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A Tutorial on Performance Evaluation and Validation Methodology for Low-Power and Lossy Networks

Envisioned communication densities in Internet of Things applications are increasing continuously. Because these wireless devices are often battery powered, we need specific energy efficient (low-power) solutions. Moreover, these smart objects use low-cost hardware with possibly weak links, leading...

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Bibliographic Details
Published in:IEEE Communications surveys and tutorials 2018-01, Vol.20 (3), p.1799-1825
Main Authors: Kritsis, Kosmas, Papadopoulos, Georgios Z., Gallais, Antoine, Chatzimisios, Periklis, Theoleyre, Fabrice
Format: Article
Language:English
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Summary:Envisioned communication densities in Internet of Things applications are increasing continuously. Because these wireless devices are often battery powered, we need specific energy efficient (low-power) solutions. Moreover, these smart objects use low-cost hardware with possibly weak links, leading to a lossy network. Once deployed, these low-power lossy networks (LLNs) are intended to collect the expected measurements, handle transient faults, topology changes, etc. Consequently, validation and verification during the protocol development are a matter of prime importance. A large range of theoretical or practical tools are available for performance evaluation. A theoretical analysis may demonstrate that the performance guarantees are respected, while simulations or experiments aim on estimating the behaviour of a set of protocols within real-world scenarios. In this paper, we review the various parameters that should be taken into account during such a performance evaluation. Our primary purpose is to provide a tutorial that specifies guidelines for conducting performance evaluation campaigns of network protocols in LLNs. We detail the general approach adopted in order to evaluate the performance of layer 2 and 3 protocols in LLNs. Furthermore, we also specify the methodology that should be adopted during the performance evaluation, while reviewing the numerous models and tools that are available to the research community.
ISSN:1553-877X
1553-877X
2373-745X
DOI:10.1109/COMST.2018.2820810