propose several methods for reducing the computational complexity. Computer simulations are conducted on a random graph to evaluate the performance of the proposed algorithm. Our numerical results show that the proposed algorithm is able to find a better solution than the conventional routing schemes. A very promising heuristic algorithm for the Steiner tree problem was proposed by Raywar-Smith. Finally, since many multimedia applications require multiple QoS constraints, such as delay, jitter, and packet loss, we extend the proposed algorithm to obtain a multi-constrained multicast tree.

An efficient gbest-guided Cuckoo Search algorithm for higher order two channel filter bank design

Abstract This paper proposes a new algorithm based on Gbest-guided Cuckoo Search (GCS) algorithm for the design of higher order Quadrature Mirror Filter (QMF) bank. Although the optimization of lower order filters can be performed easily by applying existing meta-heuristic optimization techniques like Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) etc., these methods are unsuccessful in searching higher order filter coefficients due to multimodality and nonlinear problem space; leads to some undesirable behaviors in filter responses like ripples in transition band, lower stop-band attenuation etc.. Comparison with other available results in the literature indicate that the proposed method exhibits an 69.02% increase in stop-band attenuation and 99.71% reduction in Perfect Reconstruction Error (PRE) of higher order filter bank. Besides, the percentage improvements in Fitness Function Evaluations (FFEs) of GCS based 55th order QMF bank design with respect to PSO, ABC and CSA are 81%, 82% and 59% respectively, and execution time is improved by 73%, 72% and 42% respectively. The simulation results also reveal that the proposed approach exhibits lowest mean and variance in different assessment parameters of filter bank and it does not require tuning of algorithmic parameters whereas in standard CSA replacement factor need to be adjusted. Further, the proposed algorithm is tested on six standard benchmark problems and complex benchmark functions from the CEC 2013 where it demonstrated significant performance improvements than other existing methods.

A novel accelerated artificial bee colony algorithm for optimal design of two dimensional FIR filter

This paper presents a novel approach for the design of two-dimensional (2D) Finite Impulse Response (FIR) filters. The design of FIR filters is generally non-differentiable, multimodal and higher dimensional; especially for 2D filters. A large number of filter coefficients are optimized either using constrained or unconstrained optimization approach. Due to the large number of constraints, traditional design methods cannot produce optimal filters required for some crucial applications. This makes meta-heuristic algorithms as good alternatives for addressing such constraints more efficiently. In order to improve the performance of 2D filters, we propose an Accelerated Artificial Bee Colony algorithm, termed as AABC algorithm. The earlier reported ABC based methods perform the modification of a single parameter of the solution in each cycle. But in this proposed AABC algorithm, we have adopted multiple parameters change of search equation at each step. This in turn improves the convergence speed of the algorithm by three times than the classical ABC algorithm and two times with respect to recently developed CABC method. In order to achieve better exploration behaviour of abandoned bees, we have also introduced a change during the initialization strategy of scout bees in the proposed AABC algorithm. The efficiency and robustness of the proposed algorithm are demonstrated by comparing its performance with classical Genetic Algorithm (GA), Particle Swarm Optimization , ABC and CABC methods.

A novel low complexity multichannel Cosine Modulated Filter Bank using IFIR technique for Nearly Perfect Reconstruction

This paper presents a design of low-complexity multichannel Nearly Perfect Reconstruction (NPR) Cosine Modulated Filter Bank (CMFB). CMFBs are used extensively because of the ease implementation and they have the advantage of high stopband attenuation. But this leads to certain limitations because it would require large number of filter coefficients and longer delays when the number of channels is more e.g. 32-band or 64-band CMFB. Large number of filter coefficients would imply that increased computational complexity. Here the prototype filter is designed using interpolated finite impulse response (IFIR) technique. The stretched factor is chosen in such a way so that computational cost will be reduced and minimizes the value of error parameters. The IFIR approach leads to reduction in stopband energy as well as Side-Lobe-Fall-off-Rate (SLFOR) in magnitude response of the prototype filter. One example has been included to illustrate the effectiveness of the proposed technique over the existing design methods. Here, an earlier approach to prototype filter design based on the Kaiser window is implemented using an IFIR approach. Savings in computational complexity and improvement in performance with respect to the previous works are shown.

