Design and Evaluation of Indoor Positioning System for User Access Management in Data Center
(*) Corresponding author
One critical point in data center management from the physical security perspective (according to ISO 27001 standards) is the management of user access and traffic. Physical security could be improved through the implementation of indoor positioning with a real-time monitoring system. Other than security needs, the information provided could be used for emergency evacuation purposes in a disastrous situation. Presently, indoor positioning is principally based on wireless signals, such as WiFi, RFID, Zigbee, Bluetooth, etc. This study designs a user access management system in the Data Center using indoor - positioning. For the indoor positioning method, k-Nearest Neighbor (kNN) and Fuzzy k-Nearest Neighbor (FkNN) algorithms and Kalman Filter implementation are evaluated. The simulation result shows that the proposed method can improve the positioning accuracy until 8% compared to the existing method.
Copyright © 2019 Praise Worthy Prize - All rights reserved.
A. C Salas, Indoor Positioning System based on Bluetooth Low Energy, Degree's Thesis Submitted to the Faculty of the Escola Tècnica d'Enginyeria de Telecomunicació de Barcelona Universitat Politècnica de Catalunya, Barcelona. 2014.
P. Kriz, F. Maly, and T. Kozel, Improving Indoor Localization Using Bluetooth Low Energy Beacons, Mobile Information Systems, 2016, pp. 1–11.
R. R. Sukhov, M. B. Amzakarov, and E. A. Isaev, Advanced Data Center Economy, In Business Informatic (Vol. 2, Issue 24, pp. 13-18). 2013.
D.V. Dumsky and E.A. Isaev, Data centers for physical research, In Physics Procedia (Vol. 71, pp. 298-302). Elsevier B.V. 2015.
Lin, X. Y., Ho, T. W., Fang, C. C., Yen, Z. S., Yang, B. J., & Lai, F. (2015). A mobile indoor positioning system based on iBeacon technology. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (Vol. 2015–Novem, pp. 4970–4973). Milan.
Haute, T. Van, Poorter, E. De, Crombez, P., Lemic, F., Handziski, V., Wirström, N., Wolisz, A., Voight, T., Moerman, I. (2016). Performance analysis of multiple Indoor Positioning Systems in a healthcare environment. International Journal of Health Geographics, Vol. 15, No.7, pp. 1-15.
Soewito, B., Wiguna, A., Suharjito, S., Diana, D., Bluetooth Low Energy: Comparing 4 Trilateration Models in Indoor Positioning System, (2018) International Journal on Communications Antenna and Propagation (IRECAP), 8 (6), pp. 500-509.
Z. Yang and Y. Liu, Quality of Trilateration: Confidence-Based Iterative Localization, in IEEE Transactions on Parallel and Distributed Systems, vol. 21, no. 5, pp. 631-640, May 2010.
Zhuang, Y., Yang, J., Li, Y., Qi, L., & El-Sheimy, N. (2016). Smartphone-based indoor localization with bluetooth low energy beacons. Sensors (Switzerland), 16(5), 1–20.
R. Hansen, B. Thomsen, L. L. Thomsen, and F. S. Adamsen, SmartCampusAAU - an open platform enabling indoor positioning and navigation, in Proceedings of 14th IEEE International Conference on Mobile Data Management, vol. 2, pp. 33–38, 2013.
F. Karlsson, M. Karlsson, B. Bernhardsson, F. Tufvesson, and M. Persson, Sensor fused indoor positioning using dual-band WiFi signal measurements, In Proceedings of European Control Conference (ECC), Linz, pp. 1669-1672, 2015.
F. Zafari and I. Papapanagiotou, Enhancing iBeacon Based Micro- Location with Particle Filtering, in Proceedings of IEEE Global Communications Conference (GLOBECOM), vol. 1, pp.1-7, San Diego, CA, 2015.
P. C. Deepesh, Rashmita Rath, Akshay Tiwary, Vikram N. Rao, and N. Kanakalata. 2016. Experiences with using iBeacons for Indoor Positioning, In Proceedings of the 9th India Software Engineering Conference (ISEC '16), pp.184-189, 2016.
F. Subhan, H. Hasbullah, A. Rozyyev, and S. T. Bakhsh, Indoor positioning in Bluetooth networks using fingerprinting and lateration approach, 2011 International Conference on Information Science and Applications (ICISA), pp.1-9, 2011.
Zhou, Cheng & Yuan, Jiazheng & Liu, Hongzhe & Qiu, Jing. (2017). Bluetooth Indoor Positioning Based on RSSI and Kalman Filter. Wireless Personal Communications. Vol. 96, No. 3, pp 4115-1130.
Zhang, Shichao & Li, Xuelong & Zong, Ming & Zhu, Xiaofeng & Cheng, Debo. (2017). Learning k for kNN Classification. ACM Transactions on Intelligent Systems and Technology. Vol.8, No.3., pp. 1-19.
Zhang, S., Member, S., Li, X., Zong, M., Zhu, X., & Wang, R. (2018). Efficient kNN Classification With Different Numbers of Nearest Neighbors. IEEE Transactions on Neural Networks and Learning Systems, 29(5), 1774–1785.
Keller, J.M., Gray, M.R. and Givens, J.A. (1985) A Fuzzy K-nearest Neighbor Algorithm. IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-15, No.4, pp.580-585.
D. Li, J.S. Deogun and K. Wang, Gene Function Classification Using Fuzzy K-Nearest Neighbor Approach, 2007 IEEE International Conference on Granular Computing (GRC 2007), 644–644, 2007.
Pu, Y. C., & You, P. C. (2018). Indoor positioning system based on BLE location fingerprinting with classification approach. Applied Mathematical Modelling, vol. 62, no.1, pp.654–663.
Yadav, R. K., Bhattarai, B., Gang, H.-S., & Pyun, J.-Y. (2019). Trusted K Nearest Bayesian Estimation for Indoor Positioning System. IEEE Access, vol.7, no.1, pp. 51484–51498.
Cabarkapa, D., Grujić, I., & Pavlović, P. (2015). Comparative analysis of the Bluetooth Low-Energy indoor positioning systems. 2015 12th International Conference on Telecommunication in Modern Satellite, Cable and Broadcasting Services (TELSIKS), vol.1, pp.76-79.
F. Dalkılıç, U. C. Çabuk, E. Arıkan and A. Gürkan, An analysis of the positioning accuracy of iBeacon technology in indoor environments, 2017 International Conference on Computer Science and Engineering (UBMK), Antalya, 2017, pp. 549-553.
T. J. Chainer, M. D. Schultz, P. R. Parida and M. A. Gaynes, Improving Data Center Energy Efficiency With Advanced Thermal Management, in IEEE Transactions on Components, Packaging and Manufacturing Technology, vol. 7, no. 8, pp. 1228-1239, Aug. 2017.
Shaw, R., Howley, E., & Barrett, E. (2018). An Advanced Reinforcement Learning Approach for Energy-Aware Virtual Machine Consolidation in Cloud Data Centers. 2017 12th International Conference for Internet Technology and Secured Transactions, ICITST 2017, vol.1, pp.61–66.
Sunardy, A., & Surantha, N. (2019). Performance Evaluation of Indoor Positioning Algorithm using Bluetooth Low Energy. 2018 International Conference on Information Technology Systems and Innovation, ICITSI 2018 - Proceedings, vol.1, pp.503–507.
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2023 Praise Worthy Prize