Kamini Garg
Silvia Giordano
ABSTRACT
In this paper, we study the impact of node density on data dissemination time and achieved data quality in a distributed people-centric system. Our results are obtained through an extensive simulation campaign employing Random Way Point and Random Direction mobility and realistic node densities of real environments. Our simulation results show that, the impact of node density does not significantly affect the data dissemination time after a certain threshold of node density, without compromising the achieved data quality. This result is evident for both mobility models. Our study provides an insight to the parameters we need to consider while evaluating the success of any distributed people-centric system.
- T. Abdelzaher, Y. Anokwa, P. Boda, J. Burke, D. Estrin, L. Guibas, A. Kansal, S. Madden, and J. Reich. Mobiscopes for human spaces. In IEEE Pervasive Computing, Vol. 6, No. 2, pages 20--29. IEEE, 2007. Google Scholar
Digital Library
- L. Becchetti, A. Clementi, F. Pasquale, G. Resta, P. Santi, and R. Silvestri. Flooding time in opportunistic networks under power law and exponential inter-contact times. In arXiv preprint arXiv:1107.5241, 2011.Google Scholar
- C. Bettstetter. Smooth is better than sharp: a random mobility model for simulation of wireless networks. In Proceedings of the 4th ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems, pages 19--27. ACM, 2001. Google ScholarDigital Library
- C. Bettstetter, C. Wagner, et al. The spatial node distribution of the random waypoint mobility model. In German Workshop on Mobile Ad Hoc Networks (WMAN), pages 41--58. Citeseer, 2002. Google ScholarDigital Library
- C. Boldrini and A. Passarella. Data dissemination in opportunistic networks. Mobile Ad Hoc Networking: Cutting Edge Directions, Second Edition, pages 453--490, 2013.Google ScholarCross Ref
- A. T. Campbell, S. B. Eisenman, N. D. Lane, E. Miluzzo, and R. A. Peterson. People-centric urban sensing. In Proceedings of the 2nd annual international workshop on Wireless internet, page 18. ACM, 2006. Google ScholarDigital Library
- M. Conti, S. Giordano, M. May, and A. Passarella. From opportunistic networks to opportunistic computing. volume 48, pages 126--139. IEEE, 2010. Google ScholarDigital Library
- S. Eisenman, N. Lane, E. Miluzzo, R. Peterson, G. S. Ahn, and A. Campbell. Metrosense project: People-centric sensing at scale. In Workshop on World-Sensor-Web (WSW 2006), Boulder. ACM, 2006.Google Scholar
- R. K. Ganti, N. Pham, H. Ahmadi, S. Nangia, and T. F. Abdelzaher. Greengps: A participatory sensing fuel-efficient maps application. In Proceedings of the 8th international conference on Mobile systems, applications, and services. ACM, 2010. Google ScholarDigital Library
- S. Giordano and D. Puccinelli. The human element as the key enabler of pervasiveness. In In 10th IEEE IFIP Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net 2011). IEEE, 2011.Google ScholarCross Ref
- X. Hong, M. Gerla, G. Pei, and C.-C. Chiang. A group mobility model for ad hoc wireless networks. In Proceedings of the 2nd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems, pages 53--60. ACM, 1999. Google ScholarDigital Library
- B. Hull, V. Bychkovsky, Y. Zhang, K. Chen, M. Goraczko, A. Miu, E. Shih, H. Balakrishnan, and S. Madden. Cartel: a distributed mobile sensor computing system. In Proceedings of the 4th international conference on Embedded networked sensor systems, pages 125--138. ACM, 2006. Google ScholarDigital Library
- E. Miluzzo and G. Lane. Cenceme - injecting sensing presence into social networking applications. In Proceedings of the 2nd European Conference on Smart Sensing and Context, pages 1--28. Springer LNCS, 2007. Google ScholarDigital Library
- R. Murty, A. Gosain, M. Tierney, A. Brody, A. Fahad, J. Bers, and M. Welsh. Citysense: A vision for an urban-scale wireless networking testbed. In Proceedings of the 2008 IEEE International Conference on Technologies for Homeland Security, Waltham, MA. IEEE, 2008.Google ScholarCross Ref
- E. H. Ngai, H. Huang, J. Liu, and M. B. Srivastava. Oppsense: Information sharing for mobile phones in sensing field with data repositories. In Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2011 8th Annual IEEE Communications Society Conference, pages 107--115. IEEE, 2011.Google ScholarCross Ref
- OMNET++. http://www.omnetpp.org/.Google Scholar
- A. Pettarin, A. Pietracaprina, G. Pucci, and E. Upfal. Tight bounds on information dissemination in sparse mobile networks. In Proceedings of the 30th annual ACM SIGACT-SIGOPS symposium on Principles of distributed computing, pages 355--362. ACM, 2011. Google ScholarDigital Library
- M. Srivastava, M. Hansen, J. Burke, A. Parker, S. Reddy, G. Saurabh, M. Allman, V. Paxson, and D. Estrin. Wireless urban sensing systems. In Proceedings of the 4th international conference on Embedded networked sensor systems. CENS Technical Report 65, 2006.Google Scholar
- V. H. Tuulos, J. Scheible, and H. Nyholm. Combining web, mobile phones and public displays in large-scale: Manhattan story mashup. In Pervasive Computing Springer Berlin Heidelberg, pages 37--54. Springer, 2007. Google ScholarDigital Library
Index Terms
- A study to understand the impact of node density on data dissemination time in opportunistic networks
Recommendations
Design and performance evaluation of ContentPlace, a social-aware data dissemination system for opportunistic networks
In this paper we present and evaluate ContentPlace, a data dissemination system for opportunistic networks, i.e., mobile networks in which stable simultaneous multi-hop paths between communication endpoints cannot be provided. We consider a scenario in ...
Heuristic Routing Protocol Research on Opportunistic Networks
HPCC '12: Proceedings of the 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and SystemsOpportunistic network is a kind of ad hoc networks which exploits the nodes' meeting opportunities to transmit messages. Routing protocols have a great impact on the efficiency of data transmitting in opportunistic networks, but common routing protocols ...
Modelling data dissemination in opportunistic networks
CHANTS '08: Proceedings of the third ACM workshop on Challenged networksIn opportunistic networks data dissemination is an important, although not widely explored, topic. Since opportunistic networks topologies are very challenged and unstable, data-centric approaches are an interesting direction to pursue. Data should be ...
Comments