Informatics Publishing Limited

N. M. Balamurugan ¹, S. Appavu Alias Balamurugan ²

Affiliations
1 CSE Department, Sri Venkateswara College of Engineering, Sriperumbudur, Tamilnadu, IN
2 Department of IT, KLN College of Information Technology, Sivagangai, Tamil Nadu, IN

Abstract

Background/objectives: The performance of the Ad-hoc On-demand Distance Vector routing protocol is analyzed by simulation in this paper. Method/Statistical Analysis: The simulation is developed employing the libraries provided by the simulator. The simulation is developed to model the communication of multimedia packets in an ad hoc wireless network which deploys the AODV routing protocol. Findings: The characteristics of the multimedia packets are in accordance with the Traffic dimensioning principles for multimedia wireless networks. Applications/Improvements: The simulation results are obtained and plotted for throughput, latency and control packet overhead which can be used to adjudge the performance of the protocol.

Keywords

Ad hoc Routing Protocols ,Wireless Networks

Full Text

   

S. Subashini ¹, S. Appavu alias Balamurugan ²

Affiliations
1 Department of Computer Science Engineering, Fatima Michael College of Engineering and Technology, Madurai – 625020, Tamil Nadu, IN
2 Department of Information Technology, K.L.N. College of Information and Technology, Madurai – 630612, Tamil Nadu, IN

Abstract

Background: We study an important problem of similarity grouping processing on stream data that inherently contain uncertainty. Method: In this paper SBSP - [Stage by Stage Pruning] a novel pruning method is proposed for fast, accurate clustering and classifying the data where the two stages were grouped into a single framework MYFRAME. Findings: The proposed approach group the data-by-data level pruning using Manhattan distance in first stage. In the second stage, the data is grouped by object level pruning in hyperspace. Improvements: Currently, this approach is applied in real time applications such as object detection, video retrieval, people detection and tracking, earth quake monitoring etc.

Keywords

Clustering, Data Pruning, Distance, Group Nearest Neighbor, Grouping Process, Similarity Search, Uncertain Data Streams

Full Text