Abstract
In this paper, we describe a packet data size minimization method designed specifically for advertising and discovery in ubiquitous networks. The minimization is effective for achieving superior discovery performance characteristics such as discovery time and power consumption. The proposed method for data packet size minimization is based on indexing of advertisement text. In the method, dictionaries and indexed data are stored separately, i.e. dictionaries are stored on a server and indexed data is stored on ubiquitous wireless devices, and the same dictionaries are shared among all users. We evaluate an average packet data size and dictionary size for three indexing methods: regular indexing, category indexing and attribute indexing; and show that these methods achieve data packet sizes which are about two and three times smaller than raw data packets and zipped packet data sizes respectively. Also, we show that category indexing allows users to be less dependent on the infrastructure.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Akyildiz, I.F., Weilian, S., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE Commun. Mag. 40(8), 102–114 (2002)
Borovoy, R., McDonald, M., Martin, F., Resnick, M.: Things that blink: computationally augemented name tags. IBM Systems Journal 35(3-4), 488–495 (1996)
Borovoy, R., et al.: Meme tags and community mirrows: moving from cnferences to collaboration. In: Proc. of ACM Conf. Computer Supported Cooperative Work, pp. 159–169 (1998)
McCrone, J.: You buzzing me? New Scientist, 20–23 (2000)
Laibowwitz, M., Gips, J., Aylward, R., Pentland, A., Paradiso, J.A.: A sensor network for social dynamics. In: Proc. of Conf. on Information processing in sensor networks, pp. 483–491 (2006)
Poupyrev, P., Davis, P., Morikawa, H.: TinyObj: A Framework for Service discovery in Ubiquitous Environments. In: Dourish, P., Friday, A. (eds.) UbiComp 2006. LNCS, vol. 4206, Springer, Heidelberg (2006)
Poupyrev, P., Sasao, T., Surawatari, S., Davis, P., Morikawa, H., Aoyama, T.: Service Discovery in TinyObj: Strategies and Approaches. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 34–39. Springer, Heidelberg (2005)
Madden, S., Franklin, M.J., Hellerstein, J.: TAG: A tiny aggregation service for ad-hoc sensor networks. In: Proc. of 5th Simposium on Operating Systems Design and Implementation, pp. 131–146 (2002)
Klein, M., Konig-Ries, B., Obreiter, P.: Service Rings - a Semantic Overlay for Service Discovery in Ad Hoc Networks. In: MaÅ™Ãk, V., Å tÄ›pánková, O., Retschitzegger, W. (eds.) DEXA 2003. LNCS, vol. 2736, pp. 180–185. Springer, Heidelberg (2003)
Chakraborty, D., Joshi, A., Finin, T., Yesha, Y.: GSD: A novel groupbased service discovery protocol for MANETS. In: MWCN 2002. Proc. of 4th IEEE Conf. on Mobile and Wireless Communications Networks, pp. 3165–3182 (2002)
Ratsimor, O., Chakraborty, D., Tolia, S., Kushraj, D., Kunjithapatham, A., Gupta, G., Joshi, A., Finin, T.: Allia: Alliance-based service discovery for ad-hoc environments. In: Proc. of ACM Mobile Commerce Workshop, pp. 1–9 (2002)
Google-base (2007), http://base.google.com/
7-zip compression tool (2007), http://www.7-zip.org/
Finkenzeller, K.: RFID Handbook. John Wiley & Sons, New York (1999)
Sarma, S., Brock, D., Engels, D.: Radio Frequency Identification and the Electronic Product Code. IEEE Mag. Micro 21(6), 50–54 (2001)
Bloom, B.: Space/time tradeoffs in hash coding with allowable errors. CACM 13(7), 422–426 (1970)
Broder, A., Mitzenmacher, M.: Network applications of Bloom filters: A survey. In: Proc. of the 40th Annual Allerton Conference on Communications, Control, and Computing, pp. 636–646 (2002)
Sailhan, F., Issarny, V.: Scalable Service Discovery for MANET. In: PerCom 2005. Proc. of Third IEEE Int. Conf. on Pervasive Computing and Communications, pp. 235–244 (2005)
Bluetooth Consortium, Specification of the bluetooth system core version 1.0b, Service Discovery Protocol (1999)
Avancha, S., Joshi, A., Finin, T.: Enhanced service discovery in Bluetooth. IEEE Computer 35(6), 96–99 (2002)
Sun micosystems, Jini architecutre specification 2.0 (2003)
Guttman, E., Perkins, C.: Service Location Protocol (1999)
Liefke, H., Suciu, D.: XMill: An Efficient Compressor for XML Data. In: Proc. of the ACM SIGMOD Intl. Conf. on Management of Data, pp. 153–164. ACM Press, New York (2000)
Min, J.-K., Park, M.-J., Chung, C.-W.: XPRESS: A Queriable Compression for XML data. In: Proc. Int. Conf. of Management of Data, ACM SIGMOD, pp. 122–133 (2003)
Tolani, P.M., Haritsa, J.R.: XGRIND: A query-friendly XML compressor. In: ICDE 2002. Proc. of 18th Int. IEEE Conf. on Data Engineering, pp. 225–234 (2002)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Poupyrev, P., Kawahara, Y., Davis, P., Morikawa, H. (2007). Compact Data Format for Advertising and Discovery in Ubiquitous Networks. In: Ichikawa, H., Cho, WD., Satoh, I., Youn, H.Y. (eds) Ubiquitous Computing Systems. UCS 2007. Lecture Notes in Computer Science, vol 4836. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76772-5_22
Download citation
DOI: https://doi.org/10.1007/978-3-540-76772-5_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76771-8
Online ISBN: 978-3-540-76772-5
eBook Packages: Computer ScienceComputer Science (R0)