Hücresel ağ teknolojisinin yazılım tanımlı ağlarla optimizasyonu

Recently, 5G and the Internet of Things (IoT) has attracted a plethora of attention due to its promises of higher data rates, and interconnecting our surrounding devices efficiently, inexpensive, and more reliable with their operators. The proliferation demand for data traffic will reach 77.49 exabytes per month in 2022, ushering in a new era of communication including 5G and the IoT. In IoT architecture determining the optimal paths for transmitting data in terms of increasing network data traffic while maintaining energy consumption is a major challenge. Because of the hardware and communication constraints of the objects, the network must be able to perform route discovery operations within a reasonable time frame and avoid imposing computational and traffic burdens on specific resources. In this thesis, a new model to reduce energy consumption in IoT using a combination of game theory and Software-defined networking (SDN) is presented. In this architecture, all IoT objects are connected to an SDN controller, and the management of communication between these objects is performed through the SDN controller node. Once the SDN-based topology is formed, the optimal path between each pair of objects will be discovered and selected by a game theory-based model. This algorithm performs the path selection procedure by considering both energy and delay criteria simultaneously. Evaluating the performance of the proposed method in the simulated environment and comparing its performance with previous research show that the proposed method will reduce the energy consumption and end-to-end delay in the network.