Abstract-Unmanned Aerial Vehicles (UAVs) have enormous potential in the public and civil domains. These are particularly useful in applications where human lives would otherwise be endangered. Multi-UAV systems can collaboratively complete missions more efficiently and economically as compared to single UAV systems. However, there are many issues to be resolved before effective use of UAVs can be made to provide stable and reliable context-specific networks. Much of the work carried out in the areas of Mobile Ad Hoc Networks (MANETs), and Vehicular Ad Hoc Networks (VANETs) does not address the unique characteristics of the UAV networks. UAV networks may vary from slow dynamic to dynamic; have intermittent links and fluid topology. While it is believed that ad hoc mesh network would be most suitable for UAV networks yet the architecture of multi-UAV networks has been an understudied area. Software Defined Networking (SDN) could facilitate flexible deployment and management of new services and help reduce cost, increase security and availability in networks. Routing demands of UAV networks go beyond the needs of MANETS and VANETS. Protocols are required that would adapt to high mobility, dynamic topology, intermittent links, power constraints and changing link quality. UAVs may fail and the network may get partitioned making delay and disruption tolerance an important design consideration. Limited life of the node and dynamicity of the network leads to the requirement of seamless handovers where researchers are looking at the work done in the areas of MANETs and VANETs, but the jury is still out. As energy supply on UAVs is limited, protocols in various layers should contribute towards greening of the network. This article surveys the work done towards all of these outstanding issues, relating to this new class of networks, so as to spur further research in these areas.Index Terms-Unmanned Aerial Vehicle, UAV, Multi-UAV Networks, ad hoc networks, communication networks, wireless mesh networks, software defined network, routing, seamless handover, energy efficiency I. INTRODUCTION A. The growing importance of UAV networksUnmanned Aerial Vehicles (UAVs) are an emerging The latter ones are proving to be quite useful in civilian applications. As described by Daniel and Wietfeld in [1] they are likely to become invaluable inclusions in the operations of police departments, fire brigades and other homeland security organizations in the near future. Besides, advances in electronics and sensor technology have widened the scope of UAV network applications [2] to include applications as diverse as traffic monitoring, wind estimation and remote sensing [3].In this context it would be relevant to mention that the current FAA guidelines allow a government public safety agency to operate unmanned aircraft weighing 4.4 pounds or less, within the line of sight of the operator; less than 400 feet above the ground; during daylight conditions; within Class G airspace; and outside of 5 statute miles from any airport, heliport, seapl...

From 2012 to 2015, her research concerned performance improvement of communication networks. Since 2015, she has been a Graduate Research Assistant with Washington University in St. Louis. Her current research interests include utilizing machine learning and deep learning for network security of the Industrial Internet of Things, Internet of Things, machine learning, cyber-security, secure computer networks, and wireless communications. Marcio A. Teixeira (M'18-SM'18) received the M.Sc. degree in computer science and the Ph.D. degree in electrical engineering from the Federal

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Service Function Chaining (SFC) is the problem of deploying various network service instances over geographically distributed data centers and providing inter-connectivity among them. The goal is to enable the network traffic to flow smoothly through the underlying network, resulting in an optimal quality of experience to the end-users. Proper chaining of network functions leads to optimal utilization of distributed resources. This has been a de-facto model in the telecom industry with network functions deployed over underlying hardware. Though this model has served the telecom industry well so far, it has been adapted mostly to suit the static behavior of network services and service demands due to the deployment of the services directly over physical resources. This results in network ossification with larger delays to the end-users, especially with the data-centric model in which the computational resources are moving closer to end users. A novel networking paradigm, Network Function Virtualization (NFV), meets the user demands dynamically and reduces operational expenses (OpEx) and capital expenditures (CapEx), by implementing network functions in the software layer known as virtual network functions (VNFs). VNFs are then interconnected to form a complete end-toend service, also known as service function chains (SFCs). In this work, we study the problem of deploying service function chains over network function virtualized architecture. Specifically, we study virtual network function placement problem for the optimal SFC formation across geographically distributed clouds. We set up the problem of minimizing inter-cloud traffic and response time in a multi-cloud scenario as an ILP optimization problem, along with important constraints such as total deployment costs and service level agreements (SLAs). We consider link delays and computational delays in our model. The link queues are modeled as M/D/1 (single server/Poisson arrival/deterministic service times) and server queues as M/M/1 (single server/Poisson arrival/exponential service times) based on the statistical analysis. In addition, we present a novel affinity-based approach (ABA) to solve the problem for larger networks. We provide a performance comparison between the proposed heuristic and simple greedy approach (SGA) used in the state-of-the-art systems. Greedy approach has already been widely studied in the literature for the VM placement problem. Especially we compare our proposed heuristic with a greedy approach using first-fit decreasing (FFD) method. By observing the results, we conclude that the affinity-based approach for placing the service functions in the network produces better results compared against the simple greedy (FFD) approach in terms of both, total delays and total resource cost. We observe that with a little compromise (gap of less than 10% of the optimal) in the solution quality (total delays and cost), affinity-based heuristic can solve the larger problem more quickly than ILP.

Network slicing in 5G is expected to essentially change the way in which network operators deploy and manage vertical services with different performance requirements. Efficient and secure slice provisioning algorithms are important since network slices share the limited resources of the physical network. In this article, we first analyze the security issues in network slicing and formulate an Integer Linear Programming (ILP) model for secure 5G core network slice provisioning. Then, we propose a heuristic 5G core network slice provisioning algorithm called VIKOR-CNSP based on VIKOR, which is a multi-criteria decision making (MCDM) method. In the slice node provisioning stage, the node importance is ranked with the VIKOR approach by considering the node resource and topology attributes. The slice nodes are then provisioned according to the ranking results. In the slice link provisioning stage, the k shortest path algorithm is implemented to obtain the candidate physical paths for the slice link, and a strategy for selecting a candidate physical path is proposed to increase the slice acceptance ratio. The strategy first calculates the path factor P f which is the product of the maximum link bandwidth utilization of the candidate physical path and its hop-count, and then chooses the candidate physical path with the smallest P f to host the slice link. Extensive simulations show that the proposed algorithm can achieve the highest slice acceptance ratio and the largest provisioning revenue-to-cost ratio, satisfying the security constraints of 5G core network slice requests. INDEX TERMS 5G core network slice, network slicing, slice provisioning, slice security, VIKOR approach. I. INTRODUCTION With the emergence of new application scenarios, such as Augmented Reality (AR), Industrial Internet of Things (IIoT), and Vehicle-to-Everything (V2X), 5G networks have very diverse communication requirements, including high throughput, ultra-low latency, and ultra-reliability. Table 1 lists the three main application scenarios and corresponding communication requirements in 5G networks defined by the IMT-2020 Focus Group in the Telecommunication Standardization Sector of the International Telecommunications Union (ITU-T) [1]. The one-size-fits-all architecture of traditional mobile networks is unable to meet the myriad service requirements of the 5G networks. In addition, due to the current distributed and heterogeneous network architecture, The associate editor coordinating the review of this manuscript and approving it for publication was Thanh Ngoc Dinh .