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Multi-hop data forwarding method for crowd sensing networks

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Abstract

The integration of sensing and mobile computing devices has led to the evolution of crowd sensing networks (CSNs). The widespread usage of built-in sensors in mobile devices that are carried by people on a daily basis provides new opportunities for gathering information that can be used in numerous large-scale applications. In most applications for CSNs, opportunistic users want to avoid consuming their own resources if there is no sufficient incentive. Therefore, we need to develop an energy-efficient multi-hop data forwarding method to deliver the sensory data generated by opportunistic users to participatory users. In this study, we present a multi-hop data forwarding method for use in CSNs to facilitate environmental monitoring applications. We use IEEE 802.15.4 to save the battery energy of opportunistic users. The proposed method is based on dynamic source routing (DSR). However, utilizing DSR over IEEE 802.15.4 leads to packet fragmentation, which degrades the network performance, because the header grows as a function of the route length in DSR and due to the limited packet size of IEEE 802.15.4. Therefore, we propose a multi-hop data forwarding method to reduce the header overheads. The novel feature of this method is the abbreviation of an intermediate node’s address. In our evaluation, we estimated the fragmentation ratio and our results showed that the fragmentation ratio of the proposed method remained relatively stable compared with other methods, even as the volume of data increased. The network performance is efficient and effective in terms of the latency and delivery ratio.

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References

  1. Kortuem G, Kawsar F, Fitton D, Sundramoorthy V (2010) Smart objects as building blocks for the internet of things. IEEE Internet Comput 14(1):44–51

    Article  Google Scholar 

  2. Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54(15):2787–2805

    Article  MATH  Google Scholar 

  3. Mainetti L, Patrono L, Vilei A (2011) Evolution of wireless sensor networks towards the internet of things: a survey. In Proceedings of 19th IEEE Conference on Software, Telecommunications and Computer Networks (SoftCOM), pp. 1–6

  4. Bandyopadhyay D, Sen J (2011) Internet of things: applications and challenges in technology and standardization. Springer Wirel Pers Commun 58(1):49–69

    Article  Google Scholar 

  5. Ganti RK, Ye F, Lei H (2011) Mobile crowdsensing: current state and future challenges. IEEE Commun Mag 49(11):32–39

    Article  Google Scholar 

  6. Dutta P, Aoki PM, Kumar N, Mainwaring A, Myers C, Willett W, Woodruff A (2009) Common sense: participatory urban sensing using a network of handheld air quality monitors. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, pp. 349–350

  7. Mao X, Miao X, He Y, Li XY, Liu Y (2012) CitySee: urban CO2 monitoring with sensors. In Proceedings of IEEE INFOCOM, pp. 1611–1619

  8. Hull B, Bychkovsky V, Zhang Y, Chen K, Goraczko M, Miu A, Madden S (2006) CarTel: a distributed mobile sensor computing system. In Proceedings of the 4th ACM Conference on Embedded Networked Sensor Systems, pp. 125–138

  9. Mohan P, Padmanabhan VN, Ramjee R (2008) Nericell: rich monitoring of road and traffic conditions using mobile smartphones. In Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems, pp. 323–336

  10. Mathur S, Kaul S, Gruteser M, Trappe W (2009) ParkNet: a mobile sensor network for harvesting real time vehicular parking information. In Proceedings of the 2009 MobiHoc S 3 Workshop on MobiHoc S 3, pp. 25–28

  11. Reddy S, Parker A, Hyman J, Burke J, Estrin D, Hansen M. (2007) Image browsing, processing, and clustering for participatory sensing: Lessons from a DietSense prototype. In Proceedings of the 4th Workshop on Embedded Networked Sensors, pp. 13–17

  12. Eisenman SB, Miluzzo E, Lane ND, Peterson RA, Ahn GS, Campbell AT (2009) BikeNet: a mobile sensing system for cyclist experience mapping. ACM Trans Sens Netw 6(1):6

    Article  Google Scholar 

  13. Yang H, Kim H, Mtonga K (2014) An efficient privacy-preserving authentication scheme with adaptive key evolution in remote health monitoring system. Peer Peer Netw Appl. doi:10.1007/s12083-014-0299-6

