Stream Processing Engines for Smart Healthcare Systems
- Authors
- Khiati, Rhaed; Hanif, Muhammed; Lee, Choonhwa
- Issue Date
- Nov-2018
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Big Data; Distributed Systems; Smart Healthcare Systems; Streaming Engines
- Citation
- Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018, pp.467 - 471
- Indexed
- SCOPUS
- Journal Title
- Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018
- Start Page
- 467
- End Page
- 471
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/149119
- DOI
- 10.1109/ICNIDC.2018.8525603
- Abstract
- In the emerging modern world, it is not a stretch to say that smart healthcare systems have become one of the most sought-after technological innovations by healthcare organizations and governments alike. However, with the rising population comes an increased demand for such systems to be available globally as quickly as possible. A bigger population results in an increased number of patients, meaning an even more substantial increase in the amount of big data that needs to be processed in these systems. The goal of this paper is to research and analyze the benefits that Apache Flink, one of the top streaming engines currently available, brings to smart healthcare systems and how it can help with not only enhancing the area of smart healthcare technology, but potentially revolutionize it. We will also compare Flink with other modern streaming engines to further emphasize this claim. In doing so, we plan to raise awareness about Flink as the streaming engine for future smart healthcare systems.
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