An efficient statistical approach for time synchronization in wireless sensor networks

In this paper, we propose a powerful method of estimating the model parameters for time synchronization in wireless sensor networks WSNs. Joint estimation of clock offset and clock skew has been proposed in the literature using the standard regression framework. Here, we claim that simple regression poorly estimates the parameters because of the inherent correlation among successive time readings between two sensors. We propose an alternative autoregressive model and use generalized least squares for estimating the relative offset and skew parameters. A computationally efficient Bayesian approach is also proposed for the parameter estimation considering correlated readings between two sensors. The effectiveness of the proposed approach compared with the earlier approach has been investigated through extensive simulation studies. Copyright

Quadrature Mirror Filter bank with canonical signed digit representation using linear optimization algorithm

In this paper a two channel Quadrature Mirror Filter (QMF) bank is designed using linear optimization algorithm. Filter coefficients are represented in canonical signed power of two. It is observed that the use of the Canonical Signed Digit (CSD) representation of filter coefficients can simplify the hardware implementation of digital filter. The proposed method not only reduces hardware complexity but also reduces reconstruction error of original signal to a larger extent to achieve near perfect reconstruction. A refurbishment method is used to restore the CSD format of coefficients after obtaining coefficients using linear optimization algorithm.

Two-Dimensional IIR Filter Design Using Simulated Annealing Based Particle Swarm Optimization

We present a novel hybrid algorithm based on particle swarm optimization (PSO) and simulated annealing (SA) for the design of two-dimensional recursive digital filters. The proposed method, known as SA-PSO, integrates the global search ability of PSO with the local search ability of SA and offsets the weakness of each other. The acceptance criterion of Metropolis is included in the basic algorithm of PSO to increase the swarm’s diversity by accepting sometimes weaker solutions also. The experimental results reveal that the performance of the optimal filter designed by the proposed SA-PSO method is improved. Further, the convergence behavior as well as optimization accuracy of proposed method has been improved significantly and computational time is also reduced. In addition, the proposed SA-PSO method also produces the best optimal solution with lower mean and variance which indicates that the algorithm can be used more efficiently in realizing two-dimensional digital filters.

Canonical signed digit representation of Quadrature Mirror Filter using Genetic Algorithm

In this paper a two channel Quadrature Mirror Filter (QMF) bank is designed using Genetic Algorithm (GA) and coefficients of filters are represented in Canonical Signed Digit (CSD). A fresh Genetic operator is used that combines crossover and adaptive mutation to improve the convergence rate and solution quality of GA. Prototype filter is constructed using GA and the coefficients of the filter are converted to nearest signed power of two terms which reduces hardware complexity of the overall system. The proposed design of QMF is also achieved least value of Reconstruction error. The technique improves the performance of QMF with respect to its peak reconstruction error, transition bandwidth and hardware required to realize FIR digital filter to less than the complexity of 2s complement representation. During the optimization of prototype filter coefficients only nonzero CSD digits are used so that better performance is achieved.

Simulation and Performance Analysis of OLSR under Identity Spoofing Attack for Mobile Ad-Hoc Networks

Mobile ad hoc networks (MANETs) consist of a collection of wireless mobile nodes, which dynamically exchange data without fixed base station. But, in an unfriendly and uncontrolled terrain conditions, the performance of the routing protocol may deteriorate due to intrusion. Thus, secured routing is an essential requirement for MANETs, to provide protected communication between mobile nodes. In this paper, we examine security issues related to the Optimized Link State Routing (OLSR) protocol, a proactive routing protocol for MANETs. In particular, we concentrate on the identity spoofing attack in OLSR and the network performance under this attack. We enumerate a number of possible attacks against the integrity of the OLSR routing infrastructure, due to identity spoofing. The simulation in OPNET shows that the performance of the networks degrades with increase in number of malicious nodes.