Toward a UTM-Based Service Orchestration for UAVs in MEC-NFV Environment

Bekkouche, Oussama; Bagaa, Miloud; Taleb, Tarik

doi:10.1109/globecom38437.2019.9014200

Cited by 18 publications

(14 citation statements)

References 7 publications

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“…The authors in [34] proposed a service orchestration in network function virtualization (NFV) and edge computing utilizing 5G network for UAVs. They evaluated their scheme by simulating 5 to 25 number of UAVs with a maximum of 20 BSs.…”

Section: G Communication Support For Utm Ecosystemmentioning

confidence: 99%

6G Enabled Unmanned Aerial Vehicle Traffic Management: A Perspective

2021

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Unmanned aerial vehicles (UAVs) and UAV traffic management (UTM) have drawn attention for applications such as parcel delivery, aerial mapping, agriculture, and surveillance based on line-ofsight (LoS) links. UTM is essential to operate multiple fully autonomous UAVs safely beyond the visual line of sight (BVLoS) in the future dense UAV traffic environment. Various research and development teams globally take UTM initiatives and work on platform testing with different industrial partners. In the future, urban airspace will be congested with various types of autonomous aerial vehicles, thereby resulting in complex air-traffic management caused by communication issues. The UTM requires an efficient communication backbone to handle all airborne communication services. Existing cellular networks are suitable only for terrestrial communication and have limitations in supporting aerial communications. These issues motivate the investigation of an appropriate communication technology for advanced UTM systems. Thus, in this study, we present a future perspective of 6G-enabled UTM ecosystems in a very dense and urban air-traffic scenario focusing on non-terrestrial features, including aerial and satellite communication. We also introduce several urban airspace segmentations and discuss a strategic management framework for dynamic airspace traffic management and conflict-free UAV operations. The UTM enhances the adaptive use of the airspace by shaping the airspace with the overall aim of maximizing the capability and efficiency of the network. We also discuss the 6G multi-layer parameters, i.e., space, air, and terrestrial, for safe and efficient urban air transportation in three-dimensional space. Moreover, we discuss the issues and challenges faced by future UTM systems and provide tentative solutions. We subsequently extend the vision of the UTM system and design an advanced and fully autonomous 6G-based UTM system.INDEX TERMS Unmanned Aerial Vehicle, Personalized Aerial Vehicle, UTM system, 6G, traffic management I. INTRODUCTION

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Section: G Communication Support For Utm Ecosystemmentioning

confidence: 99%

6G Enabled Unmanned Aerial Vehicle Traffic Management: A Perspective

2021

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“…UAVs are obliged to follow certain predetermined airway routes, with planned intersections and parking positions [6]. Such routes information can ease control and network integration for UAVs [7], while assuring public safety. The ownership of UAVs impacts service orchestration.…”

Section: Uav Enhanced Network Servicesmentioning

confidence: 99%

A Service-Based Architecture for Enabling UAV Enhanced Network Services

et al. 2020

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This paper provides an overview of enhanced network services, while emphasizing on the role of Unmanned Aerial Vehicles (UAVs) as core network equipment with radio and backhaul capabilities. Initially, we elaborate the various deployment options, focusing on UAVs as airborne radio, backhaul and core network equipment, pointing out the benefits and limitations. We then analyze the required enhancements in the Service-Based Architecture (SBA) to support UAV services including UAV navigation and air traffic management, weather forecasting and UAV connectivity management. The use of airborne UAVs network services is assessed via qualitative means, considering the impact on vehicular applications. Finally, an evaluation has been conducted via a testbed implementation, to explore the performance of UAVs as edge cloud nodes, hosting an Aerial Control System (ACS) function responsible for the control and orchestration of a UAV fleet.

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“…EDGE and SDN, the previous two technologies presented, can be combined with NFV, as shown by Huang et al [148], Yang et al [151], Costa-Requena et al [161], etc. Other relevant contributions combining NFV with other technologies include the works of Bekkouche et al [177], Valsamas et al [178] and Yao et al [179]. Bekkouche et al [177] propose an extended framework for the management and orchestration of unmanned aerial vehicles (UAVs).…”

Section: ) Software-defined Networking (Sdn)mentioning

confidence: 99%

“…Other relevant contributions combining NFV with other technologies include the works of Bekkouche et al [177], Valsamas et al [178] and Yao et al [179]. Bekkouche et al [177] propose an extended framework for the management and orchestration of unmanned aerial vehicles (UAVs). The framework combines NFV and MEC with the functionalities of a UAV traffic management system to satisfy the end-to-end latency requirement without fully compromising the reliability.…”

Section: ) Software-defined Networking (Sdn)mentioning

confidence: 99%

“…Mekikis et al [171] NFV MANO: Scaling Ding et al [172] NFV MANO: Redundancy Nascimento et al [173] NFV MANO: SC Optimization Cho et al [174] NFV MANO: Plcmt & Migr. Sun et al [175] NFV MANO: SC Optimization Fan et al [176] NFV MANO: Redundancy NFV MANO: SC Optimization Bekkouche et al [177] Slice Mgmt: EDGE Selection Slice Mgmt: Offloading NFV MANO: Plcmt & Migr. Valsamas et al [178] Slice Mgmt: Network Stitching Yao et al [179] Slice Mgmt: Network Stitching [183] DP Mgmt: Caching Zhang et al [184] DP Mgmt: Caching Sardara et al [185] Ctxt Awa: Cross-layer Dannewitz et al [186] DP Mgmt: Caching Wang et al [187] Ctxt Awa: Cross-layer Vakilina et al [188] DP Mgmt: Congestion control samas et al [178] and Yao et al [179] present network slicing platforms that support different interconnected services and achieve improved latency and reliability, respectively.…”

Section: ) Software-defined Networking (Sdn)mentioning

confidence: 99%

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A Survey of End-to-End Solutions for Reliable Low-Latency Communications in 5G Networks

Rico

Merino

2020

IEEE Access

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Very low latency and high reliability are two of the main requirements for new applications exploiting 5G networks. This is the case for the remote operation of robots or vehicles, the autonomous interaction of equipment in a factory, autonomous driving and tactile internet applications. Although the TCP/IP stack has been sufficient as the end-to-end solution for most of the history of the Internet, a number of surveys have appeared recently presenting many different methods for managing the end-to-end communication to meet the requirements of various technologies such as that of 5G networks. In this paper, we present a novel classification of the literature focused on new end-to-end solutions and the creation of services towards the support of low latency (1 ms) and high reliability (10-9 error rate) in current and future 5G networks. We specifically highlight how the proposals can be classified according to enabling technologies and the specific method used to achieve success in terms of the latency and reliability. The literature related to end-to-end solutions for reliable low-latency communications are organized according to three main topics: (i) end-to-end protocols that improve communication in terms of latency and reliability, (ii) functionality or technologies implemented on the network to support the current demands, and (iii) application programming interfaces that enhance the correct utilization of those protocols and additional technologies.

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Toward a UTM-Based Service Orchestration for UAVs in MEC-NFV Environment

Cited by 18 publications

References 7 publications

6G Enabled Unmanned Aerial Vehicle Traffic Management: A Perspective

6G Enabled Unmanned Aerial Vehicle Traffic Management: A Perspective

A Service-Based Architecture for Enabling UAV Enhanced Network Services

A Survey of End-to-End Solutions for Reliable Low-Latency Communications in 5G Networks

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