Abstract
Designing and implementing a distributed database for a microservices cloud-based online travel portal has been proven essential for handling a large volume of the database, load balancing of an application, and applying for global access with live data. Microservices become more popular as the applications become more complex and distributed. The main goal of microservices is to build an application by splitting the application into small services from large business components which can be deployed and run independently. In this research, we show the distributed databases design and distribution using different types of fragmentation techniques, data allocation, and data integration using relational algebra, union and join. We also illustrate how distributors, agents, and customers from all different countries can be managed in a database table from an individual country by setting up a database on a nearby site instead of searching from a whole global database. This research will help design and implement distributed databases for cloud-based online travel portals, including microservices applications, to save from a complete system failure, huge data handling, and load balancing of an application.
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This research is partly supported through the Australian Research Council Discovery Project: DP190100314.
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Barua, B., Md Whaiduzzaman, Mesbahuddin Sarker, M., Shamim Kaiser, M., Barros, A. (2023). Designing and Implementing a Distributed Database for Microservices Cloud-Based Online Travel Portal. In: Shakya, S., Du, KL., Ntalianis, K. (eds) Sentiment Analysis and Deep Learning. Advances in Intelligent Systems and Computing, vol 1432. Springer, Singapore. https://doi.org/10.1007/978-981-19-5443-6_22
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DOI: https://doi.org/10.1007/978-981-19-5443-6_22
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