2,402 research outputs found

    Cooperative end-edge-cloud computing and resource allocation for digital twin enabled 6G industrial IoT

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    End-edge-cloud (EEC) collaborative computing is regarded as one of the most promising technologies for the Industrial Internet of Things (IIoT). It offers effective solutions for managing computationally intensive and delay-sensitive tasks efficiently. Indeed, achieving intelligent manufacturing in the context of 6G networks requires the development of efficient resource scheduling schemes. However, improving the quality of service and resource management in the face of challenges like time-varying physical operating environments of IIoT, task heterogeneity, and the coupling of different resource types is undoubtedly a complex task. In this work, we propose a digital twin (DT) assisted EEC collaborative computing scheme, where DT is utilized to monitor the physical operating environment in real-time and determine the optimal strategy, and the potential deviation between the real values and DT estimates is also considered. We aim to minimize the system cost by optimizing device association, offloading mode, bandwidth allocation, and task split ratio. Our optimization is constrained by the maximum tolerable latency of the task while considering both latency and energy consumption. To solve the collaborative computation and resource allocation (CCRA) problem in the EEC, we propose an algorithm with DT based on Multi-Agent Deep Deterministic Policy Gradient (MADDPG), where each user end (UE) in DT operates as an independent agent to determine the optimum offloading decision autonomously. Simulation results demonstrate the effectiveness of the proposed scheme, which can significantly improve the task success rate compared to benchmark schemes, while reducing the latency and energy consumption of task offloading with the assistance of DT

    Securing NextG networks with physical-layer key generation: A survey

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    As the development of next-generation (NextG) communication networks continues, tremendous devices are accessing the network and the amount of information is exploding. However, with the increase of sensitive data that requires confidentiality to be transmitted and stored in the network, wireless network security risks are further amplified. Physical-layer key generation (PKG) has received extensive attention in security research due to its solid information-theoretic security proof, ease of implementation, and low cost. Nevertheless, the applications of PKG in the NextG networks are still in the preliminary exploration stage. Therefore, we survey existing research and discuss (1) the performance advantages of PKG compared to cryptography schemes, (2) the principles and processes of PKG, as well as research progresses in previous network environments, and (3) new application scenarios and development potential for PKG in NextG communication networks, particularly analyzing the effect and prospects of PKG in massive multiple-input multiple-output (MIMO), reconfigurable intelligent surfaces (RISs), artificial intelligence (AI) enabled networks, integrated space-air-ground network, and quantum communication. Moreover, we summarize open issues and provide new insights into the development trends of PKG in NextG networks

    Authentication enhancement in command and control networks: (a study in Vehicular Ad-Hoc Networks)

