Browsing by Author "Kodagoda, N."

Now showing 1 - 4 of 4

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Consumer and Farmer Centric Subscription Based Organic Vegetable/Fruit Delivery System
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Karunarathna, T.M.N.P.; Kumari, M.M.A.; Kulasinghe, W.D.K.A.; Liyanage, T.L.P.; Kodagoda, N.; Suriyanwsa, K.; Kumari, D.
For centuries, the economy of Sri Lanka has been backed by the agricultural sector. Even though it has contributed to the development of the nation on a large scale, the economies and living standards of the farmers have not been improved much. Most of the farmers remain poor mainly due to not knowing the market demand and the low buying prices of the middleman. Meanwhile, the consumers in Sri Lanka are buying non-organic vegetables and fruits which are highly contaminated with dangerous chemicals which in turn has contributed to the rapidly increasing non-communicable disease rates in both consumers and farmers. The proposed system is an attempt to solve these problems faced by both farmers and consumers by reducing the farmers-consumer knowledge gap and providing consumers a trustworthy and personalized subscription for organic vegetables/fruits with a donation platform.
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Database Scaling on Kubernetes
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Perera, H.C.S.; De Silva, T.S.D.; Wasala, W.M.D.C.; Rajapakshe, R.M.P.R.L.; Kodagoda, N.; Samaratunge, U.S.S.; Jayanandana, H.H.N.C.
Kubernetes is a hot topic in the field of Software Engineering and Distributed Computing. When compared to previous methods, the principle underlying Kubernetes, which is containerization, has altered how applications are created and delivered. However, when considering the state, particularly the databases, with Kubernetes, there is a scalability and data synchronization barrier. The most frequently used approach is to host the database outside of Kubernetes and maintain connectivity with the cluster. Kubernetes inherent capabilities are sufficient for hosting databases. But that requires high domain knowledge to do the configurations and maintain the databases on Kubernetes. The purpose of this research is to fulfil that gap by introducing a solution for managing highly available databases on Kubernetes. The solution is limited to managing PostgreSQL databases on Kubernetes using auto-scaling. A novel algorithm is proposed for auto-scaling, as previous algorithms do not take database requests into account when determining the scaling need. The drawbacks of data synchronization and auto-scaling will be solved in this research, and the end user will be able to access the service without interruption for the majority of the time, as the final solution makes the database cluster highly available for the service layer.
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MOOCs Recommender Based on User Preference and Video Quality
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Sankalpa, R.; Sankalpani, T.; Sandeepani, T.; Ransika, N.; Kodagoda, N.; Suriyawansa, K.
MOOCs (Massive Open Online Courses) are a new revolution in the field of e-learning. MOOCs are capable of providing several thousands of learners with access to courses over the internet. MOOCs are produced in many different video production styles and these styles play an important role in helping the consumer stay engaged and interested in the courses. MOOCs provide a large number of courses in different domains to a wide range of learners. It has become difficult and a timeconsuming task for a user to find the most suitable courses that suit a learner’s personal preferences. This paper describes how to recommend a course based on the preferred video style of the learner and the basic learning style of the learner which determines the learner’s preferences on other materials in a course. In the course recommendation process, this paper also describes how to classify the course in order to recommend the most appropriate massive open online courses for users according to their most preferred video production style.
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A Parallel Version of the In-Close Algorithm
(Faculty of Graduate Studies and Research, 2017-01-17) Kodagoda, N.; Andrews, S.; Pulasinghe, K.
This research paper presents a new parallel algorithm for computing the formal concepts in a formal context. The proposed shared memory parallel algorithm Parallel-Task-In-Close3 parallelizes Andrews's In-Close3 serial algorithm. The paper presents the key parallelization strategy used and presents experimental results of the parallelization using the OpenMP framework