RT Journal Article
T1 An NFV-Based Energy Scheduling Algorithm for a 5G Enabled Fleet of Programmable Unmanned Aerial Vehicles
A1 Tipantuna, Christian
A1 Hesselbach, Xavier
A1 Sanchez Aguero, Victor
A1 Valera Pintor, Francisco
A1 Vidal Fernández, Iván
A1 Nogales Dorado, Borja
AB The fifth generation of mobile networks (5G) is expected to provide diverse and stringent improvements such as greater connectivity, bandwidth, throughput, availability, improved coverage, and lower latency. Considering this, drones or Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) devices are perfect examples of existing technology that can take advantage of the capabilities provided by 5G technology. In particular, UAVs are expected to be an important component of 5G networks implementations and support different communication requirements and applications. UAVs working together with 5G can potentially facilitate the deployment of standalone or complementary communications infrastructures, and, due to its rapid deployment, these solutions are suitable candidates to provide network services in emergency scenarios, natural disasters, and search and rescue missions. An important consideration in the deployment of a programmable drone fleet is to guarantee the reliability and performance of the services through consistent monitoring, control, and management scheme. In this regard, the Network Functions Virtualization (NFV) paradigm, a key technology within the 5G ecosystem, can be used to perform automation, management, and orchestration tasks. In addition, to ensure the coordination and reliability in the communications systems, considering that the UAVs have a finite lifetime and that eventually they must be replaced, a scheduling scheme is needed to guarantee the availability of services and efficient resource utilization. To this end, in this paper is presented an UAV scheduling scheme which leverages the potential offered by NFV. The proposed strategy, based on a brute-force search combinatorial algorithm, allows obtaining the optimal scheduling of UAVs in time, in order to efficiently deploy network services. Simulation results validate the performance of the proposed strategy, by providing the number of drones needed to meet certain levels of serv
PB Wiley
SN 1530-8669
YR 2019
FD 2019-01-01
LK https://hdl.handle.net/10016/31374
UL https://hdl.handle.net/10016/31374
LA eng
NO This work has been supported by the Ministerio de Economía y Competitividad of the Spanish Government under projects TEC2016-76795-C6-1-R and TEC2016-76795-C6-3-R and also AEI/FEDER, UE. Christian Tipantuña acknowledges the support from Escuela Politécnica Nacional (EPN) and from Secretaría de Educación Superior, Ciencia, Tecnología e Innovación (SENESCYT) for his doctoral studies at Universitat Politécnica de Catalunya (UPC).
DS e-Archivo
RD 18 may. 2024