SensLAB Very Large Scale Open Wireless Sensor Network Testbed

International audienceThis paper presents a precise description of SensLAB: Very Large Scale Open Wireless Sensor Network Testbed that has been developed and deployed in order to allow the evaluation of scalable wireless sensor network protocols and applications. SensLAB's main and most important goal is to o er an accurate open access multi-users scienti c tool to support the design, development, tuning, and experimentation of real large-scale sensor network applications. The SensLAB testbed is composed of 1024 nodes and it is distributed among 4 sites. Two sites o er access to mobile nodes. Every sensor node is also able to be con gured as a sink node and can exchange data with any other sink node of the whole SensLAB testbed (locally or remotely) or any computer on the Internet. The hardware designed on purpose and software architectures that allow to reserve, con gure, deploy embedded software, boot wireless sensor nodes and gather experimental data and monitoring information are described in details. We also present short demonstration examples to illustrate the use of the SensLAB testbed

Using SensLAB as a First Class Scienti c Tool for Large Scale Wireless Sensor Network Experiments

International audienceThis paper presents a description of SensLAB(Very Large Scale Open Wireless Sensor Network Testbed) that has been developed and deployed in order to allow the evaluation through experimentations of scalable wireless sensor network protocols and applications. SensLAB's main and most important goal is to o er an accurate open access multiusers scienti c tool to support the design, the development tuning, and the experimentation of real large-scale sensor network applications. The SensLAB testbed is composed of 1024 nodes over 4 sites. Each site hosts 256 sensor nodes with speci c characteristics in order to o er a wide spectrum of possibilities and heterogeneity. Within a given site, each one of the 256 nodes is able both to communicate via its radio interface to its neighbors and to be con gured as a sink node to exchange data with any other "sink node". The hardware and software architectures that allow to reserve, con gure, deploy rmwares and gather experimental data and monitoring information are described. We also present demonstration examples to illustrate the use of the SensLAB testbed and encourage researchers to test and benchmark their applications/protocols on a large scale WSN testbed

A Survey on Facilities for Experimental Internet of Things Research

International audienceThe initial vision of the Internet of Things (IoT) was of a world in which all physical objects are tagged and uniquelly identified by RFID transponders. However, the concept has grown into multiple dimensions, encompassing sensor networks able to provide real-world intelligence and goal-oriented collaboration of distributed smart objects via local networks or global interconnections such as the Internet. Despite significant technological advances, difficulties associated with the evaluation of IoT solutions under realistic conditions, in real world experimental deployments still hamper their maturation and significant roll out. In this article we identify requirements for the next generation of the IoT experimental facilities. While providing a taxonomy, we also survey currently available research testbeds, identify existing gaps and suggest new directions based on experience from recent efforts in this field

Online Estimation of Battery Lifetime for Wireless Sensors Network

Battery is a major hardware component of wireless sensor networks. Most of them have no power supply and are generally deployed for a long time. Researches have been done on battery physical model and their adaptation for sensors. We present an implementation on a real sensor operating system and how architectural constraints have been assumed. Experiments have been made in order to test the impact of some parameter, as the application throughput, on the battery lifetime

Link Quality Metrics in Large Scale Indoor Wireless Sensor Networks

International audiencePouvoir estimer la qualité d'un lien sur la base d'un minimum de paquets est essentiel pour un réseau de capteur sans fil multisaut en environnement "indoor" compte tenu du coût énergétique de cette estimation et de ses conséquences sur la stabilité des routes construites sur ces liens. Notre étude s'appuie ainsi sur des expérimentations intensives menées sur une plateforme Senslab (\cite{www_senslab}) qui nous ont permis de trouver des lois de distribution suivies par les métriques physiques (RSSI, LQI) pour 3 catégories de liens (bons, mauvais, intermédiaires) regroupés par plage de PRR (Packet Reception Ratio). Sur la base de ces distributions, nous observons comment elles peuvent nous aider à discriminer les différents liens et ainsi les utiliser dans de futures expérimentations pour améliorer l'efficacité de protocoles de routage de réseaux de capteurs dans le choix des liens

A survey of evaluation platforms for ad hoc routing protocols: a resilience perspective