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    Intelligent transportation systems contribute to improved traffic safety by facilitating real time communication between vehicles. By using wireless channels for communication, vehicular networks are susceptible to a wide range of attacks, such as impersonation, modification, and replay. In this context, securing data exchange between intercommunicating terminals, e.g., vehicle-to-everything (V2X) communication, constitutes a technological challenge that needs to be addressed. Hence, message authentication is crucial to safeguard vehicular ad-hoc networks (VANETs) from malicious attacks. The current state-of-the-art for authentication in VANETs relies on conventional cryptographic primitives, introducing significant computation and communication overheads. In this challenging scenario, physical (PHY)-layer authentication has gained popularity, which involves leveraging the inherent characteristics of wireless channels and the hardware imperfections to discriminate between wireless devices. However, PHY-layerbased authentication cannot be an alternative to crypto-based methods as the initial legitimacy detection must be conducted using cryptographic methods to extract the communicating terminal secret features. Nevertheless, it can be a promising complementary solution for the reauthentication problem in VANETs, introducing what is known as “cross-layer authentication.” This thesis focuses on designing efficient cross-layer authentication schemes for VANETs, reducing the communication and computation overheads associated with transmitting and verifying a crypto-based signature for each transmission. The following provides an overview of the proposed methodologies employed in various contributions presented in this thesis. 1. The first cross-layer authentication scheme: A four-step process represents this approach: initial crypto-based authentication, shared key extraction, re-authentication via a PHY challenge-response algorithm, and adaptive adjustments based on channel conditions. Simulation results validate its efficacy, especially in low signal-to-noise ratio (SNR) scenarios while proving its resilience against active and passive attacks. 2. The second cross-layer authentication scheme: Leveraging the spatially and temporally correlated wireless channel features, this scheme extracts high entropy shared keys that can be used to create dynamic PHY-layer signatures for authentication. A 3-Dimensional (3D) scattering Doppler emulator is designed to investigate the scheme’s performance at different speeds of a moving vehicle and SNRs. Theoretical and hardware implementation analyses prove the scheme’s capability to support high detection probability for an acceptable false alarm value ≤ 0.1 at SNR ≥ 0 dB and speed ≤ 45 m/s. 3. The third proposal: Reconfigurable intelligent surfaces (RIS) integration for improved authentication: Focusing on enhancing PHY-layer re-authentication, this proposal explores integrating RIS technology to improve SNR directed at designated vehicles. Theoretical analysis and practical implementation of the proposed scheme are conducted using a 1-bit RIS, consisting of 64 × 64 reflective units. Experimental results show a significant improvement in the Pd, increasing from 0.82 to 0.96 at SNR = − 6 dB for multicarrier communications. 4. The fourth proposal: RIS-enhanced vehicular communication security: Tailored for challenging SNR in non-line-of-sight (NLoS) scenarios, this proposal optimises key extraction and defends against denial-of-service (DoS) attacks through selective signal strengthening. Hardware implementation studies prove its effectiveness, showcasing improved key extraction performance and resilience against potential threats. 5. The fifth cross-layer authentication scheme: Integrating PKI-based initial legitimacy detection and blockchain-based reconciliation techniques, this scheme ensures secure data exchange. Rigorous security analyses and performance evaluations using network simulators and computation metrics showcase its effectiveness, ensuring its resistance against common attacks and time efficiency in message verification. 6. The final proposal: Group key distribution: Employing smart contract-based blockchain technology alongside PKI-based authentication, this proposal distributes group session keys securely. Its lightweight symmetric key cryptography-based method maintains privacy in VANETs, validated via Ethereum’s main network (MainNet) and comprehensive computation and communication evaluations. The analysis shows that the proposed methods yield a noteworthy reduction, approximately ranging from 70% to 99%, in both computation and communication overheads, as compared to the conventional approaches. This reduction pertains to the verification and transmission of 1000 messages in total

    Optimization of Beyond 5G Network Slicing for Smart City Applications

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    Transitioning from the current fifth-generation (5G) wireless technology, the advent of beyond 5G (B5G) signifies a pivotal stride toward sixth generation (6G) communication technology. B5G, at its essence, harnesses end-to-end (E2E) network slicing (NS) technology, enabling the simultaneous accommodation of multiple logical networks with distinct performance requirements on a shared physical infrastructure. At the forefront of this implementation lies the critical process of network slice design, a phase central to the realization of efficient smart city networks. This thesis assumes a key role in the network slicing life cycle, emphasizing the analysis and formulation of optimal procedures for configuring, customizing, and allocating E2E network slices. The focus extends to catering to the unique demands of smart city applications, encompassing critical areas such as emergency response, smart buildings, and video surveillance. By addressing the intricacies of network slice design, the study navigates through the complexities of tailoring slices to meet specific application needs, thereby contributing to the seamless integration of diverse services within the smart city framework. Addressing the core challenge of NS, which involves the allocation of virtual networks on the physical topology with optimal resource allocation, the thesis introduces a dual integer linear programming (ILP) optimization problem. This problem is formulated to jointly minimize the embedding cost and latency. However, given the NP-hard nature of this ILP, finding an efficient alternative becomes a significant hurdle. In response, this thesis introduces a novel heuristic approach the matroid-based modified greedy breadth-first search (MGBFS) algorithm. This pioneering algorithm leverages matroid properties to navigate the process of virtual network embedding and resource allocation. By introducing this novel heuristic approach, the research aims to provide near-optimal solutions, overcoming the computational complexities associated with the dual integer linear programming problem. The proposed MGBFS algorithm not only addresses the connectivity, cost, and latency constraints but also outperforms the benchmark model delivering solutions remarkably close to optimal. This innovative approach represents a substantial advancement in the optimization of smart city applications, promising heightened connectivity, efficiency, and resource utilization within the evolving landscape of B5G-enabled communication technology

