Take your time, get it closer: content dissemination within mobile pedestrian crowds

  • Juan Antonio CorderoEmail author
  • Wei Lou


The explosion of traffic demands in the edge of the Internet, mostly by mobile users, is putting under pressure current networking infrastructures. This is particularly acute when huge amounts of users and active wireless devices gather in reduced geographical spaces, increasing the risk of exceeding planned capacity of deployed infrastructure. This trend motivates research on edge computing, and in particular, on mechanisms to offload or address locally part of the user injected traffic at the access infrastructure, thus reducing the need of Internet requests and retrievals. This paper concentrates on the ability of mobile crowds –and corresponding access networks—to fulfill content requests originated within the mesh, with minimal intervention of the Internet infrastructure. Simple heuristics are revisited, proposed, discussed and evaluated to improve autonomous content discovery and dissemination within high-density, low-mobility crowds, by combining notions already explored for MANET routing: deliberate jittering and autonomous distance-based overlay pruning. Results over synthetic networks and real mobility traces indicate that these mechanisms improve efficiency and quality of content request discoveries, by reducing significantly collisions and increasing stability of discovered paths in dense pedestrian crowds.


Mobile pedestrian crowd Wireless multi-hop network Content discovery Heuristic algorithm Flooding Simulation 


  1. 1.
    Jacobson, V., Smetters, D. K., Thornton, J. D., Plass, M. F., Briggs, N. H., & Braynard, R. L. (2009). Networking named content. In ACM CoNEXT’09.Google Scholar
  2. 2.
    Lee, J., Rhee, I., Lee, J., Chong, S., & Yi, Y. (2010). Mobile data offloading: How much can wifi deliver? In ACM CoNEXT.Google Scholar
  3. 3.
    Zhang, J., Xiong, T., & Lou, W. (2014). Community clinic: Economizing mobile cloud service cost via cloudlet group. In MASS 2014.Google Scholar
  4. 4.
    Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge computing: Vision and challenges. IEEE Internet of Things Journal, 3, 637–646.CrossRefGoogle Scholar
  5. 5.
    Beck, M. T., Werner, M., Feld, S., & Schimper, T. (2014). Mobile edge computing: A taxonomy. In Proceedings of the AFIN’2014.Google Scholar
  6. 6.
    Li, Y., Qian, M., Jin, D., Hui, P., Wang, Z., & Chen, S. (2014). Multiple mobile data offloading through disruption tolerant networks. IEEE Transactions on Mobile Computing, 13, 1579–1596.CrossRefGoogle Scholar
  7. 7.
    Chen, X., Wu, J., Cai, Y., Zhang, H., & Chen, T. (2015). Energy-efficient oriented traffic offloading in wireless networks: A brief survey and a learning approach for heterogeneous cellular networks. IEEE Journal on Selected Areas in Communications, 33, 627–640.CrossRefGoogle Scholar
  8. 8.
    Wang, L., & Wu, H. (2014). Fast pairing of device-to-device link underlay for spectrum sharing with cellular users. IEEE Communications Letters, 18, 1803–1806.CrossRefGoogle Scholar
  9. 9.
    Andreev, S., Pyattaev, A., Johnsson, K., Galinina, O., & Koucheryavy, Y. (2014). Cellular traffic offloading onto network-assisted device-to-device connections. IEEE Communications Magazine, 52(4), 20–31.CrossRefGoogle Scholar
  10. 10.
    Fodor, G., Dalman, E., Mildh, G., Parkvall, S., Reider, N., Milós, G., et al. (2012). Design aspects of network assisted device-to-device communications. IEEE Communications Magazine, 50(3), 170–177.CrossRefGoogle Scholar
  11. 11.
    Kaufman, B., Lilleberg, J., & Aazhang, B. (2013). Spectrum sharing scheme between cellular users and ad-hoc device-to-device users. IEEE Transactions on Wireless Communications, 12, 1038–1049.CrossRefGoogle Scholar
  12. 12.
    Zhang, Y., Pan, E., Song, L., Saad, W., Dawy, Z., & Han, Z. (2015). Social network aware device-to-device communication in wireless networks. IEEE Transactions on Wireless Communications, 14, 177–190.CrossRefGoogle Scholar
  13. 13.
    Psaras, I., Rene, S., Katsaros, K. V., Sourlas, V., Pavlou, G., Bezirgiannidis, N., Diamantopoulos, S., Komnios, I., & Tsaoussidis, V. (2016). Keyword-based mobile application sharing. In MobiArch’16.Google Scholar
