SREEVIDYA B. serves as Lecturer at department of Computer Science,Amrita School of Engineering.She is currently pursuing her M.Tech.


Publication Type: Conference Paper

Year of Publication Publication Type Title


Conference Paper

B. Sreevidya and Rajesh M, “Enhanced Energy Optimized Cluster Based On Demand Routing Protocol for Wireless Sensor Networks ”, in 6th International Conference on Advances in Computing, Communications & Informatics (ICACCI’17), Manipal University, Karnataka , 2017.[Abstract]

Wireless sensor networks (WSN) are widely used various applications such as disaster management, search and rescue operation, wild life monitoring, remote patient monitoring, structural health monitoring etc. It provides bridge between the real physical and virtual worlds. In many scenarios, the coverage area of the WSN will be very large and a multi-hop adhoc network needs to be maintained for the connectivity and data transfer among the nodes. The major part of the energy consumption of each node is used for data transfer among nodes. This paper proposes a energy efficient routing scheme. The scenario which is considered is a wireless sensor network which is a collection of clusters and data transfer happens with the help of cluster head (CH) rather than the collective effort of every node in the network. In such a cluster based WSN, it is advantageous to have a routing protocol which uses the information about clusters to decide upon route formation. This paper proposes a novel Cluster Based Routing Protocol for a WSN which optimizes the energy consumption on data transfer and thus increasing the lifetime of the WSN network. To conclude the advantages of the proposed scheme, comparison is carried out between the performance of AODV and CBRP protocols.

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Publication Type: Journal Article

Year of Publication Publication Type Title


Journal Article

B. Sreevidya, “An enhanced and productive technique for privacy preserving mining of association rules from horizontal distributed database”, International Journal of Applied Engineering Research, vol. 10, pp. 39126-39130, 2015.[Abstract]

The past two decades has seen a dramatic increase in the amount of information or data being stored in electronic format. This accumulation of data has taken place at an explosive rate. It has been estimated that the amount of information in the world doubles every 20 months and the size and number of databases are increasing even faster. The increase in use of electronic data gathering devices such as point-of-sale or remote sensing devices has contributed to this explosion of available data. Data confidentiality is a major concern in database systems especially when are huge amounts of data to be processed, so we try to implement a system where we could preserve security and maintain data confidentiality. Further there is a huge trend today towards distributed databases which make data mining very easy, reliable and efficient. In our paper we implement Fast Distributed Mining of Apriori algorithm for mining this huge transactional dataset. With the help of this algorithm we find the frequent item sets that are consumed in all transaction. Finding this frequent item sets in very important. By knowing this frequent item sets one can understand the interest of consumers and focus in profiting his business by mining association rules from them. In other words association rules can be used for decision making. © Research India Publications.

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NIRF 2017