On localisation with robust power control for safety critical wireless sensor networks

A hybrid methodology is proposed for use in low power, safety critical wireless sensor network applications, where quality-of-service orientated transceiver output power control is required to operate in parallel with radio frequency-based localization. The practical implementation is framed in an experimental procedure designed to track a moving agent in a realistic indoor environment. An adaptive time synchronized approach is employed to ensure the positioning technique can operate effectively in the presence of dataloss and where the transmitter output power of the mobile agent is varying due to power control. A deterministic multilateration-based positioning approach is adopted and accuracy is improved by filtering signal strength measurements overtime to account for multipath fading. The location estimate is arrived at by employing least-squares estimation. Power control is implemented at two separate levels in the network topology. First, power control is applied to the uplink between the tracking reference nodes and the centralized access point. A number of algorithms are implemented highlighting the advantage associated with using additional feedback bandwidth, where available, and also the need for effective time delay compensation. The second layer of power control is implemented on the uplink between the mobile agent and the access point and here quantifiable improvements in quality of service and energy efficiency are observed. The hybrid paradigm is extensively tested experimentally on a fully compliant 802.15.4 testbed, where mobility is considered in the problem formulation using a team of fully autonomous robots.A hybrid methodology is proposed for use in low power, safety critical wireless sensor network applications, where quality-of-service orientated transceiver output power control is required to operate in parallel with radio frequency-based localization. The practical implementation is framed in an experimental procedure designed to track a moving agent in a realistic indoor environment. An adaptive time synchronized approach is employed to ensure the positioning technique can operate effectively in the presence of dataloss and where the transmitter output power of the mobile agent is varying due to power control. A deterministic multilateration-based positioning approach is adopted and accuracy is improved by filtering signal strength measurements overtime to account for multipath fading. The location estimate is arrived at by employing least-squares estimation. Power control is implemented at two separate levels in the network topology. First, power control is applied to the uplink between the tracking reference nodes and the centralized access point. A number of algorithms are implemented highlighting the advantage associated with using additional feedback bandwidth, where available, and also the need for effective time delay compensation. The second layer of power control is implemented on the uplink between the mobile agent and the access point and here quantifiable improvements in quality of service and energy efficiency are observed. The hybrid paradigm is extensively tested experimentally on a fully compliant 802.15.4 testbed, where mobility is considered in the problem formulation using a team of fully autonomous robots

Détection et diagnostic des fautes dans des systèmes à base de réseaux de capteurs sans fils

