Cloud service selection in IoFT-enabled Multi-access Edge Computing: a Game Theoretic approach

Nowadays, Multi-access Edge Computing (MEC) and Internet of Flying Things (IoFT) clouds are attracting significant attention from both academic and industrial research sectors as a new paradigm for providing flexible and elastic services. This new paradigm utilizes the recent technologies of Cloud Computing (CC) and Internet of things (IoT). The conjunctive application of these new technologies engenders an impressive vision of the future in which everything is connected to the Internet via Fifth Generation (5G) technology that integrates the MEC server; this will provide instant computing applications with low latency and fast service response. In the present study, we propose a Game Theory approach for Cloud Services in MEC- and UAV-enabled networks (GTCS) that enables a normal end user to select the most suitable Unmanned Aerial Vehicle (UAV)-Service-Provider based on a set of specific features, limitations, and prices. Given that every service provider has specific features, limitations, and prices, users must select the most suitable provider. A technique based on Game Theory (GT) is used to select the optimum provider by considering user requirements and UAV provider qualities. Simulation results obtained using the OMNet++ simulator and Inet framework evidence the efficiency and good performance of our method, which presents a low latency of 0.45 s at maximum between the two scenarios, a high successful execution ratio that reaches 100% with 50 Unmanned Aerial Vehicles (UAVs), and good management of energy consumption with only 14.5% energy loss in the worst case.