Experimental Comparison of Routing Protocols for Wireless Sensors Networks: Routing Overhead and Asymmetric Links

Audéoud, Henry-Joseph; Heusse, Martin

doi:10.23919/itc.2017.8064339

Cited by 4 publications

(2 citation statements)

References 20 publications

(21 reference statements)

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“…Routing in multi-hop low power networks requires dedicated routing protocols like RPL [1], LOADng [2] or LRP [3]. These protocols have to keep their own footprint small while selecting the best way to route the data traffic.…”

Section: Introductionmentioning

confidence: 99%

Quick and Efficient Link Quality Estimation in Wireless Sensors Networks

Audéoud

Heusse

2018

2018 14th Annual Conference on Wireless on-Demand Network Systems and Services (WONS)

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In wireless sensor networks, link metric estimation at each hop should not require a long history of packet exchanges. In this paper, we explore several approaches to link quality estimation. We report on the results of experiments on the Grenoble testbed of the FIT IoT-lab composed of a set of Cortex M3 nodes with IEEE 802.15.4 radios. Whereas the received signal power is a poor indication of PDR (Packet Delivery Ratio) that one can expect on a given link, LQI (Link Quality Indicator) gives more accurate information. We propose a two stage classification, in which a very large fraction of links are immediately either deemed usable or not, while the remaining ones need a bit more testing before they are advertised by the routing protocol as good or weak links.

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Section: Introductionmentioning

confidence: 99%

Quick and Efficient Link Quality Estimation in Wireless Sensors Networks

Audéoud

Heusse

2018

2018 14th Annual Conference on Wireless on-Demand Network Systems and Services (WONS)

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“…An RPL comparison to another routing protocol called LRP is provided in [ 22 ]. The authors compare RPL and LRP in small-scale deployments.…”

Section: Related Workmentioning

confidence: 99%

Toward a Detailed Evaluation of Wireless Industrial Data Distribution Approaches

Raptis

Formica

Pagani

et al. 2022

Sensors

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Data distribution is a cornerstone of efficient automation for intelligent machines in Industry 4.0. Although in the recent literature there have been several comparisons of relevant methods, we identify that most of those comparisons are either theoretical or based on abstract simulation tools, unable to uncover the specific, detailed impacts of the methods to the underlying networking infrastructure. In this respect, as a first contribution of this paper, we develop more detailed and fine-tuned solutions for robust data distribution in smart factories on stationary and mobile scenarios of wireless industrial networking. Using the technological enablers of WirelessHART, RPL and the methodological enabler of proxy selection as building blocks, we compose the protocol stacks of four different methods (both centralized and decentralized) for data distribution in wireless industrial networks over the IEEE 802.15.4 physical layer. We implement the presented methods in the highly detailed OMNeT++ simulation environment and we evaluate their performance via an extensive simulation analysis. Interestingly enough, we demonstrate that the careful selection of a limited set of proxies for data caching in the network can lead to an increased data delivery success rate and low data access latency. Next, we describe two test cases demonstrated in an industrial smart factory environment. First, we show the collaboration between robotic elements and wireless data services. Second, we show the integration with an industrial fog node which controls the shop-floor devices. We report selected results in much larger scales, obtained via simulations.

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