Globecom 2013-Ad Hoc and Sensor Networking Symposium 250 2500 400 0c0 280 20 2 大 220 101020m20t30a040o0450 20 (aRW,0r=200(s）,0k=10 (b)RWP,0r=200(s).0k=10.4=18(m) (c)m=450.0k=10.u=18(m) 30 -Random Walk (RW) ent message(W的 300 20d 21 1000 210 20 0 200 2 100 200 309e00 500 600 00 (dm=450.0R=200(s),4=18(m) (e)RWPm=450.0R=200(s),0k=10 (①m=450,0R=200(s),0k=10.4=18(m) Fig.3.Comparison of the average searching time under Random Walk Mobility Model(RW)and Random Way-Point Mobility Model(RWP)with differen parameters (number of users m:time to live of request message 6R:number of event messages 6:expectation of movement region radius u). VII.CONCLUSION [5]J.Biswas.and M.Veloso,"Wifi localization and navigation for au- tonomous indoor mobile robots,"In Proc./CRA,Anchorage,Alaska, This paper proposes a framework using RFID-based delay USA.May2010,Pp.4379-4384. tolerant network for indoor navigation.By sufficiently leverag- [6]X.Jiang,C.-J.M.Liang,F.Zhao,K.Chen,J.Hsu,B.Zhang,and J. ing the store-forward properties of delay tolerant network,our Liu."Demo:Creating interactive virtual zones in physical space with magnetic-induction,"in Proc.SenSys.Seattle,WA.USA.Nov.2011.pp. solution provides an effective mechanism for indoor naviga- 431.432. tion.Simulation results show that our solution can efficiently [7]X.Jiang.C.-J.M.Liang,K.Chen,B.Zhang,J.Hsu,J.Liu,B.Cao,and reduce the average searching time of navigation.We discuss F.Zhao,"Design and evaluation of a wireless magnetic-based proximity detection platform for indoor applications,"in Proc.IPSN,Beijing the influences of different mobility parameters in the end. China,April 2012,pp.221-232. [8]L.Xie,B.Sheng,C.Tan,H.Han,Q.Li and D.X.Chen,"Efficient VIII.ACKNOWLEDGEMENT tag identification in mobile RFID systems,"in Proc.INFOCOM,San Diego,CA.USA.March 2010.pp.1-9. This work is partially supported by the National Ba- [9]L.Xie.Q.Li.X.Chen,S.L.Lu and D.X.Chen."Continuous Scanning sic Research Program of China (973)under Grant No. with Mobile Reader in RFID Systems:an Experimental Study,"in MobiHoc,Bangalore,India,Aug.2013. 2009CB320705;the National Natural Science Foundation [10]L.M.Ni,Y.Liu,Y.C.Lau,and A.P.Patil."LANDMARC:indoor of China under Grant No.61100196.61073028.61021062. location sensing using active RFID,"Wireless Nerworks,vol.10,no.6, Pp.701-710,Nov.2004. 91218302;the JiangSu Natural Science Foundation under [11]H.J.Lee and M.C.Lee,"Localization of mobile robot based on Grant No.BK2011559. radio frequency identification devices,"in International Joint Conference S/CE-/CASE,Busan,Korea,Oct.2006.pp.5934-5939. [12]S.S.Saad and Z.S.Nakad,"A standalone RFID indoor positioning ReFeRENcES system using passive tags,"IEEE Trans.Industrial Electronics,vol.58. no.5,pp.1961-1970,2011. [1]N.B.Priyantha.A.K.Miu,H.Balakrishnan,and S.Teller,"The cricket [13]W.Zhu,J.Cao,Y.Xu,L.Yang.and J.Kong,"Fault-tolerant RFID compass for context-aware mobile applications,"in Proc.MobiCom, reader localization based on passive RFID tags,"in Proc.INFOCOM, Rome.Italy.July 2001,pp.1-14. [2]M.Minami,Y.Fukuju,K.Hirasawa,S.Yokoyama,M.Mizumachi, Orlando,Florida USA,March 2012,pp.2183-2191. H.Morikawa,and T.Aoyama."DOLPHIN:a practical approach for [14]I.Constandache.X.Bao,M.Azizyan and R.R.Choudhury,"Did you see Bob?:human localization using mobile phones,"in Proc.MobiCom, implementing a fully distributed indoor ultrasonic positioning system," in UbiComp 2004:Ubiguitous Computing,Tokyo,Japan,Sept.2004, Chicago.Illinois,USA.Sept.2010.pp.149-160. [15]T.Camp,J.Boleng and V.Davies,"A survey of