Sivagnanasundaram Janagan

Sivagnanasundaram Janagan

Result oriented professional with experiences in specialties of Software Engineering. Research Interests: Distributed Systems, Big Data

E-mail: | phone: +94757688669 | Course: SE

Highly motivated, dedicated and result oriented professional with experiences in various specialties widely especially in software engineering field. Enthusiastic about innovative ideas, applying new technologies, enhancing current technical expertise and very hard working dedicated individual. I am determined to be cheerful and happy in all the situations I may find myself.

Interests: BDistributed Systems, Big Data, Web Engineering, Algorithms, Digital Knowledge Ecosystems

Technical Skills: Java EE, C#, ASP.Net, JavaScript, PHP, SQL, NoSQL

Project Experience

Content Based Enhancement for Apache Kafka Framework
Enhancing Apache Kafka to content based subscription model from topic based subscription model

An automated device to detect the snake type which causes the snake bite in the human’s body

IPG & Geveo HR
System to facilitate property managing, buying and selling functions and HR system to manage company staffs.

Work Experience

Work Place: Software Engineer Intern – Geveo Australasia (PVT) Ltd. (Aug,2015 to Feb,2016)

Achievements | Awards

• Second Runners Up at Microsoft Imagine Cup – 2014 (Innovation Category) for the project: VDetector
• Nominated as the best 4 students for best performance in the industrial placement – 3rd year
• Participation at IEEEXtreme Coding Competition (2013, 2014)

Final Year Project

Content based Enhancement for Apache Kafka framework

Basically Publisher/Subscriber systems can be divided into two categories. Topic based model and Content based model which provides accurate results compared to topic based model, since subscribers interested on the content of the message rather than subscribing to a topic and getting all the messages. Apache Kafka is a distributed message passing system and it supports topic based subscription model. So in this research we thought of enhancing the Kafka framework to Content based model. Addition to that we enable the dynamic subscriber environment to the proposed system where the interest of the subscriber keep changes overtime and pluggable Top-k module to return the top most streams of data matches with the interest of the subscribers.

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