MobileR : Multi-hop energy efficient localised mobile georouting in wireless sensor and actuator networks

International audienceThis paper addresses the usage of actuators (sensors with controlled mobility) for routing in wireless sensor and actuator networks. Different routing protocols have been proposed to improve routing in terms of energy efficiency through the use of controlled mobility enabled sensors . We introduce MobileR. Unlike literature proposals also using actuators, MobileR considers the cost of a full path toward one of its neighbours instead of the cost of the direct edge toward it. To do so, MobileR computes in advance the possible routing paths over the next hops relying on the one-hop neighbours and their possible relocations. Moreover MobileR is fully localised and stateless. We evaluate our solution in terms of cumulative energy consumption with regard to network density. Experiments show that, with sufficient node degree, energy used for routing is significantly reduced and so network lifetime is extended

Greedy Routing Recovery Using Controlled Mobility in Wireless Sensor Networks

International audienceOne of the most current routing families in wireless sensor networks is geographic routing. Using nodes location, they generally ap- ply a greedy routing that makes a sensor forward data to route to one of its neighbors in the forwarding direction of the destination. If this greedy step fails, the routing protocol triggers a recovery mechanism. Such re- covery mechanisms are mainly based on graph planarization and face traversal or on a tree construction. Nevertheless real-world network pla- narization is very difficult due to the dynamic nature of wireless links and trees are not so robust in such dynamic environments. Recovery steps generally provoke huge energy overhead with possibly long inefficient paths. In this paper, we propose to take advantage of the introduction of controlled mobility to reduce the triggering of a recovery process. We propose Greedy Routing Recovery (GRR) routing protocol. GRR en- hances greedy routing energy efficiency as it adapts network topology to the network activity. Furthermore GRR uses controlled mobility to relocate nodes in order to restore greedy and reduce energy consuming recovery step triggering. Simulations demonstrate that GRR successfully bypasses topology holes in more than 72% of network topologies avoid- ing calling to expensive recovery steps and reducing energy consumption while preserving network connectivity

Routage multi-flots économe en énergie dans les réseaux de capteurs et actionneurs

International audienceL'introduction d'actionneurs capables de se déplacer sur ordre dans les réseaux de capteurs a permis l'émergence d'un nouveau genre de protocoles de routage. Ceux-ci tirent parti de cette nouvelle possibilité de relocaliser les éléments du réseau pour adapter dynamiquement sa topologie au trafic. Ils vont ainsi faire se déplacer physiquement les nœuds au fur et à mesure du routage afin d'optimiser le coût des transmissions radio. Toutefois, dans les réseaux de capteurs, il y a souvent plusieurs nœuds géographiquement proches pour reporter un même événement à la station de base. Les messages routés empruntent alors différents chemins qui sont physiquement proches, et certains nœuds appartiennent à plusieurs d'entre eux. Ces derniers vont alors sans cesse devoir se relocaliser sur les différents chemins et donc mourir prématurément. En réponse à ce problème, nous proposons PAMAL, le premier protocole de routage qui optimise la topologie réseau et sait tirer avantage des intersections des chemins de routage de manière complètement locale. PAMAL va ainsi provoquer la fusion des chemins de routage qui se croisent, et ce de plus en plus près des sources au cours et du temps. Les résultats de simulations montrent que ce comportement associé à un mécanisme d'agrégation permet d'améliorer la durée de vie du réseau de 37 %

Heterogeneous data reduction in WSN: Application to Smart Grids

International audienceThe transformation of existing power grids into Smart Grids (SGs) aims to facilitate grid energy automation for a better quality of service by providing fault tolerance and integrating renewable energy resources in the power market. This evolution towards a smarter electricity grid requires the ability to transmit in real time a maximum of data on the network usage. A Wireless Sensor Network (WSN) distributed across the power grid is a promising solution, given the reduced cost and ease of deployment of such networks. These advantages come up against the unstable radio links and limited resources of WSN. In order to reduce the amount of data sent over the network, and thus reduce energy consumption, data prediction is a potent solution of data reduction. It consists on predicting the values sensed by sensor nodes within certain error threshold, and resides both at the sensors and at the sink. The raw data is sent only if the desired accuracy is not satisfied, thereby reducing data transmission. We focus on time series estimation with Least Mean Square (LMS) for data prediction in WSN, in a Smart Grid context, where several applications with different data types and Quality of Service (QoS) requirements will exist on the same network. LMS proved its simplicity and robustness for a wide variety of applications, but the parameters selection (step size and filter length) can directly affect its global performance, choosing the right ones is then crucial. Having no clear and robust method on how to optimize these parameters for a variety of applications, we propose a modification of the original LMS that consists of training the filter for a certain time with the data itself in order to customize the aforementioned parameters. We consider different types of real data traces for the photo voltaic cells monitoring. Our simulation results provide a better data prediction while minimizing the mean square error compared to an existing solution in literatur

