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Source traffic modeling in wireless sensor networks for target tracking

Published: 27 October 2008 Publication History

Abstract

Researches around wireless sensor network (WSN) were very prolific recently. However, traffic modeling related WSN research was poorly less. In this paper, source traffic dynamics in a simulated target tracking WSN scenario are explored. We find the source traffic arrival process doesn't follow the usually considered Poisson model. Instead, an ON/OFF model is found to be capable of capturing the burst nature of source traffic arrival. Further, we find the measured ON/OFF periods follow the generalized Pareto distribution perfectly. Mathematical analysis also shows a surprising fact: all ON/OFF period distributions in the experiment exhibit short-tail property, which is a nice property that could be exploited by applications such as anomaly detection and node failure detection.

References

[1]
I. Demirkol, F. Alagöz, H. Delic, and C. Ersoy. Wireless sensor networks for intrusion detection: packet traffic modeling. IEEE Communications Letters, 10(1):22--24, January 2006.
[2]
I. Downard. Simulating sensor networks in ns-2. http://cs.itd.nrl.navy.mil/pubs/docs/nrlsensorsim04.pdf, 2004.
[3]
S. Tang. An analytical traffic flow model for cluster-based wireless sensor networks. In 1st International Symposium on Wireless Pervasive Computing, 2006.
[4]
Q. Wang. Ns2-miun. http://apachepersonal.miun.se/~qinwan/resources.htm.
[5]
X. Zhao, D. Massey, M. Lad, and L. Zhang. On/off model: a new tool to understand bgp update burst. Technical Report 04-819, USC-CSD, August 2004.

Cited By

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  • (2021)Modeling of IIoT Traffic Processing by Intra-Chip NoC Routers of 5G/6G Networks2021 International Siberian Conference on Control and Communications (SIBCON)10.1109/SIBCON50419.2021.9438874(1-5)Online publication date: 13-May-2021
  • (2021)Modeling Flow of Smart City Network: Review and Analysis2021 International Conference on Information Science and Communications Technologies (ICISCT)10.1109/ICISCT52966.2021.9670222(1-6)Online publication date: 3-Nov-2021
  • (2021)Estimation of Hurst Index and Traffic SimulationAdvances in Computer Science for Engineering and Education IV10.1007/978-3-030-80472-5_4(37-46)Online publication date: 21-Jul-2021
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cover image ACM Conferences
PE-WASUN '08: Proceedings of the 5th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
October 2008
110 pages
ISBN:9781605582368
DOI:10.1145/1454609
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 October 2008

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Author Tags

  1. sensor network
  2. target tracking
  3. traffic modeling

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MSWiM '08
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PE-WASUN '08 Paper Acceptance Rate 16 of 42 submissions, 38%;
Overall Acceptance Rate 70 of 240 submissions, 29%

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Cited By

View all
  • (2021)Modeling of IIoT Traffic Processing by Intra-Chip NoC Routers of 5G/6G Networks2021 International Siberian Conference on Control and Communications (SIBCON)10.1109/SIBCON50419.2021.9438874(1-5)Online publication date: 13-May-2021
  • (2021)Modeling Flow of Smart City Network: Review and Analysis2021 International Conference on Information Science and Communications Technologies (ICISCT)10.1109/ICISCT52966.2021.9670222(1-6)Online publication date: 3-Nov-2021
  • (2021)Estimation of Hurst Index and Traffic SimulationAdvances in Computer Science for Engineering and Education IV10.1007/978-3-030-80472-5_4(37-46)Online publication date: 21-Jul-2021
  • (2020)Predicting Internet of Things Data Traffic Through LSTM and Autoregressive Spectrum AnalysisNOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium10.1109/NOMS47738.2020.9110357(1-8)Online publication date: 20-Apr-2020
  • (2020)Traffic modelling of smart city internet of things architectureIET Communications10.1049/iet-com.2019.125214:8(1275-1284)Online publication date: May-2020
  • (2019)Processing of the Gaussian Traffic from IoT Sources by Decentralized Routing Devices2019 International Siberian Conference on Control and Communications (SIBCON)10.1109/SIBCON.2019.8729617(1-4)Online publication date: Apr-2019
  • (2018)Data Traffic Modeling of ML-MAC for Wireless Sensor NetworksIntelligent Communication, Control and Devices10.1007/978-981-10-5903-2_36(347-356)Online publication date: 11-Apr-2018
  • (2017)A two-level hidden Markov model for characterizing data traffic from vehiclesProceedings of the Seventh International Conference on the Internet of Things10.1145/3131542.3131556(1-8)Online publication date: 22-Oct-2017
  • (2017)Augmenting Security of Internet-of-Things Using Programmable Network-Centric Approaches: A Position Paper2017 26th International Conference on Computer Communication and Networks (ICCCN)10.1109/ICCCN.2017.8038504(1-6)Online publication date: Jul-2017
  • (2017)Traffic-aware task placement with guaranteed job completion time for geo-distributed big data2017 IEEE International Conference on Communications (ICC)10.1109/ICC.2017.7996541(1-6)Online publication date: May-2017
  • Show More Cited By

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