Handover-Aware Content Replication for Mobile-CDN

Bilen, Tuğçe; Canberk, Berk

doi:10.1109/lnet.2018.2873982

Cited by 9 publications

(4 citation statements)

References 7 publications

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“…This omnidirectional antennas can execute the signal transmission in all directions; for this reason, it could be considered more suitable for AANETs. Additionally, we consider each aircraft as a router with the capacity to receive, queue and route packets to its neighbors according to the AANET concept and we model these queues according to the G/G/1 system with buffer size of 30 packets [37]. This maximum size is selected to reduce the drops caused by queuing overflow.…”

Section: J O U R N a L P R E -P R O O Fmentioning

confidence: 99%

Q-Learning Driven Routing for Aeronautical Ad-Hoc Networks

Bilen

Canberk²

2022

Pervasive and Mobile Computing

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Section: J O U R N a L P R E -P R O O Fmentioning

confidence: 99%

Q-Learning Driven Routing for Aeronautical Ad-Hoc Networks

Bilen

Canberk²

2022

Pervasive and Mobile Computing

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“…These advantages are achieved by establishing air-to-air (A2A) links between airplanes that execute packet transfer, as shown in Figure 1 . More specifically, airplanes’ packets are transferred through A2A links in an ad hoc manner until reaching the destination node having Internet connectivity [ 3 , 4 ]. Each plane acts as a router for packet transfer in this formed network without the assistance of any centralized terminal.…”

Section: Introductionmentioning

confidence: 99%

AI-Driven Aeronautical Ad Hoc Networks for 6G Wireless: Challenges, Opportunities, and the Road Ahead

Bilen

Canberk

Sharma

et al. 2022

Sensors

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Aeronautical ad hoc network (AANET) has been considered a promising candidate to complete the vision of “Internet in the sky” by supporting high-speed broadband connections on airplanes for 6G networks. However, the specific characteristics of AANET restrict the applicability of conventional topology and routing management algorithms. Here, these conventional methodologies reduce the packet delivery success of AANET with higher transfer delay. At that point, the artificial intelligence (AI)-driven solutions have been adapted to AANET to provide intelligent frameworks and architectures to cope with the high complexity. The AI-driven AANET can provide intelligent topology formation, sustainability, and routing management decisions in an automated fashion by considering its specific characteristics during the learning operations. More clearly, AI-driven AANETs support intelligent management architectures, overcoming conventional methodologies’ drawbacks. Although AI-based management approaches are widely used in terrestrial networks, there is a lack of a comprehensive study that supports AI-driven solutions for AANETs. To this end, this article explores the possible utilization of primary AI methodologies on the road to AI-driven AANET. Specifically, the article addresses unsupervised, supervised, and reinforcement learning as primary AI methodologies to enable intelligent AANET topology formation, sustainability, and routing management. Here, we identify the challenges and opportunities of these primary AI methodologies during the execution of AANET management. Furthermore, we discuss the critical issue of security in AANET before providing open issues.

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“…The more content delivery systems grow, the more complex security their security management becomes [18]. Among advances in content delivery, one may mention CDNs [19][20][21]. These networks serve to high-performance delivery of digital contents as well as streaming of audio and video in collaboration with other technologies such as cloud computing [22,23].…”

Section: Introductionmentioning

confidence: 99%

A Survey on Piracy Protection Techniques in Digital Cinema Watermarking Schemes

Zolfaghari¹,

Mitra²

2020

Recent Trends in Communication Networks

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Watermarking is used in several areas such as CDNs (Content Delivery Networks), as part of the rights management system for counterfeit prevention. Watermarking schemes need some additional features in order to be used in digital cinema. In fact, extra watermarks are added to movies by cinema projectors in projection time, which help identify the cinema hall in which the illegal copy has been recorded. But distortions caused by hand vibrations and the point of view angle make it difficult to recover the watermark. This makes it necessary to be distortionresistant for the watermarking schemes used in digital cinema. On the other hand, theatre owners would like to locate the camcorder that has recorded the pirate copy. This requires watermarking schemes to be able to estimate the distance and angle using the distributed pirate copy. In this chapter, we present a review on watermarking techniques specifically designed to attack the aforementioned problems.

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Handover-Aware Content Replication for Mobile-CDN

Cited by 9 publications

References 7 publications

Q-Learning Driven Routing for Aeronautical Ad-Hoc Networks

Q-Learning Driven Routing for Aeronautical Ad-Hoc Networks

AI-Driven Aeronautical Ad Hoc Networks for 6G Wireless: Challenges, Opportunities, and the Road Ahead

A Survey on Piracy Protection Techniques in Digital Cinema Watermarking Schemes

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