505 research outputs found

    Adaptive Data-driven Optimization using Transfer Learning for Resilient, Energy-efficient, Resource-aware, and Secure Network Slicing in 5G-Advanced and 6G Wireless Systems

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    Title from PDF of title page, viewed January 31, 2023Dissertation advisor: Cory BeardVitaIncludes bibliographical references (pages 134-141)Dissertation (Ph.D)--Department of Computer Science and Electrical Engineering. University of Missouri--Kansas City, 20225G–Advanced is the next step in the evolution of the fifth–generation (5G) technology. It will introduce a new level of expanded capabilities beyond connections and enables a broader range of advanced applications and use cases. 5G–Advanced will support modern applications with greater mobility and high dependability. Artificial intelligence and Machine Learning will enhance network performance with spectral efficiency and energy savings enhancements. This research established a framework to optimally control and manage an appropriate selection of network slices for incoming requests from diverse applications and services in Beyond 5G networks. The developed DeepSlice model is used to optimize the network and individual slice load efficiency across isolated slices and manage slice lifecycle in case of failure. The DeepSlice framework can predict the unknown connections by utilizing the learning from a developed deep-learning neural network model. The research also addresses threats to the performance, availability, and robustness of B5G networks by proactively preventing and resolving threats. The study proposed a Secure5G framework for authentication, authorization, trust, and control for a network slicing architecture in 5G systems. The developed model prevents the 5G infrastructure from Distributed Denial of Service by analyzing incoming connections and learning from the developed model. The research demonstrates the preventive measure against volume attacks, flooding attacks, and masking (spoofing) attacks. This research builds the framework towards the zero trust objective (never trust, always verify, and verify continuously) that improves resilience. Another fundamental difficulty for wireless network systems is providing a desirable user experience in various network conditions, such as those with varying network loads and bandwidth fluctuations. Mobile Network Operators have long battled unforeseen network traffic events. This research proposed ADAPTIVE6G to tackle the network load estimation problem using knowledge-inspired Transfer Learning by utilizing radio network Key Performance Indicators from network slices to understand and learn network load estimation problems. These algorithms enable Mobile Network Operators to optimally coordinate their computational tasks in stochastic and time-varying network states. Energy efficiency is another significant KPI in tracking the sustainability of network slicing. Increasing traffic demands in 5G dramatically increase the energy consumption of mobile networks. This increase is unsustainable in terms of dollar cost and environmental impact. This research proposed an innovative ECO6G model to attain sustainability and energy efficiency. Research findings suggested that the developed model can reduce network energy costs without negatively impacting performance or end customer experience against the classical Machine Learning and Statistical driven models. The proposed model is validated against the industry-standardized energy efficiency definition, and operational expenditure savings are derived, showing significant cost savings to MNOs.Introduction -- A deep neural network framework towards a resilient, efficient, and secure network slicing in Beyond 5G Networks -- Adaptive resource management techniques for network slicing in Beyond 5G networks using transfer learning -- Energy and cost analysis for network slicing deployment in Beyond 5G networks -- Conclusion and future scop

    Digital agriculture: research, development and innovation in production chains.

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    Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil

    Efficient Security Protocols for Constrained Devices

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    During the last decades, more and more devices have been connected to the Internet.Today, there are more devices connected to the Internet than humans.An increasingly more common type of devices are cyber-physical devices.A device that interacts with its environment is called a cyber-physical device.Sensors that measure their environment and actuators that alter the physical environment are both cyber-physical devices.Devices connected to the Internet risk being compromised by threat actors such as hackers.Cyber-physical devices have become a preferred target for threat actors since the consequence of an intrusion disrupting or destroying a cyber-physical system can be severe.Cyber attacks against power and energy infrastructure have caused significant disruptions in recent years.Many cyber-physical devices are categorized as constrained devices.A constrained device is characterized by one or more of the following limitations: limited memory, a less powerful CPU, or a limited communication interface.Many constrained devices are also powered by a battery or energy harvesting, which limits the available energy budget.Devices must be efficient to make the most of the limited resources.Mitigating cyber attacks is a complex task, requiring technical and organizational measures.Constrained cyber-physical devices require efficient security mechanisms to avoid overloading the systems limited resources.In this thesis, we present research on efficient security protocols for constrained cyber-physical devices.We have implemented and evaluated two state-of-the-art protocols, OSCORE and Group OSCORE.These protocols allow end-to-end protection of CoAP messages in the presence of untrusted proxies.Next, we have performed a formal protocol verification of WirelessHART, a protocol for communications in an industrial control systems setting.In our work, we present a novel attack against the protocol.We have developed a novel architecture for industrial control systems utilizing the Digital Twin concept.Using a state synchronization protocol, we propagate state changes between the digital and physical twins.The Digital Twin can then monitor and manage devices.We have also designed a protocol for secure ownership transfer of constrained wireless devices. Our protocol allows the owner of a wireless sensor network to transfer control of the devices to a new owner.With a formal protocol verification, we can guarantee the security of both the old and new owners.Lastly, we have developed an efficient Private Stream Aggregation (PSA) protocol.PSA allows devices to send encrypted measurements to an aggregator.The aggregator can combine the encrypted measurements and calculate the decrypted sum of the measurements.No party will learn the measurement except the device that generated it