Routing protocols allow for the spontaneous formation of wireless multi-hop networks without dedicated infrastructure, also known as ad hoc networks. Despite significant technological advances, difficulties associated with the evaluation of ad hoc routing protocols under realistic conditions, still hamper their maturation and significant roll out in real world deployments. In particular, the resilience evaluation of ad hoc routing protocols is essential to determine their ability of keeping the routing service working despite the presence of changes, such as accidental faults or malicious ones (attacks). However, the resilience dimension is not always addressed by the evaluation platforms that are in charge of assessing these routing protocols. In this paper, we provide a survey covering current state-of-the-art evaluation platforms in the domain of ad hoc routing protocols paying special attention to the resilience dimension. The goal is threefold. First, we identify the most representative evaluation platforms and the routing protocols they have evaluated. Then, we analyse the experimental methodologies followed by such evaluation platforms. Finally, we create a taxonomy to characterise experimental properties of such evaluation platforms.This work is partially supported by the Spanish Project ARENES (TIN2012-38308-C02-01), the ANR French Project AMORES (ANR-11-INSE-010), and the Intel Doctoral Student Honour Programme 2012.Friginal López, J.; Andrés Martínez, DD.; Ruiz García, JC.; Martínez Raga, M. (2014). A survey of evaluation platforms for ad hoc routing protocols: a resilience perspective. Computer Networks. 75(A):395-413. https://doi.org/10.1016/j.comnet.2014.09.010S39541375

A Distributed Sensor Data Search Platform for Internet of Things Environments

Recently, the number of devices has grown increasingly and it is hoped that, between 2015 and 2016, 20 billion devices will be connected to the Internet and this market will move around 91.5 billion dollars. The Internet of Things (IoT) is composed of small sensors and actuators embedded in objects with Internet access and will play a key role in solving many challenges faced in today's society. However, the real capacity of IoT concepts is constrained as the current sensor networks usually do not exchange information with other sources. In this paper, we propose the Visual Search for Internet of Things (ViSIoT) platform to help technical and non-technical users to discover and use sensors as a service for different application purposes. As a proof of concept, a real case study is used to generate weather condition reports to support rheumatism patients. This case study was executed in a working prototype and a performance evaluation is presented.Comment: International Journal of Services Computing (ISSN 2330-4472) Vol. 4, No.1, January - March, 201

The P2P-RPL Routing Protocol for IPv6 Sensor Networks: Testbed Experiments

International audienceAn important part of the foreseen Internet of Things consists in wireless sensor networks running adapted IPv6 protocols. Since the way sensors are scattered is generally unplanned and may evolve with time, a routing protocol is needed in order to provide paths across such networks. Efforts towards standardizing RPL, a routing protocol tar- geting sensor networks, have thus recently taken place. This paper analyzes some fundamental tradeoffs inherent to RPL, which enables the protocol to require smaller routing state than most other routing protocols. However, these tradeoffs are on the other hand an issue in several Home and Build- ing Automation use-cases, which require sensor to sensor communication - aside of communication from sensor to sink. RPL basically requires that all communication paths go through a central router (the sink), which provides severely suboptimal paths in these use-cases. In order to alleviate this, an extension of the protocol is proposed based on a reactive scheme that can provide shorter paths on-demand, without necessarily going through the sink. This paper then evaluates this extension via experiments on a sensor network testbed running RPL and its extension over IEEE 802.15.4 radio. These experiments confirm that the extension provides substantially shorter paths

Data dissemination scheme for distributed storage for IoT observation systems at large scale

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Algorithmes de localisation distribués en intérieur pour les réseaux sans fil avec la technologie IEEE 802.15.4

