Machine Learning for Unmanned Aerial System (UAS) Networking

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex missions simultaneously. However, the limitations of the conventional approaches are still a big challenge to make a trade-off between the massive management and efficient networking on a large scale. With 5G NR and machine learning, in this dissertation, my contributions can be summarized as the following: I proposed a novel Optimized Ad-hoc On-demand Distance Vector (OAODV) routing protocol to improve the throughput of Intra UAS networking. The novel routing protocol can reduce the system overhead and be efficient. To improve the security, I proposed a blockchain scheme to mitigate the malicious basestations for cellular connected UAS networking and a proof-of-traffic (PoT) to improve the efficiency of blockchain for UAS networking on a large scale. Inspired by the biological cell paradigm, I proposed the cell wall routing protocols for heterogeneous UAS networking. With 5G NR, the inter connections between UAS networking can strengthen the throughput and elasticity of UAS networking. With machine learning, the routing schedulings for intra- and inter- UAS networking can enhance the throughput of UAS networking on a large scale. The inter UAS networking can achieve the max-min throughput globally edge coloring. I leveraged the upper and lower bound to accelerate the optimization of edge coloring. This dissertation paves a way regarding UAS networking in the integration of CPS and machine learning. The UAS networking can achieve outstanding performance in a decentralized architecture. Concurrently, this dissertation gives insights into UAS networking on a large scale. These are fundamental to integrating UAS and National Aerial System (NAS), critical to aviation in the operated and unmanned fields. The dissertation provides novel approaches for the promotion of UAS networking on a large scale. The proposed approaches extend the state-of-the-art of UAS networking in a decentralized architecture. All the alterations can contribute to the establishment of UAS networking with CPS

Novel Interference And Spectrum Aware Routing Techniques}{for Cognitive Radio Ad Hoc Networks

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2011Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2011Yüksek hızlı kablosuz ağlara artan rağbet nedeniyle, radyo spektrumu dünya üzerinde en çok kullanılan ve pahalı doğal kaynaklardan biri haline gelmiştir. Lisanslı spektrumu etkin şekilde kullanma ve paylaşmaya olanak sağlaması nedeniyle radyo spektrumundan yararlanma potansiyelini arttıran bilişsel radyo teknolojisi büyük ilgi toplamaktadır. Söz konusu potansiyelden faydalanmak üzere bilişsel radyo ağları tasarlanırken üzerinde önemle durulması gereken en önemli konulardan bir tanesi de yönlendirmedir. Çalışmamızda bilişsel radyo ağlarında kullanılmak üzere önerilen yönlendirme teknikleri hakkında bir bakış açısı sunulmakla beraber asıl olarak girişim ve spektruma dayalı özgün yönlendirme teknikleri önerilmektedir. Öncelikle, spektrum kullanım karakteristikleri ve ağdaki akışların yarattığı girişim göz önüne alınarak yönlendirme ölçütleri tasarlanmıştır. Ayrıca, bilişsel radyo ağları için otonom dağıtık uyarlanır menzil kontrol stratejisi önerilmiştir. Bu önerilere ek olarak dağıtık ve etkin bir kümeleme tabanlı yönlendirme tekniği geliştirilmiştir. Son olarak, bilişsel radyo ağları için otonom dağıtık uyarlanır menzil kontrol stratejisi ve spektrum erişebilirliği ve girişim maliyeti ölçütlerini bir arada kullanan özgün bir yönlendirme tekniği önerilmiştir. Önerilen yeni yönlendirme ölçütlerinin kullanımı nedeniyle önerilen teknik trafiği kullanılabilir spektrumun daha çok ve girişimin daha az olduğu rotalara yönlendirmektedir. NS2 benzetim ortamı kullanılarak gerçekleştirilen testler, önerilen yöntemlerin bilişsel radyo ağlarına uygunluğunu ve ağ başarımını arttırdığını göstermiştir. Ayrıca güncel bilişsel radyo teknolojisini kullanan diğer yöntemlerle karşılaştırıldığında önerilen tekniklerin hem uçtan uca veri aktarımını arttırdığı hem de uçtan uca gecikmeyi azalttığı ve başarımlarının daha yüksek olduğu gözlemlenmiştir.Radio spectrum has become one of the most heavily used and expensive natural resource around the world because of the growing demand for high-speed wireless networks. Cognitive radio has received great attention due to tremendous potential to improve the utilization of the radio spectrum by efficiently reusing and sharing the licensed spectrum. To design such mobile cognitive radio networks, routing is one of the key challenging issues to be addressed and requires deep investigation. This study gives some insights about the potential routing approaches that can be employed, and suggests novel interference and spectrum aware routing techniques for cognitive radio networks. First, the spectrum usage characteristics, and the interference created by existing flows in the network both from the primary and secondary users are taken into account to define routing metrics. Next, an autonomous distributed adaptive transmission range control scheme for cognitive radio networks is proposed. A distributed and efficient cluster based routing technique, which benefits from new metrics, is also introduced. The last proposed routing algorithm incorporates novel metrics and autonomous distributed adaptive transmission range control mechanism to provide self adaptivity. As a consequence, the proposed protocol routes traffic across paths with better spectrum availability and reduced interference via these new routing metrics. Extensive experimental evaluations are performed in the ns2 simulator to show that proposed protocols provide better adaptability to the environment and maximize throughput, minimize end-to-end delay in a number of realistic scenarios and outperforms recently proposed routing protocols developed for cognitive radio networks.DoktoraPh

Next-Generation Public Safety Systems Based on Autonomous Vehicles and Opportunistic Communications

An emergency scenario is characterized by the unpredictability of the environment conditions and by the scarcity of the available communication infrastructures. After a natural or human disaster, the main public and private infrastructures are partially damaged or totally destroyed. These infrastructures include roads, bridges, water supplies, electrical grids, telecommunications and so on. In these conditions, the first rescue operations executed by the public safety organizations can be very difficult, due to the unpredictability of the disaster area environment and the lack in the communications systems. The aim of this work is to introduce next-generation public safety systems where the main focus is the use of unmanned vehicles that are able to exploit the self-organizing characteristics of such autonomous systems. With the proposed public safety systems, a team of autonomous vehicles will be able to overcome the hazardous environments of a post disaster scenario by introducing a temporary dynamic network infrastructure which enables the first responders to cooperate and to communicate with the victims involved. Furthermore, given the pervasive penetration of smart end-user devices, the emergence of spontaneous networks could constitute promising solutions to implement emergency communication systems. With these systems the survivors will be able to self-organize in a communication network that allows them to send alerts and information messages towards the rescue teams, even in absence of communication infrastructures

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Formulation, implementation considerations, and first performance evaluation of algorithmic solutions - D4.1

Deliverable D4.1 del projecte Europeu OneFIT (ICT-2009-257385)This deliverable contains a first version of the algorithmic solutions for enabling opportunistic networks. The presented algorithms cover the full range of identified management tasks: suitability, creation, QoS control, reconfiguration and forced terminations. Preliminary evaluations complement the proposed algorithms. Implementation considerations towards the practicality of the considered algorithms are also included.Preprin

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms