research-article

A study to understand the impact of node density on data dissemination time in opportunistic networks

Authors:

Silvia Giordano,

Anna FörsterAuthors Info & Claims

HP-MOSys '13: Proceedings of the 2nd ACM workshop on High performance mobile opportunistic systems

Pages 9 - 16

https://doi.org/10.1145/2507908.2507919

Published: 03 November 2013 Publication History

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.

References

[1]

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.

Digital Library

[2]

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.

[3]

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.

Digital Library

[4]

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.

Digital Library

[5]

C. Boldrini and A. Passarella. Data dissemination in opportunistic networks. Mobile Ad Hoc Networking: Cutting Edge Directions, Second Edition, pages 453--490, 2013.

[6]

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.

Digital Library

[7]

M. Conti, S. Giordano, M. May, and A. Passarella. From opportunistic networks to opportunistic computing. volume 48, pages 126--139. IEEE, 2010.

Digital Library

[8]

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.

[9]

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.

Digital Library

[10]

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.

[11]

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.

Digital Library

[12]

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.

Digital Library

[13]

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.

Digital Library

[14]

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.

[15]

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.

[16]

OMNET++. http://www.omnetpp.org/.

[17]

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.

Digital Library

[18]

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.

[19]

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.

Digital Library

Cited By

Al Mawla CDedu E(2024)Network Parameter Influence on Communications in Dense Wireless NanonetworksProceedings of the 11th Annual ACM International Conference on Nanoscale Computing and Communication10.1145/3686015.3689360(97-102)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3686015.3689360
Hernández-Orallo EArmero-Martínez ACalafate CManzoni P(2023)Analysis and Evaluation of Tracker Tag EfficiencyWireless Communications & Mobile Computing10.1155/2023/28802292023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/2880229
Rashidibajgan SHupperich T(2022)Improving the Performance of Opportunistic Networks in Real-World Applications Using Machine Learning TechniquesJournal of Sensor and Actuator Networks10.3390/jsan1104006111:4(61)Online publication date: 26-Sep-2022
https://doi.org/10.3390/jsan11040061
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Index Terms

A study to understand the impact of node density on data dissemination time in opportunistic networks
1. Computing methodologies
  1. Modeling and simulation

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Published In

cover image ACM Conferences

HP-MOSys '13: Proceedings of the 2nd ACM workshop on High performance mobile opportunistic systems

November 2013

98 pages

ISBN:9781450323727

DOI:10.1145/2507908

General Chairs:
Constandinos X. Mavromoustakis
University of Nicosia, Cyprus
,
Tasos Dagiuklas
Hellenic Open University, Greece
,
Lei Shu
Guangdong University of Petrochemical Technology, China

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSIM: ACM Special Interest Group on Simulation and Modeling

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2013

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MSWiM '13

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SIGSIM

MSWiM '13: 16th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

November 3 - 8, 2013

Barcelona, Spain

Acceptance Rates

HP-MOSys '13 Paper Acceptance Rate 13 of 35 submissions, 37%;

Overall Acceptance Rate 13 of 35 submissions, 37%

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Cited By

Al Mawla CDedu E(2024)Network Parameter Influence on Communications in Dense Wireless NanonetworksProceedings of the 11th Annual ACM International Conference on Nanoscale Computing and Communication10.1145/3686015.3689360(97-102)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3686015.3689360
Hernández-Orallo EArmero-Martínez ACalafate CManzoni P(2023)Analysis and Evaluation of Tracker Tag EfficiencyWireless Communications & Mobile Computing10.1155/2023/28802292023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/2880229
Rashidibajgan SHupperich T(2022)Improving the Performance of Opportunistic Networks in Real-World Applications Using Machine Learning TechniquesJournal of Sensor and Actuator Networks10.3390/jsan1104006111:4(61)Online publication date: 26-Sep-2022
https://doi.org/10.3390/jsan11040061
Vatandas ZKuladinithi KKillat UTimm-Giel A(2021)Evaluation of Cluster Effect in Mobile Opportunistic Networks2021 17th International Conference on Network and Service Management (CNSM)10.23919/CNSM52442.2021.9615581(84-90)Online publication date: 25-Oct-2021
https://doi.org/10.23919/CNSM52442.2021.9615581
Sati MShanab SElshawesh ASati S(2021)Density and Degree Impact on Opportunistic Network Communications2021 IEEE 1st International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering MI-STA10.1109/MI-STA52233.2021.9464518(705-710)Online publication date: 25-May-2021
https://doi.org/10.1109/MI-STA52233.2021.9464518
Hernández-Orallo EArmero-Martínez A(2020)How Human Mobility Models Can Help to Deal with COVID-19Electronics10.3390/electronics1001003310:1(33)Online publication date: 28-Dec-2020
https://doi.org/10.3390/electronics10010033
Yang BWu ZFan YJiang XShen S(2019)Non-Asymptotic Capacity Study in Multicast Mobile Ad Hoc NetworksIEEE Access10.1109/ACCESS.2019.29253687(115109-115121)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2925368
Chancay-Garcia LHernandez-Orallo EManzoni PCalafate CCano J(2018)Evaluating and Enhancing Information Dissemination in Urban Areas of Interest Using Opportunistic NetworksIEEE Access10.1109/ACCESS.2018.28462016(32514-32531)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2846201
Hernandez-Orallo EMurillo-Arcila MCano JCalafate CConejero JManzoni P(2018)An Analytical Model Based on Population Processes to Characterize Data Dissemination in 5G Opportunistic NetworksIEEE Access10.1109/ACCESS.2017.27797486(1603-1615)Online publication date: 2018
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Orozco JSantos ROchoa SMeseguer R(2017)A Stochastic Approach for Modeling Message Dissemination in Opportunistic NetworksWireless Personal Communications: An International Journal10.1007/s11277-017-4604-697:2(2207-2228)Online publication date: 1-Nov-2017
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