The Internet of Things is finally blooming through diverse applications, from home automation and monitoring to health tracking and quantified-self movement. Consumers deploy more and more low-rate and low-power connected devices that provide complex services. In this scenario, positioning these intelligent objects in their environment is necessary to provide geo-localized services, as well as to optimize the network operation. However, indoor positioning of devices using only their radio interface is still very imprecise. Indoor wireless localization techniques often deduce from the Radio frequency (RF) signal attenuation the distances that separate a mobile node from a set of reference points called landmarks. The received signal strength indicator (RSSI), which reflects this attenuation, is known in the literature to be inaccurate and unreliable when it comes to distance estimation, due to the complexity of indoor radio propagation (shadowing, multi-path fading). However, it is the only metric that will certainly be available in small and inexpensive smart objects. In this thesis, we therefore seek algorithmic solutions to the following problem: is it possible to achieve a fair localization using only the RSSI readings provided by low-quality hardware? To this extent, we first study the behavior of the RSSI, as reported by real hardware like IEEE 802.15.4 sensor nodes, in several indoor environments with different sizes and configurations , including a large scale wireless sensor network. Such experimental results confirm that the relationship between RSSI and distance depends on many factors; even the battery pack attached to the devices increases attenuation. In a second step, we demonstrate that the classical log-normal shadowing propagation model is not well adapted in indoor case, because of the RSSI values dispersion and its lack of obvious correlation with distance. We propose to correct the observed inconsistencies by developing algorithms to filter irrelevant samples. Such correction is performed by biasing the classical log-normal shadowing model to take into account the effects of multipath propagation. These heuristics significantly improved RSSI-based indoor localization accuracy results. We also introduce an RSSI-based positioning approach that uses a maximum likelihood estimator conjointly with a statistical model based on machine learning. In a third step, we propose an accurate distributed and cooperative RSSI-based localization algorithm that refines the set of positions estimated by a wireless node. This algorithm is composed of two on-line steps: a local update of position¿s set based on stochastic gradient descent on each new RSSI measurement at each sensor node. Then an asynchronous communication step allowing each sensor node to merge their common local estimates and obtain the agreement of the refined estimated positions. Such consensus approach is based on both a distributed local gradient step and a pairwise gossip protocol. This enables each sensor node to refine its initial estimated position as well as to build a local map of itself and its neighboring nodes. The proposed algorithm is compared to multilateration, Multi Dimensional Scaling (i.e. MDS) with modern majorization problem and classical MDS. Simulation as well as experimental results obtained on real testbeds lead to a centimeter-level accuracy. Both landmarks and blind nodes communicate in the way that the data processing and computation are performed by each sensor node without any central computation point, tedious calibration or intervention from a human.L¿internet des objets se développe à travers diverses applications telles que la domotique, la surveillance à domicile, etc. Les consommateurs s¿intéressent à ces applications dont les objets interagissent avec des dispositifs de plus en plus petits et connectés. La localisation est une information clé pour plusieurs services ainsi que pour l¿optimisation du fonctionnement du réseau. En environnement intérieur ou confiné, elle a fait l¿objet de nombreuses études. Cependant, l¿obtention d¿une bonne précision de localisation demeure une question difficile, non résolue. Cette thèse étudie le problème de la localisation en environnement intérieur appliqué aux réseaux sans fil avec l¿utilisation unique de l¿atténuation du signal. L¿atténuation est mesurée par l¿indicateur de l¿intensité du signal reçu (RSSI). Le RSSI est connu dans la littérature comme étant imprécis et peu fiable en ce qui concerne l¿estimation de la distance, du fait de la complexité de la propagation radio en intérieur : il s¿agit des multiples trajets, le shadowing, le fading. Cependant, il est la seule métrique directement mesurable par les petits objets communicants et intelligents. Dans nos travaux, nous avons amélioré la précision des mesures du RSSI pour les rendre applicables à l¿environnement interne dans le but d¿obtenir une meilleure localisation. Nous nous sommes également intéressés à l¿implémentation et au déploiement de solutions algorithmiques relatifs au problème suivant : est-il possible d¿obtenir une meilleure précision de la localisation en utilisant uniquement les mesures de RSSI fournies par les n¿uds capteurs sans fil IEEE 802.15.4 ? Dans cette perspective, nous avons d¿abord étudié le comportement du RSSI dans plusieurs environnements intérieurs de différentes tailles et selon plusieurs configurations , y compris un réseau de capteurs sans fil à grande échelle (SensLAB). Pour expliquer les résultats des mesures, nous avons caractérisé les objets communicants que nous utilisons, les n¿uds capteurs Moteiv TMote Sky, par une série d¿expériences en chambre anéchoïque. Les résultats expérimentaux confirment que la relation entre le RSSI et la distance dépend de nombreux facteurs même si la batterie intégrée à chaque n¿ud capteur produit une atténuation. Ensuite, nous avons démontré que le modèle de propagation log-normal shadowing n¿est pas adapté en intérieur, en raison de la dispersion des valeurs de RSSI et du fait que celles-ci ne sont pas toujours dépendantes de la distance. Ces valeurs devraient être considérées séparément en fonction de l¿emplacement de chaque n¿ud capteur émetteur. Nous avons proposé des heuristiques pour corriger ces incohérences observées à savoir les effets de la propagation par trajets multiples et les valeurs aberrantes. Nos résultats expérimentaux ont confirmé que nos algorithmes améliorent significativement la précision de localisation en intérieur avec l¿utilisation unique du RSSI. Enfin, nous avons étudié et proposé un algorithme de localisation distribué, précis et coopératif qui passe à l¿échelle et peu consommateur en termes de temps de calcul. Cet algorithme d¿approximation stochastique utilise la technique du RSSI tout en respectant les caractéristiques de l¿informatique embarquée des réseaux de capteurs sans fil. Il affine l¿ensemble des positions estimées par un n¿ud capteur sans fil. Notre approche a été comparée à d¿autres algorithmes distribués de l¿état de l¿art. Les résultats issus des simulations et des expériences en environnements internes réels ont révélé une meilleure précision de la localisation de notre algorithme distribué. L¿erreur de localisation est de l¿ordre du centimètre sans aucun n¿ud ou unité centrale de traitement, ni de calibration fastidieuse ni d¿intervention humaine