LDM: Link Discovery Method for new Resource Integration

International audienceIn this paper we address the problem of resource discovery in the Linked Open Data cloud (LOD) where data described by different schemas is not always linked. We propose an approach that allows discovery of new links between data. These links can help to match schemas that are conceptually relevant with respect to a given application domain. Furthermore, these links can be exploited during the querying process in order to combine data coming from different sources. In this approach we exploit the semantic knowledge declared in different schemas in order to model: (i) the influences between concept similarities, (ii) the influences between data similarities, and (iii) the influences between data and concept similarities. The similarity scores are computed by an iterative resolution of two non linear equation systems that express the concept similarity computation and the data similarity computation. The proposed approach is illustrated on scientific publication data.Dans ce papier nous nous intéressons au problème de découverte de resource dans le LOD (Linked Open Data), dans lequel les données décrites conformément à différents schémas ne sont pas toujours liées. Les liens sémantiques entre données peuvent aider à la recherche de correspondances entre schémas. De plus ces liens peuvent être exploités au moment des requêtes pour combiner des données décrites dans différentes sources. Dans cette approche, nous exploitons la sémantique des schémas de façon à modéliser : (1) les influences entre similarités de concept, (2) les influences entre similarités de données. Les scores de similarité sont calculés en résolvant itérativement deux systèmes d'équations représentant le calcul des similarités conceptuelles et le calcul des similarités entre données. L'approche est illustrée en utilisant le domaine des publications scientifiques

Transport mechanism for wireless micro sensor network

Wireless sensor network (WSN) is a wireless ad hoc network that consists of very large number of tiny sensor nodes communicating with each other with limited power and memory constrain. WSN demands real-time routing which requires messages to be delivered within their end-to-end deadlines (packet lifetime). This report proposes a novel real-time with load distribution (RTLD) routing protocol that provides real time data transfer and efficient distributed energy usage in WSN. The RTLD routing protocol ensures high packet throughput with minimized packet overhead and prolongs the lifetime of WSN. The routing depends on optimal forwarding (OF) decision that takes into account of the link quality, packet delay time and the remaining power of next hop sensor nodes. RTLD routing protocol possesses built-in security measure. The random selection of next hop node using location aided routing and multi-path forwarding contributes to built-in security measure. RTLD routing protocol in WSN has been successfully studied and verified through simulation and real test bed implementation. The performance of RTLD routing in WSN has been compared with the baseline real-time routing protocol. The simulation results show that RTLD experiences less than 150 ms packet delay to forward a packet through 10 hops. It increases the delivery ratio up to 7 % and decreases power consumption down to 15% in unicast forwarding when compared to the baseline routing protocol. However, multi-path forwarding in RTLD increases the delivery ratio up to 20%. In addition, RTLD routing spreads out and balances the forwarding load among sensor nodes towards the destination and thus prolongs the lifetime of WSN by 16% compared to the baseline protocol. The real test bed experiences only slight differences of about 7.5% lower delivery ratio compared to the simulation. The test bed confirms that RTLD routing protocol can be used in many WSN applications including disasters fighting, forest fire detection and volcanic eruption detection

Implementing the TEA algorithm on sensors

Sensors are tiny computers with limited computational capability and physical resources. The implementation of secure protocols for sensor network is a big challenge. In order to provide high security for sensor networks, it is very important to choose a small, efficient and effective encryption algorithm as a security primitive. The TEA (Tiny Encryption Algorithm) is an efficient algorithm that requires little memory and resources. These features make the TEA a good candidate for security mechanism for sensors. In this paper we describe an implementation of the TEA algorithm on the platform of sensor networks (Berkeley Motes). In our experiment, the data packets obtained from photo and temperature sensors are encrypted on the sensor node using the TEA algorithm. After that, they are sent to the base station by radio. The base station will receive the data packets and forward them to attached PC, where the data packets are decrypted and displayed. We also propose a particular approach to efficiently evaluate the performance of the TEA in terms of execution time on sensor nodes