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Context-aware mechanisms for device discovery optimization

Abstract : Research in communication networks aims to improve the capabilities and performance of network technologies, and to satisfy the ever increasing demand for instant information access and exchange. For example, work on Fifth Generation (5G) Wireless Systems aims to increase data rates and spectral efficiency while lowering latency and energy consumption. Within this context, proximity-based networking is being considered in order to improve the data sharing between nearby devices, regardless of the availability of additional infrastructure. An integral component of these solutions is the ability to quickly detect (or discover) other systems in the vicinity. While system and service discovery has been a concept used in networks for some time, its adoption by wireless networks has increased the importance and relevance of this type of mechanisms. Therefore, the goal of this thesis is to optimize the performance of the discovery process by using context-aware mechanisms. First, we start by an introductory description of the challenges faced by network users and how current solutions (i.e. Long Term Evolution (LTE)) are unable to cover their needs. Second, we present the architecture we will use to evaluate our proposals, namely the device-to-device (D2D) architecture defined by the Third-Generation Partnership Program (3GPP) for use in LTE networks, with an emphasis on the description of the discovery process as defined in the standard specifications. Then, we present an analytical study, along with an implementation model to test and validate the performance of direct discovery. Building upon that analysis, we propose an adaptive transmission algorithm that optimizes the discovery process for static topologies. This contribution is used as the foundation for extended and enhanced algorithms targeting scenarios where the availability of historic data allows for predicting user density fluctuations, and fully dynamic situations without external infrastructure or support, showing how context-aware mechanisms can provide almost optimal performance. All these contributions and analysis are supported and validated by simulation models and experiments that showcase the importance and correctness of our proposals in the optimization of the performance and reliability in D2D direct discovery
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Submitted on : Monday, February 19, 2018 - 1:19:05 PM
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  • HAL Id : tel-01712303, version 1

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Aziza Ben Mosbah. Context-aware mechanisms for device discovery optimization. Networking and Internet Architecture [cs.NI]. Institut National des Télécommunications, 2017. English. ⟨NNT : 2017TELE0018⟩. ⟨tel-01712303⟩

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