mobility models for ad pp.347-365. hoc network research,"Wireless communications and mobile computing, [3]G.Fischer,B.Dietrich,and F.Winkler,"Bluetooth indoor localization system,"in Proc.WPNC,Hanover,Germany,March 2004,pp.147-156. vol2,no.5,pp.483-502,2002. [16]K.Lee,S.Hong.S.J.Kim,I.Rhee and S.Chong,"Slaw:A new [4]M.Azizyan,I.Constandache,and R.Roy Choudhury,"SurroundSense: mobility model for human walks,"in Proc.INFOCOM,Rio de Janeiro, mobile phone localization via ambience fingerprinting,"in Proc.Mobi- Brazil,April 2009,pp.855-863. Com,Beijing.China,Sept.2009,pp.261-272. 18850 100 150 200 250 300 350 400 450 500 0 500 1000 1500 2000 2500 Number of users m Average searching time (s) blind navigation solution our navigation solution centralized navigation solution (a) RW, θR = 200(s), θk = 10 50 100 150 200 250 300 350 400 450 500 0 500 1000 1500 2000 2500 Number of users m Average searching time (s) blind navigation solution our navigation solution centralized navigation solution (b) RWP, θR = 200(s), θk = 10, µ = 18(m) 0 50 100 150 200 200 220 240 260 280 300 320 340 360 380 400 Time to live of request message θ R (s) Average searching time (s) Random Walk (RW) Random Waypoint (RWP) (c) m = 450, θk = 10, µ = 18(m) 1 2 3 4 5 6 7 8 9 10 200 205 210 215 220 225 230 235 240 245 250 Number of event messages θ k Average searching time (s) Random Walk (RW) Random Waypoint (RWP) (d) m = 450, θR = 200(s), µ = 18(m) 0 10 20 30 40 50 60 220 240 260 280 300 320 340 360 380 Expectation of movement region radius µ (m) Average searching time (s) (e) RWP, m = 450, θR = 200(s), θk = 10 0 100 200 300 400 500 600 700 0 500 1000 1500 2000 2500 3000 3500 Time (s) Number of messages event message (RW) event message (RWP) request message (RW) request message (RWP) (f) m = 450, θR = 200(s), θk = 10, µ = 18(m) Fig. 3. Comparison of the average searching time under Random Walk Mobility Model (RW) and Random Way-Point Mobility Model (RWP) with different parameters (number of users m; time to live of request message θR; number of event messages θk; expectation of movement region radius µ). VII. CONCLUSION This paper proposes a framework using RFID-based delay tolerant network for indoor navigation. By sufficiently leverag￾ing the store-forward properties of delay tolerant network, our solution provides an effective mechanism for indoor naviga￾tion. Simulation results show that our solution can efficiently reduce the average searching time of navigation. We discuss the influences of different mobility parameters in the end. VIII. ACKNOWLEDGEMENT This work is partially supported by the National Ba￾sic Research Program of China (973) under Grant No. 2009CB320705; the National Natural Science Foundation of China under Grant No. 61100196, 61073028, 61021062, 91218302; the JiangSu Natural Science Foundation under Grant No. BK2011559. REFERENCES [1] N. B. Priyantha, A. K. Miu, H. Balakrishnan, and S. Teller, “The cricket compass for context-aware mobile applications,” in Proc. MobiCom, Rome, Italy, July 2001, pp. 1-14. [2] M. Minami, Y. Fukuju, K. Hirasawa, S. Yokoyama, M. Mizumachi, H. Morikawa, and T. Aoyama, “DOLPHIN: a practical approach for implementing a fully distributed indoor ultrasonic positioning system,” in UbiComp 2004: Ubiquitous Computing, Tokyo, Japan, Sept. 2004, pp. 347-365. [3] G. Fischer, B. Dietrich, and F. Winkler, “Bluetooth indoor localization system,” in Proc. WPNC, Hanover, Germany, March 2004, pp. 147-156. [4] M. Azizyan, I. Constandache, and R. 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