    Google Scholar 

  14. Ma H, Zhao D, Yuan P (2014) Opportunities in mobile crowd sensing. IEEE Commun Mag 52(8):29–35

    Article  Google Scholar 

  15. Lane ND, Eisenman SB, Musolesi M, Miluzzo E, Campbell AT (2008) Urban sensing systems: opportunistic or participatory? In Proceedings of the 9th ACM Workshop on Mobile Computing Systems and Applications, pp. 11–16

  16. Heile RF (2003) Part 15.4: wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs)

  17. Johnson DB (2003) The dynamic source routing protocol for mobile ad hoc networks. draft-ietf-manet-dsr-09. txt

  18. Al-Karaki JN, Kamal AE (2004) Routing techniques in wireless sensor networks: a survey. IEEE Trans Wirel Commun 11(6):6–28

    Article  Google Scholar 

  19. Royer EM, Toh CK (1999) A review of current routing protocols for ad hoc mobile wireless networks. IEEE Pers Commun 6(2):46–55

    Article  Google Scholar 

  20. Jayakumar G, Gopinath G (2007) Ad hoc mobile wireless networks routing protocols-a review. J Comput Sci 3(8):574

    Article  Google Scholar 

  21. Perkins CE, Bhagwat P (1994) Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers. ACM SIGCOMM Comput Commun Rev 24(4):234–244

    Article  Google Scholar 

  22. Chiang CC, Wu HK, Liu W, Gerla M (1997) Routing in clustered multihop, mobile wireless networks with fading channel. In proceedings of IEEE SICON, pp. 197–211

  23. Murthy S, Garcia-Luna-Aceves JJ (1996) An efficient routing protocol for wireless networks. Mob Netw Appl 1(2):183–197

    Article  Google Scholar 

  24. Clausen T, Jacquet P, Adjih C, Laouiti A, Minet P, Muhlethaler P, Viennot L (2003) Optimized link state routing protocol (OLSR). RFC 3626, IETF

  25. Perkins CE, Royer EM (1999) Ad-hoc on-demand distance vector routing. In Proceedings of Second IEEE Workshop on Mobile Computing Systems and Applications, pp. 90–100

  26. Park VD, Corson MS (1997) A highly adaptive distributed routing algorithm for mobile wireless networks. In INFOCOM’97. Sixth Annu Joint Conf IEEE Comput Commun Soc 3:1405–1413

    Google Scholar 

  27. Cheng BN, Wheeler J, Hung B (2013) Internet Protocol Header Compression (IPHC) technology and its applicability on the tactical edge, IEEE Commun Mag 58–65

  28. Degermark M, Nordgren B, Pink S (1999) IP HeaderCompression. RFC 2507, IETF. http://tools.ietf.org/html/rfc2507

  29. Bormann C, Degermark M (2001) RObust Header Compression (ROHC): framework and four profiles: RTP, UDP, ESP, and uncompressed. RFC 3095, IETF. http://tools.ietf.org/html/rfc3095

  30. Cheng BN, Zuena J, Wheeler J, Moore S, Hung B (2013) MANET ip header compression. In IEEE MILCOM’13. pp. 494–503

  31. OMNeT++ (2014) http://www.omnetpp.org/. Accessed 1

  32. MiXim framework (2014) http://mixim.sourceforge.net/ . Accessed 1

  33. Bansal M, Rajput R, Gupta G (1999) Mobile ad hoc networking (MANET): routing protocol performance issues and evaluation considerations. RFC 2501, IETF

  34. Jamieson K, Balakrishnan H (2007) PPR: partial packet recovery for wireless networks. ACM SIGCOMM Comp Commun Rev 37(4):409–420

    Article  Google Scholar 

  35. Chipcon product from Texas Instruments. 2.4 GHz IEEE 802.15.4 /ZigBee-ready RF Transceiver. http://www.ti.com/lit/ds/symlink/cc2420.pdf

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Authors and Affiliations

  1. School of Computer Science and Engineering, Pusan National University, Building #C26, Room#314, ESLAB, 2, Busandaehak-ro 63beon-gil, Geumjeong-gu, Busan, 609-735, South Korea

    Yeonsu Jung & Yunju Baek

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  1. Yeonsu Jung
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  2. Yunju Baek
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Correspondence to Yunju Baek.

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Jung, Y., Baek, Y. Multi-hop data forwarding method for crowd sensing networks. Peer-to-Peer Netw. Appl. 9, 628–639 (2016). https://doi.org/10.1007/s12083-015-0333-3

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