Les pannes sont la règle et non l'exception dans les réseaux de capteurs sans fil. Un nœud capteur est fragile et il peut échouer en raison de l'épuisement de la batterie ou de la destruction par un événement externe. En outre, le nœud peut capter et transmettre des valeurs incorrectes en raison de l'influence de l'environnement sur son fonctionnement. Les liens sont également vulnérables et leur panne peut provoquer un partitionnement du réseau et un changement dans la topologie du réseau, ce qui conduit à une perte ou à un retard des données. Dans le cas où les nœuds sont portés par des objets mobiles, ils peuvent être mis hors de portée de la communication. Les réseaux de capteurs sont également sujets à des attaques malveillantes, telles que le déni de service, l'injection de paquets défectueux, entraînant un comportement inattendu du système et ainsi de suite. En plus de ces défaillances prédéfinies (c'est-à-dire avec des types et symptômes connus), les réseaux de capteurs présentent aussi des défaillances silencieuses qui ne sont pas connues à l'avance, et qui sont très liées au système. En revanche, les applications de RCSF, en particulier les applications de sécurité critiques, telles que la détection d'incendie ou les systèmes d'alarme, nécessitent un fonctionnement continu et fiable du système. Cependant, la garantie d'un fonctionnement correct d'un système pendant l'exécution est une tâche difficile. Cela est dû aux nombreux types de pannes que l'on peut rencontrer dans un tel système vulnérable et non fiable. Une approche holistique de la gestion des fautes qui aborde tous les types de fautes n'existe pas. En effet, les travaux existants se focalisent sur certains états d'incohérence du système. La raison en est simple : la consommation d'énergie augmente en fonction du nombre d'éléments à surveiller, de la quantité d'informations à collecter et parfois à échanger. Dans cette thèse, nous proposons un Framework global pour la gestion des fautes dans un réseau de capteurs. Ce framework, appelé IFTF , fournit une vision complète de l'état du système avec la possibilité de diagnostiquer des phénomènes anormaux. IFTF détecte les anomalies au niveau des données, diagnostique les défaillances de réseau, détecte les défaillances d'applications, et identifie les zones affectées du réseau. Ces objectifs sont atteints grâce à la combinaison efficace d'un service de diagnostic réseau (surveillance au niveau des composants), un service de test d'applications (surveillance au niveau du système) et un système de validation des données. Les deux premiers services résident sur chaque nœud du réseau et le système de validation des données réside sur chaque chef de groupe. Grâce à IFTF, les opérations de maintenance et de reconfiguration seront plus efficaces, menant à un système WSN (Wireless Sensor Network) plus fiable. Du point de vue conception, IFTF fournit de nombreux paramètres ajustables qui le rendent approprié aux divers types d'applications. Les résultats de simulation montrent que la solution présentée est efficace en termes de coût mémoire et d'énergie. En effet, le système de validation des données n'induit pas un surcoût de communication. De plus, le fonctionnement des deux services test et diagnostic augmente la consommation d'énergie de 4% en moyenne, par rapport au fonctionnement du service de diagnostic uniquement.Sensor faults are the rule and not the exception in every Wireless Sensor Network (WSN) deployment. Sensor nodes are fragile, and they may fail due to depletion of batteries or destruction by an external event. In addition, nodes may capture and communicate incorrect readings because of environmental influence on their sensing components. Links are also failure-prone, causing network partitions and dynamic changes in network topology, leading to delays in data communications. Links may fail when permanently or temporarily blocked by an external or environmental condition. Packets may be corrupted due to the erroneous nature of communications. When nodes are embedded or carried by mobile objects, nodes can be taken out of the range of communications. WSNs are also prone to malicious attacks, such as denial of service, injection of faulty packets, leading to unexpected behavior of the system and so on. In addition to these predefined faults or failures (i.e., with known types and symptoms), many times the sensor networks exhibits silent failures that are unknown beforehand and highly system-related. Applications over WSNs, in particular safety critical applications, such as fire detection or burglar alarm systems, require continuous and reliable operation of the system. However, validating that a WSN system will function correctly at run time is a hard problem. This is due to the numerous faults that can be encountered in the resource constrained nature of sensor platforms together with the unreliability of the wireless links networks. A holistic fault management approach that addresses all fault issues does not exist. Existing work most likely misses some potential causes of system failures. The reason is simple : the more elements to monitor, the more information to be collected and sometimes to be exchanged, then the more the energy consumption becomes higher. In this thesis, we propose an Integrated Fault Tolerance Framework (IFTF) that provides a complete picture of the system health with possibility to zoom in on the fault reasons of abnormal phenomena. IFTF detects data anomalies, diagnoses network failures, detects application level failures, identifies affected areas of the network and may determine the root causes of application malfunctioning. These goals are achieved efficiently through combining a network diagnosis service (component/element level monitoring) with an application testing service (system level monitoring) and a data validation system. The first two services reside on each node in the network and the data validation system resides on each cluster head. Thanks to IFTF, the maintenance and reconfiguration operations will be more efficient leading to a more dependable WSN. From the design view, IFTF offers to the application many tunable parameters that make it suitable for various application needs. Simulation results show that the presented solution is efficient both in terms of memory use and power consumption. Data validation system does not incur power consumption (communication overhead). Using testing service combined to diagnosis service incurs a 4 %, on average, increase in power consumption compared to using solely network diagnosis solutions.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

A Novel Scheduling Algorithm for Improved Performance of Multi-Objective Safety-Critical Wireless Sensor Networks Using Long Short-Term Memory

The multiple objective optimisation (MOO) challenges encountered in the context of wireless sensor networks (WSNs) present a formidable NP-hard problem. These issues primarily arise from the constraints imposed by critical factors such as connectivity, coverage, and, most notably, energy consumption. Simultaneously fulfilling these three requirements is no longer considered the standard approach for enhancing system dependability. To illustrate, a prospective solution may optimise one or two of these requirements while bolstering overall network energy efficiency. Nonetheless, prior endeavours documented in the extant literature reveal unexplored avenues for enhancement. Hence, this paper introduces a new methodology aimed at alleviating MOO concerns and thereby enhancing the quality of service (QoS) in WSNs. A long short-term memory (LSTM) model is proposed as an analytical tool to deliver an energy-efficient scheduling solution that aligns and optimises WSN parameters, striving to attain the most favourable system performance. The LSTM algorithm’s effectiveness is assessed through the iterative application of periods, confirming the desired QoS levels. The unique feature of LSTM lies in its capability to observe specific event sequences and subsequently establish them as the system’s default configuration for its entire operational lifespan. Once these favourable parameters are identified, LSTM automatically ensures consistent service availability and reliability throughout the network’s lifespan. The results obtained demonstrate the superiority of the proposed LSTM-based scheduling algorithm in comparison to the self-organising map (SOFM)-based node scheduling algorithm. The LSTM-based approach outperforms the SOFM-based alternative by a remarkable 75% in terms of coverage and exhibits a 20% enhancement in network lifetime, all while maintaining equivalent levels of connectivity (i.e., 99%) in both algorithms