Abstract
Multidimensional data in different fields (e.g., science and technology resources, medicine, finance and transportation) have emerged in the big data era. Technology of visualization is critical to analyze multidimensional data which is large-scale. Thus, the highly variability of multidimensional data leads to the necessity of improving data management efficiency by updating data in real time. Nevertheless, traditional real-time communication technology suffers from low efficiency and large bandwidth consumption. Based on WebSocket, this paper proposes a multidimensional data service platform architecture that is scalable, real-time and versatile. First, on the platform, we compare the network load and network latency above Ajax polling and WebSocket. Secondly, for multidimensional data, we further validate the effectiveness of WebSocket in the application scenarios of frequent updating and multi-user concurrent requests. WebSocket-based platform greatly shortens the time for people to understand and analyze massive and complex multidimensional data. The application results show that the design is effective for real-time updating of multidimensional data.
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Acknowledgements
This work is supported by the National Key R&D Program of China (Grant No. 2017YFB1401501) and Engineering Research Center of Information Networks, Ministry of Education.
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Haihong, E., Kong, H., Liu, Y., Song, M., Ou, Z. (2019). A Real-Time Update Approach for Visualizing Multidimensional Big Data. In: Milošević, D., Tang, Y., Zu, Q. (eds) Human Centered Computing. HCC 2019. Lecture Notes in Computer Science(), vol 11956. Springer, Cham. https://doi.org/10.1007/978-3-030-37429-7_10
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DOI: https://doi.org/10.1007/978-3-030-37429-7_10
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