  14. 14.
    Tseng, Y.-C., Ni, S.-Y., Chen, Y.-S., & Sheu, J.-P. (2002). The broadcast storm problem in a mobile ad hoc network. Wireless Networks, 8, 153–167.CrossRefzbMATHGoogle Scholar
  15. 15.
    Ye, F., Chen, A., Lu, S., & Zhang, L. (2001). A scalable solution to minimum cost forwarding in large sensor networks. In ICCCN’2001.Google Scholar
  16. 16.
    Wang, L., Bayhan, S., Ott, J., Kangasharju, J., Sathiaseelan, A., & Crowcroft, J. (2015). Pro-diluvian: Understanding scoped-flooding for content delivery in information-centric networking. In ACM ICN’15.Google Scholar
  17. 17.
    Chen, W., Guha, R. K., Kwon, T. J., Lee, J., & Hsu, Y.-Y. (2011). A survey and challenges in routing and data dissemination in vehicular ad hoc networks. Wireless Communications and Mobile Computing, 11, 787–795.CrossRefGoogle Scholar
  18. 18.
    Zyba, G., Voelker, G. M., Ioannidis, S., & Diot C. (2011). Dissemination in opportunistic mobile ad-hoc networks: The power of the crowd. In IEEE Infocom.Google Scholar
  19. 19.
    Drolia, U., Mickulicz, N., Gandhia, R., & Narasimhan, P. (2015). Krowd: A key-value store for crowded venues. In MobiArch’15.Google Scholar
  20. 20.
    Ioannidis, S., Chaintreau, A., Massoulie, L. (2009). Optimal and scalable distribution of content updates over a mobile social network. In IEEE Infocom’09.Google Scholar
  21. 21.
    Sasson, Y., Cavin, D., & Schiper, A. (2003). Probabilistic broadcast for flooding in wireless mobile ad hoc networks. In WCNC’03.Google Scholar
  22. 22.
    Nand, P., & Sharma, S. C. (2011). Probability based improved broadcasting for AODV routing protocol. In ICCICS’11.Google Scholar
  23. 23.
    Baccelli, E., Cordero, J. A., & Jacquet, P. (2010). Optimization of critical data synchronization via link overlay RNG in mobile ad hoc networks. In IEEE MASS.Google Scholar
  24. 24.
    Cordero, J. A., Yi, J., & Clausen, T. (2014). An adaptive jitter mechanism for reactive route discovery in sensor networks. Sensors, 14, 14440–14471.CrossRefGoogle Scholar
  25. 25.
    Clausen, T., Dearlove, C., & Adamson, B. (2008). Jitter considerations in mobile ad hoc networks (manets). RFC 5148, IETF.Google Scholar
  26. 26.
    Iosifidis, G., Gao, L., Huang, J., & Tassiulas, L. (2014). Enabling crowd-sourced mobile internet access. In IEEE INFOCOM.Google Scholar
  27. 27.
    Kotz, D., Newport, C., & Elliott, C. (2003). The mistaken axioms of wireless-network research. Dartmouth College Computer Science Technical Report TR2003-467. Accessed 02 May 2018.
  28. 28.
    Zhao, J., & Govindan, R. (2003). Understanding packet delivery performance in dense wireless sensor networks. In SenSys’03.Google Scholar
  29. 29.
    Roy, R. R. (2010). Handbook of mobile ad hoc networks for mobility models. Berlin: Springer.zbMATHGoogle Scholar
  30. 30.
    Carofiglio, G., Gallo, M., Muscariello, L., & Perino, D. (2011). Modeling data transfer in content-centric networking. In ITC’11.Google Scholar
  31. 31.
    Chakeres, I., & Belding-Royer, E. (2005). AODV implementation design and performance evaluation. International Journal of Wireless and Mobile Computing, 2(3).Google Scholar
  32. 32.
    Broch, J., Matz, D. A., Johnson, D. B., Hu, Y.-C., & Jetcheva, J. (1998). A performance comparison of multi-hop wireless ad hoc network routing protocol. In ACM MobiCom.Google Scholar
  33. 33.
    Friedman, R., Hay, D., & Kliot, D. (2009). Jittering broadcast transmissions in manets: Quantification and implementation strategies. Technical Report, Department of Computer Science, Technion.Google Scholar
  34. 34.
    Lenders, V., May, M., & Plattner, B. (2008). Density-based anycast: A robust routing strategy for wireless ad hoc networks. IEEE/ACM Transactions on Networking, 16, 852–863.CrossRefGoogle Scholar
  35. 35.
    Rhee, I., Shin, M., Hong, S., Lee, K., Kim, S., & Chong, S. (2009). Crawdad dataset ncsu/mobilitymodels (v. 2009-07-23).

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of ComputingHong Kong Polytechnic UniversityKowloonHong Kong, China
  2. 2.École polytechniquePalaiseauFrance

Personalised recommendations