Informatics Publishing Limited

P. T. V. Bhuvaneswari ¹, V. Vaidehi ¹

Affiliations
1 Department of Electronics Engineering, Madras Institute Technology, Anna University, Chennai, IN

Abstract

In this paper, we present a survey of various improvements made in LEACH that has produced different routing protocols for WSNs and highlight their features. Further this paper also addresses the other challenges of cluster-based routing protocols that need to be considered in future designs.

Keywords

Wireless Sensor Network, Leach, Clustering

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Jiju S. John ¹, R. Kayalvizhi ¹, V. Vaidehi ¹

Affiliations
1 Dept. of Electronics Engineering, MIT Campus, Anna University, Chennai, IN

Abstract

Wireless Sensor Networks deployed for various kinds of applications are prone to large number of attacks. Among various kinds of attacks, clone attack is predominant where a node pretends to have multiple identities and act as a legitimate node further launching several other attacks by taking control over the network. The existing solutions are not satisfactory as they consume large energy and memory. The proposed work deals with the implementation of cluster based mechanism for the detection of clone node otherwise known as node replication attacks. It shows that the proposed method has more detection probability and consumes less energy than the existing distributed approach.

Keywords

Clone Attack, Clustering, Cost Estimation, RED.

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S. Indira Gandhi ¹, V. Vaidehi ¹, Xavier Fernando ²

Affiliations
1 Madras Institute of Technology, Anna University, Chrompet–600044, IN
2 Department of Electrical Engineering, Ryerson University, Toronto, CA

Abstract

Effective Routing and Wavelength Assignment are the two important criteria used for improving the blocking performance in optical Wavelength Division Multiplexing (WDM) networks. Due to the increase in data traffic in the internet scenario, the existing algorithms for effective wavelength assignment and routing are not adequate to provide an optimal level of performance. Hence, the need arises to propose efficient routing and wavelength assignment algorithms to meet the requirements of different types of networks that are part of the internet. In this paper, Hop Routing Algorithm (HRA) has been proposed to improve the Overlay Routing Algorithm (ORA) for Automatically Switched Optical Networks (ASON). The existing ORA allocates long light path for each connection request. This is not an efficient method for utilizing the light path if the connection request requires only minimum bandwidth. The proposed HRA checks the bandwidth requirement of the connection request and compares it with link bandwidth. If the bandwidth of the connection request is lower than the available link bandwidth, then HRA allocates a light path for the next hop. Thus, longer light path for each small connection request is restricted by HRA and it uses minimum number of wavelengths. It is observed that the proposed HRA accepts more requests without exceeding the available bandwidth. From the simulation studies it is found that the packet loss has been reduced in the proposed HRA. Also, this paper presents a computational model for estimating the Blocking Probability in ASON network.

Keywords

Optical Networks, Routing, ASON, ORA, WDM.

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M. Malleswaran ¹, V. Vaidehi ², J. Mary Anita ³

Affiliations
1 Electronics and Communication Engineering Department, Anna University of Technology Tirunelveli, Tirunelveli, 627007, IN
2 Information Technology Department, Anna University, MIT Campus, Chennai, IN
3 Electrical and Electronics Engineering Department, Anna University of Technology Tirunelveli, Tirunelveli, 627007, IN

Abstract

The GPS/INS integration is the adequate solution to provide a navigation system that has superior performance in comparison with either a GPS or an INS stand-alone system. The GPS/INS integration is typically carried out through Kalman filter (KF). However, the fact that KF highly depends on a predefined dynamics model forms a major drawback. Most recently, Adaptive neuro fuzzy inference system (ANFIS) has been proposed which is trained during the availability of GPS signal to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. This paper introduces a hybrid evolutionary algorithm of cooperative particle swarm optimization (CPSO) and cultural algorithm that is used to update the ANFIS parameters. The results demonstrate the comparison of the optimized ANFIS with PSO, CPSO and with hybrid evolutionary algorithm of cultural cooperative particle swarm optimization (CPSO) and cultural algorithm (CA), for INS/GPS integration.

Keywords

INS/GPS, ANFIS, Data Fusion, CPSO, CA.