    Accelerating Audio Data Analysis with In-Network Computing

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    Digital transformation will experience massive connections and massive data handling. This will imply a growing demand for computing in communication networks due to network softwarization. Moreover, digital transformation will host very sensitive verticals, requiring high end-to-end reliability and low latency. Accordingly, the emerging concept “in-network computing” has been arising. This means integrating the network communications with computing and also performing computations on the transport path of the network. This can be used to deliver actionable information directly to end users instead of raw data. However, this change of paradigm to in-network computing raises disruptive challenges to the current communication networks. In-network computing (i) expects the network to host general-purpose softwarized network functions and (ii) encourages the packet payload to be modified. Yet, today’s networks are designed to focus on packet forwarding functions, and packet payloads should not be touched in the forwarding path, under the current end-to-end transport mechanisms. This dissertation presents fullstack in-network computing solutions, jointly designed from network and computing perspectives to accelerate data analysis applications, specifically for acoustic data analysis. In the computing domain, two design paradigms of computational logic, namely progressive computing and traffic filtering, are proposed in this dissertation for data reconstruction and feature extraction tasks. Two widely used practical use cases, Blind Source Separation (BSS) and anomaly detection, are selected to demonstrate the design of computing modules for data reconstruction and feature extraction tasks in the in-network computing scheme, respectively. Following these two design paradigms of progressive computing and traffic filtering, this dissertation designs two computing modules: progressive ICA (pICA) and You only hear once (Yoho) for BSS and anomaly detection, respectively. These lightweight computing modules can cooperatively perform computational tasks along the forwarding path. In this way, computational virtual functions can be introduced into the network, addressing the first challenge mentioned above, namely that the network should be able to host general-purpose softwarized network functions. In this dissertation, quantitative simulations have shown that the computing time of pICA and Yoho in in-network computing scenarios is significantly reduced, since pICA and Yoho are performed, simultaneously with the data forwarding. At the same time, pICA guarantees the same computing accuracy, and Yoho’s computing accuracy is improved. Furthermore, this dissertation proposes a stateful transport module in the network domain to support in-network computing under the end-to-end transport architecture. The stateful transport module extends the IP packet header, so that network packets carry message-related metadata (message-based packaging). Additionally, the forwarding layer of the network device is optimized to be able to process the packet payload based on the computational state (state-based transport component). The second challenge posed by in-network computing has been tackled by supporting the modification of packet payloads. The two computational modules mentioned above and the stateful transport module form the designed in-network computing solutions. By merging pICA and Yoho with the stateful transport module, respectively, two emulation systems, i.e., in-network pICA and in-network Yoho, have been implemented in the Communication Networks Emulator (ComNetsEmu). Through quantitative emulations, the experimental results showed that in-network pICA accelerates the overall service time of BSS by up to 32.18%. On the other hand, using in-network Yoho accelerates the overall service time of anomaly detection by a maximum of 30.51%. These are promising results for the design and actual realization of future communication networks

    Digital agriculture: research, development and innovation in production chains.

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    Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil.Translated by Beverly Victoria Young and Karl Stephan Mokross

    Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

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    This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