Fonction objectif pour un RPL adapté aux Smart Grids

International audienceL'acheminement des données dans l'Internet des Objets a depuis toujours été un défi. En effet, il s'agit de router des données dans un réseau caractérisé par une hétérogénéité omniprésente : logicielle, matérielle, mais aussi applicative. En réponse, l'IETF (Internet Engineering Task Force) a standardisé le protocole de routage généraliste RPL (Routing Protocol for Low-Power and Lossy networks). Toutefois, RPL n'est pas adapté pour les Smart Grids car sa fonction objectif de base, MRHOF (Minimum Rank with Hysteresis Objective Function) avec ETX (Expected Transmission Count), ne gère pas la qualité de service. Or, dans un Smart Grid, les différents messages de contrôle ou de commande (relevé de compteur, activation d'une centrale) doivent être traités avec une qualité et priorité différente. En réponse, on présente un travail en cours : OFQS. OFQS est une fonction objectif qui comprend une métrique multi-objectifs mOFQS. Cette métrique intègre à la fois la qualité des liens, le délai d'acheminement des paquets et aussi l'énergie restante dans les batteries des noeuds. OFQS/mOFQS assure ainsi une différentiation dans la qualité de service adaptée aux différentes applications des Smart Grids en la comparant avec MRHOF/ETX. Par la suite, notre approche pourra être paramétrée, permettant ainsi à chaque application de choisir son niveau de QoS (Quality of Service) sur la base de ses besoins

QoS-compliant Data Aggregation for Smart Grids

International audienceThe Smart Grid (SG) aims to transform the current electric grid into a "smarter" network where the integration of renewable energy resources, energy efficiency and fault tolerance are the main benefits. A Wireless Sensor Network (WSN) controlling and exchanging messages across the grid is a promising solution because of its infrastructure free and ease of deployment characteristics. This comes at the cost of resource constrained and unstable links for such networks. The management of communication is then an issue: billions of messages with different sizes and priorities are sent across the network. Data aggregation is a potential solution to reduce loads on the communication links, thus achieving a better utilization of the wireless channel and reducing energy consumption. On the other hand, SG applications require different Quality of Service (QoS) priorities. Delays caused by data aggregation must then be controlled in order to achieve a proper communication. In this paper, we propose a work in progress, that consists of a QoS efficient data aggregation algorithm with two aggregation functions for the different traffics in a SG network. We expect to reduce the energy consumption while respecting the data delivery delays for the different SG applications

Green data collection and processing in smart cities

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Heterogeneous data reduction in WSN: Application to Smart Grids

International audienceThe transformation of existing power grids into Smart Grids (SGs) aims to facilitate grid energy automation for a better quality of service by providing fault tolerance and integrating renewable energy resources in the power market. This evolution towards a smarter electricity grid requires the ability to transmit in real time a maximum of data on the network usage. A Wireless Sensor Network (WSN) distributed across the power grid is a promising solution, given the reduced cost and ease of deployment of such networks. These advantages come up against the unstable radio links and limited resources of WSN. In order to reduce the amount of data sent over the network, and thus reduce energy consumption, data prediction is a potent solution of data reduction. It consists on predicting the values sensed by sensor nodes within certain error threshold, and resides both at the sensors and at the sink. The raw data is sent only if the desired accuracy is not satisfied, thereby reducing data transmission. We focus on time series estimation with Least Mean Square (LMS) for data prediction in WSN, in a Smart Grid context, where several applications with different data types and Quality of Service (QoS) requirements will exist on the same network. LMS proved its simplicity and robustness for a wide variety of applications, but the parameters selection (step size and filter length) can directly affect its global performance, choosing the right ones is then crucial. Having no clear and robust method on how to optimize these parameters for a variety of applications, we propose a modification of the original LMS that consists of training the filter for a certain time with the data itself in order to customize the aforementioned parameters. We consider different types of real data traces for the photo voltaic cells monitoring. Our simulation results provide a better data prediction while minimizing the mean square error compared to an existing solution in literatur

Energy Efficient Multi-Flow Routing in Mobile Sensor Networks.

International audienceControlled mobility is one of the most complex challenges in Wireless Sensor Networks (WSN). Only a few routing protocols consider controlled mobility in order to extend the network lifetime. They are all designed to optimize the physical route topology from a source to a destination. However, there is often more than one sensor which reports an event to the sink in WSN. In existing solutions, this leads to oscillation of nodes which belong to different routes and their premature death. Experiments show that the need of a routing path merge solution is high. As a response we propose the first routing protocol which locates and uses paths crossing to adapt the topology to the network traffic in a fully localized way while still optimizing energy efficiency. Furthermore the protocol makes the intersection to move away from the destination, getting closer to the sources, allowing higher data aggregation and energy saving. Our approach outperforms existing solutions and extends network lifetime up to 37%

Prototyping a Multi-Root ONS

International audienceThe Object Naming System (ONS) is a central lookup service used in the EPCglobal network for retrieving location information about a specific Electronic Product Code (EPC). This centralized solution lacks scalability and fault tolerance and encounters some political issues. We present the design principles of a fully-distributed multi-root solution for ONS lookup service. In distributed systems, the problem of providing a scalable location service requires a dynamic mechanism to associate identification and location. We design, prototype, and evaluate PRONS, a DHT-based solution for the multi-root problem. We show that PRONS achieves significant performance levels while respecting a number of neutrality requirements