B. Uma Maheswari currently serves as Assistant Professor at department of Computer Science,Amrita School of Engineering.She is currently pursuing her Ph.D.


Publication Type: Journal Article

Year of Publication Publication Type Title


Journal Article

B. Uma Maheswari and Dr. T.S.B. Sudarshan, “Fenwick tree based capability-aware live multimedia streaming in sparse MANETs”, International Journal of Applied Engineering Research, vol. 10, pp. 12655-12670, 2015.[Abstract]

Recent advancement in the network technology and infrastructure support video streaming over multiple paths. Realizing high quality video streaming over Mobile Adhoc Networks (MANET) is a very challenging task. This paper proposes an Application Layer Based Capability Aware protocol for single server multi user live streaming application. In wireless network each device has different capability in terms of data-storage, mobility, forwarding data, availability etc., and proposed protocol aims to realize these capabilities and to distribute video chunks in multiple paths by segmenting the stream based on its capacity. This is achieved with the help of Fenwick Tree – a data structure which is integrated in the Application Layer. The system is implemented and tested under various scenarios. The results show there is a considerable increase in throughput and decrease in total transfer time. © Research India Publications

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Journal Article

S. Saravanan and B. Uma Maheswari, “Analyzing Large Web Log Files in a Hadoop Distributed Cluster Environment”, International Journal of Computer Technology and Applications (IJCTA), vol. 5, no. 5, 2014.[Abstract]

Analysing web log files has become an important task for E-Commerce companies to predict their customer behaviour and to improve their business. Each click in an E-commerce web page creates 100 bytes of data. Large E-Commerce websites like flipkart.com, amazon.in and ebay.in are visited millions of customers simultaneously. As a result, these customers generate petabytes of data in their web log files. As the web log file size is huge we require parallel processing and reliable data storage system for processing the web log files. Both the requirements are provided by Hadoop framework. Hadoop provides Hadoop Distributed File System (HDFS) and MapReduce rogramming model for processing huge dataset efficiently and effectively. In this paper, NASA web log file is analysed and the total number of hits received by each web page in a website, the total number of hits received by a web site in each hour using Hadoop framework is calculated and it is shown that Hadoop framework takes less response time to produce accurate results. Keywords - Hadoop, MapReduce, Log Files, Parallel Processing, Hadoop Distributed File System, ECommerce More »»

Publication Type: Conference Paper

Year of Publication Publication Type Title


Conference Paper

B. Uma Maheswari and Dr. T.S.B. Sudarshan, “An ECDD technique to optimize QoS in wireless overlay network for multipath video streaming”, in Proceedings of the 2015 International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2015, 2015, pp. 50-53.[Abstract]

Multimedia applications over wireless networks are growing day by day. To provide better user experience the use of overlay network is the promising solution. However, maintaining overlay in wireless network is the challenging task which produces additional overheads. This overhead degrades the quality of the video transmitted over overlay networks. To overcome these issues ECDD model is proposed in this paper. mTreebone is used to build an overlay This model also adopts FEC scheme for error correction and video data is transmitted by using sub packetization method in multiple paths. The simulation results show the improved performance of the algorithm with respect to end to end delay and retransmission requests. Number of retransmission requests is reduced by 52.27% than SPMLD. © 2015 IEEE.

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NIRF 2017