    Analysis and Design of Non-Orthogonal Multiple Access (NOMA) Techniques for Next Generation Wireless Communication Systems

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    The current surge in wireless connectivity, anticipated to amplify significantly in future wireless technologies, brings a new wave of users. Given the impracticality of an endlessly expanding bandwidth, there’s a pressing need for communication techniques that efficiently serve this burgeoning user base with limited resources. Multiple Access (MA) techniques, notably Orthogonal Multiple Access (OMA), have long addressed bandwidth constraints. However, with escalating user numbers, OMA’s orthogonality becomes limiting for emerging wireless technologies. Non-Orthogonal Multiple Access (NOMA), employing superposition coding, serves more users within the same bandwidth as OMA by allocating different power levels to users whose signals can then be detected using the gap between them, thus offering superior spectral efficiency and massive connectivity. This thesis examines the integration of NOMA techniques with cooperative relaying, EXtrinsic Information Transfer (EXIT) chart analysis, and deep learning for enhancing 6G and beyond communication systems. The adopted methodology aims to optimize the systems’ performance, spanning from bit-error rate (BER) versus signal to noise ratio (SNR) to overall system efficiency and data rates. The primary focus of this thesis is the investigation of the integration of NOMA with cooperative relaying, EXIT chart analysis, and deep learning techniques. In the cooperative relaying context, NOMA notably improved diversity gains, thereby proving the superiority of combining NOMA with cooperative relaying over just NOMA. With EXIT chart analysis, NOMA achieved low BER at mid-range SNR as well as achieved optimal user fairness in the power allocation stage. Additionally, employing a trained neural network enhanced signal detection for NOMA in the deep learning scenario, thereby producing a simpler signal detection for NOMA which addresses NOMAs’ complex receiver problem

    Digitalization and Development

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    This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the intermediary organizations essential for the orderly performance of socioeconomic agents. The book incisively reviews policy instruments critical for the effective and orderly development of the embedding organizations, and the regulatory framework needed to quicken the appropriation of socioeconomic synergies from digitalization and Industry 4.0 technologies. It highlights the importance of collaboration between government, academic and industry partners, as well as makes key recommendations on how to encourage adoption of IR4.0 technologies in the short- and long-term. This book bridges the concepts and applications of digitalization and Industry 4.0 and will be a must-read for policy makers seeking to quicken the adoption of its technologies

    Natural and Technological Hazards in Urban Areas

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    Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events

    Communications-Aware Robotics: Challenges and Opportunities

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    The use of Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs) has seen significant growth in the research community, industry, and society. Many of these agents are equipped with communication systems that are essential for completing certain tasks successfully. This has led to the emergence of a new interdisciplinary field at the intersection of robotics and communications, which has been further driven by the integration of UAVs into 5G and 6G communication networks. However, one of the main challenges in this research area is how many researchers tend to oversimplify either the robotics or the communications aspects, hindering the full potential of this new interdisciplinary field. In this paper, we present some of the necessary modeling tools for addressing these problems from both a robotics and communications perspective, using the UAV communications relay as an example.Comment: 6 pages, 4 figures, accepted for presentation to the 2023 International Conference on Unmanned Aircraft Systems (ICUAS) at Lazarski University, Warsaw, Polan
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