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M. Malleswaran ¹, V. Vaidehi ², S. Angel Deborah ³

Affiliations
1 Electronics and Communication Engineering Department, Anna University of Technology Tirunelveli, Tirunelveli-627007, IN
2 Information Technology Department, Anna University, MIT Campus, Chennai, IN
3 Electrical and Electronics Engineering Department, Anna University of Technology Tirunelveli, Tirunelveli-627007, IN

Abstract

GPS and INS are commonly integrated using a Kalman filter (KF) to provide a robust aircraft navigation solution, overcoming drawbacks of GPS satellite signals blockage. This work presents an alternative method of integrating GPS and INS data, called Artificial Neural Networks. This method uses Adaptive Resonance Theory-Counter Propagation Neural Networks (ART-CPN) to predict the INS position error. The performance of ART-CPN is analyzed using real time data in terms of Root Mean Square Error (RMSE), Performance Index (PI), number of hidden neuron, number of epochs and learning rate. The performance of Forward only Counter Propagation Network (FCPN) and Full Counter Propagation Network (Full CPN) are also analyzed and compared with ART-CPN. ART-CPN is found to have better clustering ability when compared to FCPN and Full CPN. ART-CPN also has better learning ability and network constructing ability when compared to FCPN and Full CPN. It has better learning speed due to its one step learning process.

Keywords

ART-CPN, FCPN, Full CPN, GPS, INS, NPUA.

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S. Indira Gandhi ¹, V. Vaidehi ¹, Xavier Fernando ²

Affiliations
1 Department of Electronics Engineering, Madras Institute of Technology, Tamil Nadu, IN
2 Department of Electrical and Computer Engineering, Ryerson University, CA

Abstract

Dynamic Online Routing Algorithm (DORA) has been already proposed for conventional networks to distribute load evenly across the network. However, the exponential growth of the internet has placed heavy burdens on network management and control application when the existing protocols are used. Adding more resources to the network may temporarily remove congestion conditions. However, it is not a cost-effective solution in solving resource contention problems in the long run. The network providers are facing problems in setting up on-demand network tunnels in backbone or transport networks. The MDORA proposed in this work is useful to decide the optimum number of regenerators to be placed on each node. Placement of regenerator in all the nodes is not cost effective and hence in this work, techniques have been proposed to place the regenerators only in selected nodes. Node selection for regenerator placement is performed using fuzzy logic.

Keywords

DORA, MDORA, Fuzzy Logic, Conventional Network.

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S. Vasuhi ¹, V. Vaidehi ², N. T. Naresh Babu ¹

Affiliations
1 Department of Electronics Engineering, M.I.T, Anna University, Tamil Nadu, IN
2 Department of Computer Technology, M.I.T, Anna University, Tamil Nadu, IN

Abstract

This paper proposes a real-time system for face authentication, obtained through fusion of Infra Red (IR) and visible images. In order to identify the unknown person authentication in highly secured areas, multiple algorithms are needed. The four well known algorithms for face recognition, Block Independent Component Analysis(BICA), Kalman Filtering(KF) method, Discrete Cosine Transform(DCT) and Orthogonal Locality Preserving Projections (OLPP) are used to extract the features. If the data base size is very large and the features are not distinct then ambiguity will exists in face recognition. Hence more than one sensor is needed for critical and/or highly secured areas. This paper deals with multiple fusion methodology using weighted average and Fuzzy Logic. The visible sensor output depends on the environmental condition namely lighting conditions, illumination etc., to overcome this problem use histogram technique to choose appropriate algorithm. DCT and Kalman filtering are holistic approaches, BICA follows feature based approach and OLPP preserves the Euclidean structure of face space. These recognizers are capable of considering the problem of dimensionality reduction by eliminating redundant features and reducing the feature space. The system can handle variations like illumination, pose, orientation, occlusion, etc. up to a significant level. The integrated system overcomes the drawbacks of individual recognizers. The proposed system is aimed at increasing the accuracy of the person authentication system and at the same time reducing the limitations of individual algorithms. It is tested on real time database and the results are found to be 96% accurate.

Keywords

Face Recognition, Combined Classifier, Weighted Average, Matching Score Level, Fuzzy Fusion.

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