We present an intelligent data management framework that can facilitate development of highly scalable and mobile healthcare applications for remote monitoring of patients. This is achieved through the use of a global log data abstraction that leverages the storage and processing capabilities of the edge devices and the cloud in a seamless manner. In existing log based storage systems, data is read as fixed size chunks from the cloud to enhance performance. However, in healthcare applications, where the data access pattern of the end users differ widely, this approach leads to unnecessary storage and cost overheads. To overcome these, we propose dynamic log chunking. The experimental results, comparing existing fixed chunking against the H-Plane model, show 13 %–19 % savings in network bandwidth as well as cost while fetching the data from the cloud.
cited By 0; Conference of 13th International Conference on Mobile Web and Intelligent Information Systems, MobiWIS 2016 ; Conference Date: 22 August 2016 Through 24 August 2016; Conference Code:179799
R. Krishnan Pathinarupothi, Bithin Alangot, Dr. Maneesha V. Ramesh, Dr. Krishnashree Achuthan, and P. Rangan, V., “H-Plane: Intelligent Data Management for Mobile Healthcare Applications”, in Mobile Web and Intelligent Information Systems: 13th International Conference, MobiWIS 2016, Vienna, Austria, August 22-24, 2016, Proceedings, M. Younas, Awan, I., Kryvinska, N., Strauss, C., and van Thanh, D., Eds. Cham: Springer International Publishing, 2016, pp. 283–294.