Abstract

High speed data retrieval is a main problem which affects the efficiency of hospital management system with internet of things (IoT). For this reason, we propose a new retrieval method, named dynamical clustering center (DCC) method, which dynamically determines the optimized clustering center when constructing the R-tree. By choosing an optimized clustering center, the method allows the spatial data in the same subspace to be organized into the same sub-tree, and builds an efficient R-tree index layer by layer from the root to the leaves. The experiments show that the proposed method can improve system stability and retrieval efficiency for the smart hospital information system.

Keyword

Hospital system, IoT, Retrieval, R-tree.

Cite this article

Wang X, Meng W, Zhang M

Refference

[1][1]Ge M, Bangui H, Buhnova B. Big data for internet of things: a survey. Future Generation Computer Systems. 2018; 87:601-14.

[2][2]Abdelgawad A, Yelamarthi K. Internet of things (IoT) platform for structure health monitoring. Wireless Communications and Mobile Computing. 2017.

[3][3]Biltoft J, Finneman L. Clinical and financial effects of smart pump–electronic medical record interoperability at a hospital in a regional health system. The Bulletin of the American Society of Hospital Pharmacists. 2018; 75(14):1064-8.

[4][4]Akbulut FP, Akan A. A smart wearable system for short-term cardiovascular risk assessment with emotional dynamics. Measurement. 2018; 128:237-46.

[5][5]Bibi F, Guillaume C, Gontard N, Sorli B. A review: RFID technology having sensing aptitudes for food industry and their contribution to tracking and monitoring of food products. Trends in Food Science & Technology. 2017; 62:91-103.

[6][6]Balkir AS, Foster I, Rzhetsky A. A distributed look-up architecture for text mining applications using mapreduce. In proceedings of international conference for high performance computing, networking, storage and analysis 2011. ACM.

[7][7]Wang C, Zhu Y, Ma Y, Qiu M, Liu B, Hou J, et al. A query-oriented adaptive indexing technique for smart grid big data analytics. Journal of Signal Processing Systems. 2018; 90(8-9):1091-103.

[8][8]Neubauer K, Haubelt C, Wanko P, Schaub T. Utilizing quad-trees for efficient design space exploration with partial assignment evaluation. In Asia and South pacific design automation conference 2018 (pp. 434-9). IEEE.

[9][9]Balasubramanian L, Sugumaran M. A state-of-art in R-tree variants for spatial indexing. International Journal of Computer Applications. 2012; 42(20):35-41.

[10][10]Bayani M, Segura A, Alvarado M, Loaiza M. IoT-based library automation and monitoring system: developing an implementation framework of implementation. E-Ciencias de la Información. 2018; 8(1):83-100.

[11][11]Dehury CK, Sahoo PK. Design and implementation of a novel service management framework for IoT devices in cloud. Journal of Systems and Software. 2016; 119:149-61.

[12][12]Gelogo YE, Hwang HJ, Kim HK. Internet of things (IoT) framework for u-healthcare system. International Journal of Smart Home. 2015; 9(11):323-30.

[13][13]Radanović I, Likić R. Opportunities for use of blockchain technology in medicine. Applied Health Economics and Health Policy. 2018; 16(5):583-90.

[14][14]Kim JC, Chung K. Mining health-risk factors using PHR similarity in a hybrid P2P network. Peer-to-Peer Networking and Applications. 2018; 11(6):1278-87.

[15][15]Banawan K, Ulukus S. Private information retrieval from coded databases. In international conference on communications 2017 (pp. 1-6). IEEE.

[16][16]Jin T, Wang J, La Rosa M, Ter Hofstede A, Wen L. Efficient querying of large process model repositories. Computers in Industry. 2013; 64(1):41-9.

[17][17]Guangjun W, Shupeng W, Ming C. Massive structured data oriented storage and retrieve system. Journal of Computer Research and Development. 2012; 49(1):1-5.

[18][18]Chen J, Chen Y, Du X, Li C, Lu J, Zhao S, et al. Big data challenge: a data management perspective. Frontiers of Computer Science. 2013; 7(2):157-64.

[19][19]Dittrich J, Quiané-Ruiz JA, Richter S, Schuh S, Jindal A, Schad J. Only aggressive elephants are fast elephants. Proceedings of the VLDB Endowment. 2012; 5(11):1591-602.

[20][20]Gaede V, Günther O. Multidimensional access methods. ACM Computing Surveys. 1998; 30(2):170-231.

[21][21]Ahn HK, Mamoulis N, Wong HM. A survey on multidimensional access methods. University of Science and Technology, Clearwater Bay, Hong Kong. 2002:1-19.

[22][22]Lu H, Ooi BC. Spatial indexing: past and future. IEEE Data Eng. Bull.1993; 16(3):16-21.

[23][23]Sellis T, Roussopoulos N, Faloutsos C. The R+-Tree: a dynamic index for multi-dimensional objects. International conference on very large data bases 1987.

[24][24]Beckmann N, Kriegel HP, Schneider R, Seeger B. The R*-tree: an efficient and robust access method for points and rectangles. In SIGMOD record 1990 (pp. 322-31). ACM.

[25][25]Roussopoulos N, Leifker D. Direct spatial search on pictorial databases using packed R-trees. ACM SIGMOD record. 1985; 14(4):17-31.

[26][26]Brakatsoulas S, Pfoser D, Theodoridis Y. Revisiting R-tree construction principles. In east European conference on advances in databases and information systems 2002 (pp. 149-62). Springer, Berlin, Heidelberg.

[27][27]Run-tao LI, Zhong-xiao HA. Spatial index structure based on R-tree and quadtree: RQOP_tree. Journal of Harbin Institute of Technology. 2010; 42(2):323-7.

[28][28]Jing-bin W. Optimization algorithm for R-tree combining with spatial-clusting. Computer Engineering and Application. 2014; 50(5):112-5.

[29][29]Huang Z, Qin Y, Zhang X, Zhao J, Jiang L. A static R-tree organization method based on top-down recursive clustering. In international conference on geoinformatics 2013 (pp. 1-5). IEEE.

[30][30]Saveetha V, Sophia S. Optimal tabu k-means clustering using massively parallel architecture. Journal of Circuits, Systems and Computers. 2018; 27(13).

[31][31]Narayana GS, Vasumathi D. An attributes similarity-based K-medoids clustering technique in data mining. Arabian Journal for Science and Engineering. 2018; 43(8):3979-92.

[32][32]Sethi P, Sarangi SR. Internet of things: architectures, protocols, and applications. Journal of Electrical and Computer Engineering. 2017.

[33][33]Chen X. Fast synchronization clustering algorithms based on spatial index structures. Expert Systems with Applications. 2018; 94:276-90.

[34][34]Achakeev D, Seeger B. A class of R-tree histograms for spatial databases. In proceedings of the international conference on advances in geographic information systems 2012 (pp. 450-3). ACM.

[35][35]Gao X, Qiu J. Social media data analysis with IndexedHBase and iterative MapReduce. In proceedings of the workshop on many-task computing on clouds, grids, and supercomputers 2013.

[36][36]Liu B, Zhu Y, Wang C, Chen Y, Huang T, Shi W, et al. A versatile event-driven data model in Hbase database for multi-source data of power grid. In international conference on smart cloud 2016 (pp. 208-13). IEEE.

[37][37]Chen X, Zhang C, Ge B, Xiao W. Spatio-temporal queries in HBase. In international conference on big data 2015 (pp. 1929-37). IEEE.