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Effect of network topology on localization algorithm’s performance

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Abstract

Localization is an important part of wireless network design. In many internet of things (IoT) and other applications, the information produced by an individual entity or node is of limited use without knowledge of its location. Not only it is needed to report data that is geographically meaningful, but it is also required for services such as geographic and context-based routing protocols, location-aware services, location of sensed events in the physical world, object or target tracking, coverage area management and disaster event notification, like gas leakage detection system. This work is intended to perform comprehensive study on effects of topology on performance of existing range-free localization algorithms, in particular, localization in anisotropic network (irregular areas due to holes). We extended a simulation framework, written in Python, which is specially designed for wireless network simulation and add an interactive generic topology generator module. Our simulation framework also produces interactive charts, plots, and log all relevant simulation results for further analysis. In the first phase of our research we are interested in establishing a comprehensive simulation framework or guideline by implementing the original Distance Vector or DV-Hop algorithm. We first generate multiple isotropic and anisotropic topologies of different shapes and then simulate the DV-Hop localization algorithm. We then analyze the results statistically and visually. Our proposed contribution in this paper provides a framework and guideline to systematically and statistically study and compare different network algorithms.

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Authors and Affiliations

  1. Department of Information and Computer Science, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    Farrukh Shahzad PhD

  2. Department of Computer Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    Tarek R. Sheltami

  3. Jodrey School of Computer Science, Acadia University, Wolfville, NS, B4P 2R6, Canada

    Elhadi M. Shakshuki

  4. American University of Ras Al Khaimah, Ras Al Khaimah, United Arab Emirates

    Elhadi M. Shakshuki

Authors
  1. Farrukh Shahzad PhD
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  2. Tarek R. Sheltami
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  3. Elhadi M. Shakshuki
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Correspondence to Farrukh Shahzad PhD.

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Shahzad, F., Sheltami, T.R. & Shakshuki, E.M. Effect of network topology on localization algorithm’s performance. J Ambient Intell Human Comput 7, 445–454 (2016). https://doi.org/10.1007/s12652-016-0349-4

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  • DOI: https://doi.org/10.1007/s12652-016-0349-4

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