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Cognitive control models of multiple access IoT networks using LoRa technology
Affiliation:2. School of Computer Applications, KIIT Deemed to be University, Bhubaneswar, India;1. Université de Nantes, CNRS, IETR UMR 6164, La Roche sur Yon F-85000, France;2. ICCS-Lab, Computer Science Department, AUCE, Beirut, Lebanon;3. LABSTICC, UMR CNRS 6285, ENSTA Bretagne, 2 Rue FranȺois Verny, Brest 29806, France;4. Université de Nantes, CNRS, LS2N UMR 6004, Nantes F-44000, France;5. MIS Department, Lebanese University, Rachaya, Lebanon;1. University Bremen, Institute for Microsensors, -Actuators and -Systems, Otto Hahn Allee 1, 28359 Bremen, Germany;2. Microsensys GmbH, In der Hochstedter Ecke 2, 99098 Erfurt, Germany;3. Competence Center for Fruit Growing - Lake Constance (KOB), Schumacherhof 6, 88213 Ravensburg, Germany;4. Microsystems Center Bremen, Otto Hahn Allee 1, 28359 Bremen, Germany
Abstract:In this paper,we propose a random-access model for describing several wireless communication technologies. These networks have found application in the construction of wireless sensor networks, and the proposed model can be used for flows with different properties, considering the corresponding distribution functions. The model considers the technical features of the LoRa technology and subscriber traffic. We also address the management of random multiple wireless access in a Software-Defined Networking (SDN) like control architectures, and proposing a model for flows with different properties, considering the corresponding distribution functions. We develop a method for optimizing the parameters of an access network by the probability of data delivery. Then we describe the probability of bit error, frame loss, collision, and the choice of network parameters considering the heterogeneity of conditions for different users. Numerical results show the efficiency of our proposed scheme by maintaining the required network parameters in case of its function conditions changing.
Keywords:LoRa  Cognitive control  Multiple random access  Collisions probability  Delivery probability
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