    Electronic musical instruments as interactive exhibits in museums

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    Whilst recent museum exhibitions have explored electronic musical instruments, the interpretational focus has been on materiality rather than sounds produced. Similarly, whilst authors have ‘followed the instruments’ to find the people who used and designed them, those who create and shape their sounds remain comparatively hidden. To address this problem, this thesis introduces sound genealogy – a methodology towards following the evolution of a sound through material networks and people - as an interpretational framework to support exhibition teams in explicitly connecting sounds to instrument interfaces using multi-sensory interactive exhibits. Adopting this methodology will improve visitors’ experiences of music and sound content, helping them connect sounds from their lived experiences to the instruments associated with them: demonstrating how material networks can influence a sound’s popularity and musical value over time, whilst drawing attention to the people involved in the design and use of both sounds and instruments. Chapter one positions this research within contemporary exhibition practices and analyses the methodologies and literature that define the scope for upcoming discussions. The involvement of the UK’s Science Museum Group institutions is also highlighted. Chapters two to four present three case-study insights based on observations of objects and their sounds, and the use of representative exhibits, in North American, European, and British museums. These case studies were chosen so as to represent a range of instrument categories (synthesizers, samplers, drum machines) and interpretational foci (interface, sound, function). Interview data obtained from exhibition team members highlights the strategies and challenges in co-creating positive exhibit experiences for diverse audiences. Evidence from these case studies also supports the analyses of theories and concepts from museum studies, science and technology studies, and sound studies in chapters five and six. This helps to position - and advocate for - the adoption of a sound genealogy methodology in demonstrating the value of sound through interactivity. Additionally, the anticipation and management of visitor behaviours is considered in the context of successfully attaining learning and entertainment goals. Finally, chapters seven and eight document the creation and evaluation of an original interactive exhibit by the author, supported by the sound genealogy methodology

    Decentralized Ultra-Reliable Low-Latency Communications through Concurrent Cooperative Transmission

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    Emerging cyber-physical systems demand for communication technologies that enable seamless interactions between humans and physical objects in a shared environment. This thesis proposes decentralized URLLC (dURLLC) as a new communication paradigm that allows the nodes in a wireless multi-hop network (WMN) to disseminate data quickly, reliably and without using a centralized infrastructure. To enable the dURLLC paradigm, this thesis explores the practical feasibility of concurrent cooperative transmission (CCT) with orthogonal frequency-division multiplexing (OFDM). CCT allows for an efficient utilization of the medium by leveraging interference instead of trying to avoid collisions. CCT-based network flooding disseminates data in a WMN through a reception-triggered low-level medium access control (MAC). OFDM provides high data rates by using a large bandwidth, resulting in a short transmission duration for a given amount of data. This thesis explores CCT-based network flooding with the OFDM-based IEEE 802.11 Non-HT and HT physical layers (PHYs) to enable interactions with commercial devices. An analysis of CCT with the IEEE 802.11 Non-HT PHY investigates the combined effects of the phase offset (PO), the carrier frequency offset (CFO) and the time offset (TO) between concurrent transmitters, as well as the elapsed time. The analytical results of the decodability of a CCT are validated in simulations and in testbed experiments with Wireless Open Access Research Platform (WARP) v3 software-defined radios (SDRs). CCT with coherent interference (CI) is the primary approach of this thesis. Two prototypes for CCT with CI are presented that feature mechanisms for precise synchronization in time and frequency. One prototype is based on the WARP v3 and its IEEE 802.11 reference design, whereas the other prototype is created through firmware modifications of the Asus RT-AC86U wireless router. Both prototypes are employed in testbed experiments in which two groups of nodes generate successive CCTs in a ping-pong fashion to emulate flooding processes with a very large number of hops. The nodes stay synchronized in experiments with 10 000 successive CCTs for various modulation and coding scheme (MCS) indices and MAC service data unit (MSDU) sizes. The URLLC requirement of delivering a 32-byte MSDU with a reliability of 99.999 % and with a latency of 1 ms is assessed in experiments with 1 000 000 CCTs, while the reliability is approximated by means of the frame reception rate (FRR). An FRR of at least 99.999 % is achieved at PHY data rates of up to 48 Mbit/s under line-of-sight (LOS) conditions and at PHY data rates of up to 12 Mbit/s under non-line-of-sight (NLOS) conditions on a 20 MHz wide channel, while the latency per hop is 48.2 ”s and 80.2 ”s, respectively. With four multiple input multiple output (MIMO) spatial streams on a 40 MHz wide channel, a LOS receiver achieves an FRR of 99.5 % at a PHY data rate of 324 Mbit/s. For CCT with incoherent interference, this thesis proposes equalization with time-variant zero-forcing (TVZF) and presents a TVZF receiver for the IEEE 802.11 Non-HT PHY, achieving an FRR of up to 92 % for CCTs from three unsyntonized commercial devices. As CCT-based network flooding allows for an implicit time synchronization of all nodes, a reception-triggered low-level MAC and a reservation-based high-level MAC may in combination support various applications and scenarios under the dURLLC paradigm
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