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Realistic performance analysis of WSN protocols through trace based simulation

Published: 17 October 2010 Publication History

Abstract

It is a difficult endeavor to realistically evaluate the performance of wireless sensor network (WSN) protocols. Generic network simulators are often used, but they tend to rely on synthetic models. Because WSN performance can be affected by many subtle features, these simulators lack a certain level of realism. The most realistic performance assessment is to implement the protocol in question and observe its performance in a real world deployment. This approach, however, is time consuming, costly, and makes the direct comparison of various protocols nearly impossible. We believe there exists a need to evaluate the real-world performance of WSN protocols in a controlled and repeatable fashion. To that end, we enable trace based WSN simulation by first enhancing an existing WSN profiler that automates the collection of connectivity traces and the generation of statistical link properties. We then present a trace based WSN simulator built on the discrete event simulator SimPy using the standard Python. The use of the high level language Python allows new WSN protocols to be rapidly prototyped and evaluated under the real-world conditions captured by the WSN profiler. To validate the premise that our simulation results closely model the real-world performance of the same protocol, we present a thorough performance analysis of the modern WSN collection tree protocol (CTP). Our approach enables the creation and use of a WSN trace database collected from various deployment environments. Such a database could be used to both fairly and more realistically benchmark existing WSN protocols and provide timely feedback on the real-world performance of protocols still in the development process.

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Cited By

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  • (2024)Cost‐Efficient Network Design in Multichannel WSNs With Power Control: A Grey Wolf Optimization Approach to Routing and ClusteringInternational Journal of Distributed Sensor Networks10.1155/2024/13571952024:1Online publication date: 20-Aug-2024
  • (2020) Trace‐based simulation for 6TiSCH Internet Technology Letters10.1002/itl2.1623:4Online publication date: 22-May-2020
  • (2018)Simulating Opportunistic Networks: Survey and Future DirectionsIEEE Communications Surveys & Tutorials10.1109/COMST.2017.278218220:2(1547-1573)Online publication date: Oct-2019
  • Show More Cited By

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cover image ACM Conferences
PE-WASUN '10: Proceedings of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
October 2010
114 pages
ISBN:9781450302760
DOI:10.1145/1868589
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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Publication History

Published: 17 October 2010

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Author Tags

  1. experimental validation
  2. performance analysis
  3. simpy
  4. trace based simulation

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Overall Acceptance Rate 70 of 240 submissions, 29%

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Cited By

View all
  • (2024)Cost‐Efficient Network Design in Multichannel WSNs With Power Control: A Grey Wolf Optimization Approach to Routing and ClusteringInternational Journal of Distributed Sensor Networks10.1155/2024/13571952024:1Online publication date: 20-Aug-2024
  • (2020) Trace‐based simulation for 6TiSCH Internet Technology Letters10.1002/itl2.1623:4Online publication date: 22-May-2020
  • (2018)Simulating Opportunistic Networks: Survey and Future DirectionsIEEE Communications Surveys & Tutorials10.1109/COMST.2017.278218220:2(1547-1573)Online publication date: Oct-2019
  • (2017)Ubiquitous sensor network simulation and emulation environments: A surveyJournal of Network and Computer Applications10.1016/j.jnca.2017.05.00993(150-181)Online publication date: Sep-2017
  • (2016)Forest-based supply chain modelling using the SimPy simulation frameworkIFAC-PapersOnLine10.1016/j.ifacol.2016.03.01649:2(90-95)Online publication date: 2016
  • (2014)DrySimProceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems10.1145/2641798.2641838(3-11)Online publication date: 21-Sep-2014
  • (2014)A self-adaptive fault-tolerant systems for a dependable Wireless Sensor NetworksDesign Automation for Embedded Systems10.1007/s10617-013-9126-118:3-4(223-250)Online publication date: 1-Sep-2014
  • (2013)Comparing wireless flooding protocols using trace-based simulationsEURASIP Journal on Wireless Communications and Networking10.1186/1687-1499-2013-1692013:1Online publication date: 19-Jun-2013
  • (2011)A TinyOS based tool for gathering real-world wireless tracesProceedings of the 6th ACM international workshop on Wireless network testbeds, experimental evaluation and characterization10.1145/2030718.2030746(105-106)Online publication date: 19-Sep-2011
  • (2011)Enabling distributed building control with wireless sensor networksProceedings of the 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks10.1109/WoWMoM.2011.5986155(1-3)Online publication date: 20-Jun-2011

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