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Title SECURE AND DE-DUPLICATION BASED DATA AGGREGATION IN WIRELESS BODY AREA NETWORKS

Author(s) Iqra Sehr

Abstract Wireless Body Area Networks (WBAN) are helpful for monitoring, diagnostic, and therapeutic levels. These networks gather real time medical information by using various sensors with secure communication links. It facilitates doctors to observe a patient’s health conditions by monitoring patient’s vital signs away from the hospital. Sensors sense the data and forward it to the head node. The collector node consumes power to process this redundant information. It wastes too much power by sending same kind of data to next level repeatedly. During data aggregation, the collector node receives input data packets, process them and transmits it as a single packet that causes communication, energy and storage overhead. A data de-duplication approach has been proposed to remove redundancy and ensure single instantiation of data. In this work, we have proposed a de-duplication based data aggregation mechanism that includes adaptive chunking algorithm (ACA). It identifies a cut-point between two windows. It includes fixed size and variable sized window that is identified as per minimum threshold for windows size. Our algorithm locates a second level variable length chunk based on the delimiter to improve the size of variable length window. The algorithms have been simulated using NS-2.35 on Ubuntu where TCL code is used for deploying sensing devices and message initiation. C language is used for implementing the algorithms, message receiving and sending among sensors, head nodes and sink nodes. Test results show that increase in variable sized window is measured by 65.6%, 68% and 71.2% in case of RAM, AE and proposed ACA, respectively. It results in better de-duplication identification. In this case, collector nodes consume 64% more energy as compared to sensor nodes. Results show better performance of proposed scheme over counterparts in terms of cut-point identification failure, fixed and variable length chunk size, average chunk size, number of chunks, cut-point identification failure and energy consumption.

Type Thesis/Dissertation MS

Faculty Engineering and Computer Science

Department Computer Science

Language English

Publication Date 2019-01-15

Subject Wireless Body Area Networks

Publisher NUML

Contributor(s)

Format PDF

Identifier

Source

Relation

Coverage

Rights NUML

Category MSCS Thesis

Description MSCS Thesis by Iqra Sehr