A Stream Data Processing Framework for Location-Based Service Using NoSQL Technology

Abstract:

One of the most exciting changes in Location-Based Services is the incredible growth of internet, development of wearable devices, and advanced positioning technologies. In addition, the big data from those sources helps performing seamless LBS as a technology. The existing processing methods used to detect the location of a particular tag, or specific device are not enough for complex processing while collecting all of the streaming data at the same time using a variety of wireless communication system [10,11,12,13]. We can use big data processing method for processing all the streaming data in real time. In this paper, we propose a framework for improving performance of Seamless LBS using NoSQL technology.

• Periodical: Applied Mechanics and Materials (Volume 763)
• Pages: 159-163
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.763.159
• Online since: May 2015
• Authors: Nan Ju Kim*, Eui In Choi
• Keywords: Bigdata, Cassandra, NoSQL, Seamless LBS

References

[1] H. Choi, LBS. Location-Based Services trend Computer Software Research [J]. Korea Electronics and Telecommunications Research Institute, No. 86, (2003).

[2] K. Pahlavan et al. Indoor geolocation science and technology [J]. IEEE Communication. Mag., Vol. 40, No. 2, 2002, pp.112-118.

[3] G. Lee. Development of location data stream professor for RTLS [J]. Korea GIS Conference, No. 6, 2002, pp.15-20.

[4] G. Sun et al. Signal processing techniques in network aided positioning [J]. IEEE Signal Processing Mag., Vol. 22, No. 4, 2005, pp.12-23.

DOI: 10.1109/msp.2005.1458273

[5] H. Shim et al. Comparative analysis for advanced technologies of the location based service [J]. The Korean Institute of Information and Communication Engineering, Vol. 16, No. 4, 2012, pp.853-871.

DOI: 10.6109/jkiice.2012.16.4.853

[6] Information on wikipedia. org/wiki/NoSQL.

[7] Information on wikipedia. org/wiki/Cassandra.

[8] Y. Zhao. Standardization of mobile phone positioning for 3G systems [J]. IEEE Communication. Mag., Vol. 40, No. 7, 2002, pp.108-116.

DOI: 10.1109/mcom.2002.1018015

[9] Y. Jaejun et al. Interior space, a new chapter in thefusion attention [J]. Electronics and Telecommunications Research Institute, No. 1571, 2011, pp.14-16.

[10] Y. Jaejun et al. Trend of Indoor Spatial Information Standardization [J]. TTA Journal, Vol. 144, 2012, pp.65-71.

[11] OMA-TP-2013296R01-INPIndoorlocationpublicsafety, http: /www. openMobilealliance. org.

[12] R. Mautz et al. Indoor Positioning Technologies [J]. Habilitation Thesis at ETH Zurich, Feb, 2012, p.152.

[13] Proposes new indoor requirements and revisions to Existing E911 rules, http: /www. fcc. gov/ document/proposes-new-indoor-requirments-and-revisions-existing-e911-rules.

[14] Y. Cho et al. WARP-P: Wireless signal Acquisition with Reference Point by using simplified PDF – sys-tem concept and performance assessment [J]. Proc. The ION 2013 Pacific PNT Meeting, Apr, (2013).

[15] D. Tipper el al. Providing Fault Tolerance in WirelessAccess Networks [J]. " IEEE Communication, Mag., Vol. 40, No. 1, Jan. 2002, p.58–64.

[16] C. Maria. Managing Service Performance in the Cassandra Distributed Storage System [J]. IEEE 5th International Conference on Cloud Computing Technology and Science, 2013, pp.64-71.

DOI: 10.1109/cloudcom.2013.16

[17] D. Elif et al. An Evaluation of Cassandra for Hadoop [J]. IEEE 6th International Conference on Cloud Computing, 2013, pp.494-501.

[18] Information on wikipedia. org/wiki/Application server.

[19] Information on wikipedia. org/wiki/Geographic information platform.

[20] Information on wikipedia. org/wiki/Visual Light Communications.