Abstract
With the popularity of mobile phones, mobile sensing system has become an important research area in wireless sensor network. In this paper, a multi-resolution task distribution method for mobile sensing system is presented. First, a task map of sensing area is defined according to its physical map. Then a set of of information parameters are designed, and the task map is encoded. Thus the mobile nodes are capable of downloading the task map using parametric encoding map. In our proposed method, mobile nodes can stop receiving task map at any time, and a task map with suitable resolution is obtained. Through experiment about error rate of parametric encoding, multi-resolution receiving method and encoded information size, we can conclude that parametric encoding and multi-resolution receiving are suitable for mobile sensing system.
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
Howard, A., Matarić, M.J., Sukhatme, G.S.: Mobile sensor network deployment using potential fields: A distributed, scalable solution to the area coverage problem. In: Proc of International Symposium on Distributed Autonomous Robotics Systems, pp. 299–303 (2002)
Mun, M., et al.: Peir, the Personal Environmental Impact Report, as a Platform for Participatory Sensing Systems Research. In: Proc. 7th ACM MobiSys, pp. 55–68 (2009)
Thiagarajan, A., et al.: VTrack: Accurate, Energy-Aware Traffic Delay Estimation Using Mobile Phones. In: Proc. 7th ACM SenSys, Berkeley, CA (November 2009)
Bao, X., Roy Choudhury, R.: Movi: mobile phone based video highlights via collaborative sensing. In: Proc. 8th International Conference on Mobile Systems, Applications, and Services, MobiSys 2010, pp. 357–370. ACM, New York (2010)
Oliver, N., Mangas, F.F.: Healthgear: Automatic sleep apnea detection and monitoring with a mobile phone. Journal of Communications (March 2007)
Ngai, E., Huang, H., Liu, J., Srivastava, M.: OppSense: Information sharing for mobile phones in sensing field with data repositories. In: Proc. of SECON (June 2011)
Rana, R., Chou, C., Kanhere, S., Bulusu, N., Hu, W.: Ear-phone: an end-to-end participatory urban noise mapping system. In: Proc. of ACM/IEEE IPSN 2010, pp. 105–116 (2008)
Burke, J., Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., Srivastava, M.B.: Participatory sensing. In: Workshop on World-Sensor-Web (WSW 2006), pp. 117–134 (2006)
Dang, T., Feng, W., Bulusu, N.: Zoom: A multi-resolution tasking framework for crowdsourced geo-spatial sensing. In: Proc. of IEEE Infocom, pp. 501–505 (2011)
Xia, K., Wei, C.: Study on Real-Time Navigation Data Model Based on ESRI Shapefile. In: Proc. of IEEE Infocom, pp. 174–178 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, J., Zhou, S. (2014). A Multi-resolution Task Distribution Method in Mobile Sensing System. In: Sun, L., Ma, H., Hong, F. (eds) Advances in Wireless Sensor Networks. CWSN 2013. Communications in Computer and Information Science, vol 418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54522-1_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-54522-1_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54521-4
Online ISBN: 978-3-642-54522-1
eBook Packages: Computer ScienceComputer Science (R0)