4.5 Article

Optimizing FANET Lifetime for 5G Softwarized Network Provisioning

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSM.2022.3193883

关键词

5G mobile communication; Optimization; Mathematical models; Computer architecture; Autonomous aerial vehicles; Task analysis; Routing; 5G; NFV; UAV; service chains; mathematical optimization; virtual function placement

资金

  1. Programma ricerca di Ateneo UNICT 2020-22 linea 2-OMNIA of the University of Catania
  2. MIUR PRIN project Liquid_Edge
  3. POR S6 project

向作者/读者索取更多资源

This paper proposes a comprehensive framework that integrates FANET with a 5G network, aiming to provide interconnected services. Through a mathematical optimization model and two placement strategies, energy consumption can be minimized, leading to increased UAV flight time and network lifetime.
Recently, Flying Ad Hoc Networks (FANET) have been proposed to empower 5G networks to support complex missions and provide ubiquitous connectivity to heterogeneous devices. However, it is needed to cope with the limited UAV capabilities (e.g., limited available energy to supply engines and computing elements, limited computing capabilities), as well as with the need to provide network and application services as foreseen in highly dynamic and time varying 5G ecosystems. This paper presents for the first time a comprehensive framework that integrates a FANET with a 5G network, with the aim of providing services that can be even chained with each other. This model is comprehensive in the sense that it takes into account physical constraints of the devices, as well as features and requirements of traffic flows. For this framework, the paper proposes a mathematical optimization model, allowing Virtual Function (VF) placement and chaining, aimed at minimizing energy consumption and service unsatisfaction probabilities of the FANET as a whole without employing heuristics for the solution of the problem. Two placement strategies named MLP and WMP are introduced and compared with the standard placement strategy named NoShP. An extensive numerical analysis shows that MLP and WMP allow us to well catch network dynamics and to reduce the number of virtual functions needed while decreasing the power consumption, so increasing UAV flight time and network lifetime.

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