Tables of integrals

hysteresis in magnetism (electromagnetism)

Unmanned Aerial Vehicles (UAVs) have become increasingly important in assisting 5G and beyond 5G (B5G) mobile networks. Indeed, UAVs have all the potentials to both satisfy the ever-increasing mobile data demands of such mobile networks and provide ubiquitous connectivity to different kinds of wireless devices. However, the UAV assistance paradigm faces a set of crucial issues and challenges. For example, the network management of current UAV-assisted systems is time consuming, complicated, and carried out manually, thus causing a multitude of interoperability issues. To efficiently address all these issues, Software-Defined Network (SDN) and Network Function Virtualization (NFV) are two promising technologies to efficiently manage and improve the UAV assistance for the next generation of mobile networks. In the literature, no clear guidelines are describing the different use cases of SDN and NFV in the context of UAV assistance to terrestrial networks, including mobile networks. Motivated by this fact, in this survey, we guide the reader through a comprehensive discussion of the main characteristics of SDN and NFV technologies. Moreover, we provide a thorough analysis of the different classifications, use cases, and challenges related to UAV-assisted systems. We then discuss SDN/NFV-enabled UAV-assisted systems, along with several case studies and issues, such as the involvement of UAVs in cellular communications, monitoring, and routing, to name a few. We furthermore present a set of open research challenges, high-level insights, and future research directions related to UAV-assisted systems.

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Softwarization of UAV Networks: A Survey of Applications and Future Trends

The increasing population across the globe makes it essential to link smart and sustainable city planning with the logistics of transporting people and goods, which will significantly contribute to how societies will face mobility in the coming years. The concept of smart mobility emerged with the popularity of smart cities and is aligned with the sustainable development goals defined by the United Nations. A reduction in traffic congestion and new route optimizations with reduced ecological footprint are some of the essential factors of smart mobility; however, other aspects must also be taken into account, such as the promotion of active mobility and inclusive mobility, encouraging the use of other types of environmentally friendly fuels and engagement with citizens. The Internet of Things (IoT), Artificial Intelligence (AI), Blockchain and Big Data technology will serve as the main entry points and fundamental pillars to promote the rise of new innovative solutions that will change the current paradigm for cities and their citizens. Mobility-as-a-service, traffic flow optimization, the optimization of logistics and autonomous vehicles are some of the services and applications that will encompass several changes in the coming years with the transition of existing cities into smart cities. This paper provides an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it. An overview of how smart mobility fits into smart cities is provided by characterizing its main attributes and the key benefits of using smart mobility in a smart city ecosystem. Further, this paper highlights other various opportunities and challenges related to smart mobility. Lastly, the major services and applications that are expected to arise in the coming years within smart mobility are explored with the prospective future trends and scope.

Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges.

Given the ongoing transition towards a more decentralised and adaptive energy system, the potential of blockchain-enabled smart contracts for the energy sector is being increasingly recognised. Due to their self-executing, customisable and tamper-proof nature, they are seen as a key technology for enabling the transition to a more efficient, transparent and transactive energy market. The applications of smart contracts include coordination of smart electric vehicle charging, automated demand-side response, peer-to-peer energy trading and allocation of the control duties amongst the network operators. Nevertheless, their use in the energy sector is still in its early stages as there are many open challenges related to security, privacy, scalability and billing. In this paper, we systematically review 178 peer-reviewed publications and 13 innovation projects, providing a thorough analysis of the strengths and weaknesses of smart contracts used in the energy sector. This work offers a broad perspective on the opportunities and challenges that stakeholders using this technology face, in both current and emergent markets, such as peer-to-peer energy trading platforms. To provide a roadmap for researchers and practitioners interested in the technology, we propose a systematic model of the smart contracting process, by developing a novel 6-layer architecture, as well as presenting a sample energy contract in pseudocode form and as open-source code. Our analysis focuses on the two mainstream application areas we identify for smart contract use in this area: energy and flexibility trading, and distributed control. The paper concludes with a comprehensive, critical discussion of the advantages and challenges that must be addressed in the area of smart contracts and blockchains in energy, and a set of recommendations that researchers and developers should consider when applying smart contracts to energy system settings. 

https://doi.org/10.1016/j.rser.2021.112013

Smart contracts in energy systems: A systematic review of fundamental approaches and implementations

Energy management is one of the greatest challenges in smart cities. Moreover, the presence of autonomous vehicles makes this task even more complex. In this paper, we propose a data-driven smart grid framework which aims to make smart cities energy-efficient focusing on two aspects: energy trading and autonomous vehicle charging. The framework leverages deep learning, linear optimization, semantic technology, domain-specific modelling notation, simulation and elements of relay protection. The evaluation of deep learning module together with code generation time and energy distribution cost reduction performed within the simulation environment also presented in this paper are given. According to the results, the achieved energy distribution cost reduction varies and depends from case to case.

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Data-driven framework for energy-efficient smart cities

SMADA-Fog: Semantic model driven approach to deployment and adaptivity in fog computing

Recent COVID-19 outbreak has affected both human resources and economy around the world dramatically leading towards pandemic and serious global crisis. In this paper, a simulation environment leveraging the synergy of deep learning-based predictions and linear optimization for efficient resource planning is presented. The proposed solution shows satisfiable prediction performance and enables efficient resource exchange by reducing the trading costs.

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Simulation Environment for Optimal Resource Planning During COVID-19 Crisis

Semantic approach to RIoT autonomous robots mission coordination

Security issues in drone communication include man-in-the-middle attacks, packet replays and forgery. On the other hand, privacy issues include location tracing and lack of user anonymity. Consequently, drone communication security and privacy is critical and as such, numerous schemes have been proposed to address these issues. However, most of the conventional approaches either do not fully address security and privacy issues or result in high communication and computational overheads. In this paper, an efficient authentication protocol is proposed for internet of drones (IoDs) to counter both privacy and security attacks. The simulation results show that this protocol is robust against attacks such as de-synchronization, replays, impersonation, tracing, side channel attacks and offers anonymity, forward and backward key secrecy. It also requires less storage costs and authentication time, while exhibiting average communication and computational overheads.

Nenad Petrovic

Papers

Data-driven framework for energy-efficient smart cities

SMADA-Fog: Semantic model driven approach to deployment and adaptivity in fog computing

Simulation Environment for Optimal Resource Planning During COVID-19 Crisis

Semantic approach to RIoT autonomous robots mission coordination

Efficient PUF Based Authentication Protocol for Internet of Drones