Informatics Publishing Limited

B. Thenral ¹, K. Thirunadana Sikamani ¹

Affiliations
1 Department of Electronics and Communication Engineering, St. Peter’s University, Chennai – 600054, Tamil Nadu, IN

Abstract

Objective: The main intent of this research is to improve the quality of service in Wireless Mesh Networks by reducing the number of hops and communication overhead generated in the network. Methods: In this manuscript, the Angle based Multicast Routing Algorithm (AMRA) is introduced for reducing communication overhead and thus improving performance in the wireless mesh networks. Every intermediate node towards the destination is selected based on the angle towards the forwarding nodes. The next intermediate node is selected in the forwarding direction, if the angle is within 60° of the current node. This method reduces the number of hops in transmitting data. Results: The Angle based Multicast Routing Algorithm (AMRA) show higher performance when compared to the existing CAMP method. If the number of nodes is 50, the packet delivery rate is comparatively better in AMRA and the throughput in AMRA is 70%. According to the comparison results, the proposed approach works better than the other existing schemes with high quality of service. Conclusion: The simulation results demonstrate that the Angle based Multicast Routing Algorithm (AMRA) has high quality of service compared to the existing CAMP.

Keywords

Angle, Multicast Routing, Quality-of-Service, Wireless Mesh Networks

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M. Edwin Jayasingh ¹, K. Thirunadana Sikamani ², S. Allwin ¹

Affiliations
1 Department of Computer Science and Engineering, Infant Jesus College of Engineering, Tuticorin, Tamilnadu, IN
2 Department of Computer Science and Engineering, St.Peter‟s College of Engineering and Technology, Chennai, Tamilnadu, IN

Abstract

This work aims at developing a novel approach for the detection of cervical cancer in Pap smear images using textural feature analysis and provides a direct way to compare those images. The traditional methods employed for this detection would take lot of manual intervention which builds unwanted human errors. The main aim of this paper find out the most relevant texture features by which the detection of cervical cancer can be done, which in turn minimize the manual screening process in detection. This analysis helps in automation process in detection and classification of cytology images based on texture features. It also provides the valuable data to the cytologists to detect the abnormal region in cervical cancer cells. The project is implemented in MATLAB®, a numerical computing environment for data visualization and analysis. Experiments were conducted by extracting various texture features of pap smear images and it is programmed to detect the cancer of normal and abnormal stage in cervical cancer cells. Selection of classifier is also the most important task of this analysis since different classifiers works differently on applying selected features. Applying the most relevant features to various classifiers, we used the Weka tool to rank the features which are mostly fit into the detection. The comparison can be done on classifiers and the optimal results are shown.

Keywords

Cervical Cancer, Textural Feature, Cancer Detection, Cancer Stages.

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D. Santhosh Kumari ¹, K. Thirunadana Sikamani ²

Affiliations
1 Department of Electronics and Communication Engineering, St. Peter’s University, Chennai - 600054, Tamil Nadu, IN
2 Department of Computer Science and Engineering, St. Peter’s College of Engineering and Technology, Chennai - 600054, Tamil Nadu, IN

Abstract

Objective: The main intent of this research is to detect the selfish node in Mobile Ad-hoc Networks (MANETs) and to select the Cluster Head (CH) based on the energy level and Node Communication Ratio (NCR). Methods/Analysis: In this paper, a new mechanism is developed to identify the selfish nodes in the communication network. Based on the level of energy and the Node Communication Ratio, the Cluster Head is selected. The cluster head in turn is used to contribute to the network within its infrastructure range. The sink node will be noticing the behavior of each and every communicating node in the network. Results: The communication based clustering has proved better performance in terms of packet delivery rate, packet loss rate, packet delay rate and better energy efficiency during data transmission. Conclusion: The simulation results show that this scheme has improved quality of service compared to the existing scheme 2Ack. This scheme can be applied in the areas of military operations, emergency and disaster management in order to ensure reliable data delivery on-the-move.

Keywords

Cluster Head, Clustering, Mobile Ad-hoc Network, Selfish Node

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