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Reliability and cost efficiency in coding-based in-network data storage and data retrieval for IoT/WSNs

Abstract : Wireless Sensor Networks (WSN) are made up of small devices limited in terms of memory, processing and energy capacity. They work interconnected and autonomously in order to monitoring a region or an object of interest. The evolution in the development of devices more powerful (with new capability such as energy harvesting and acting) and less expensive made the WSNs a crucial element in the emergence of Internet of Things (IoT). Nonetheless, assuming the new applications and services offered in the IoT scenario, new issues arise in the data management performed in the WSNs. Indeed, in this new context, WSNs have to deal with a large amount of data, now consumed on-demand, while ensure a good trade-off between its reliability and retrievability, and the energy consumption. In the scope of this thesis, we are interested in the data management in the WSN in the context of IoT realm. Specifically, we approach the problem of in-network data storage by posing the following question: How to store data for a short term in the WSNs so that the data could be easily retrieved by the consumers while ensuring the best trade-off between data reliability and conservation of energy resources? Foremost, we propose a reliable data storage scheme based on coding network, and assuming a communication model defined by the Publish/Subscribe paradigm. We validate the efficiency of our proposal by a theoretical analyses that is corroborate by a simulation evaluation. The results show that our scheme achieves a reliability of 80% in data delivery with the best cost-benefit compared to other data storage scheme. Aiming to further improve the performance of the data storage scheme proposed in our first contribution, we propose its optimization (modeling it as a Markov Decision Process (MDP)) in order to store data with optimal trade-off between reliability and communication overhead (in this context, also seen as energy consumption), and in an autonomously and adaptive way. For the best of our knowledge, our optimized data storage scheme is the only to ensure data reliability while adapt itself according to the service requirements and network condition. In addition, we propose a generalization of the mathematical model used in our first contribution, and a system model that defines the integration of WSNs performing our data storage scheme in the context for which it was envisaged, the IoT realm. Our performance evaluation shows that our optimization allows the consumers to retrieve up to 70% more packets than a scheme without optimization whereas increase the network lifetime of 43%.Finally, after being interested in finding the best trade-off between reliability and cost, we now focus on an auxiliary way to reduce the energy consumption in the sensor nodes. As our third contribution, we propose a study, in two parts, to measure how much a node activity scheduling can save energy. First, we propose an improvement in the duty cycle mechanism defined in the 802.15.4. Then, we propose a duty cycle mechanism introduced into our data storage scheme aiming at saving energy in the storage nodes. The simulation results show that our solution to the duty cycle mechanism in 802.15.4 led in considerable saving in energy costs. However, regarding duty cycle in our data storage scheme, it did not end up in more energy saving. Actually, as our optimized scheme already saves as much resource energy as possible while ensuring high reliability, the duty cycle mechanism can not improve the energy saving without compromise the data reliability. Nonetheless, this result corroborates that our scheme, indeed, performs under the optimal trade-off between reliability and communication overhead (consumption energy)
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Camila Helena Souza Oliveira. Reliability and cost efficiency in coding-based in-network data storage and data retrieval for IoT/WSNs. Computation and Language [cs.CL]. Université Paris-Est, 2015. English. ⟨NNT : 2015PESC1134⟩. ⟨tel-01368200⟩



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