Balancing QoS and Security in the Edge: Existing Practices, Challenges, and 6G Opportunities With Machine Learning

Fadlullah, Zubair Md.; Mao, Bomin; Kato, Nei

doi:10.1109/comst.2022.3191697

Cited by 29 publications

(5 citation statements)

References 200 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, the design of the 6G network must not only address these emerging threats but also proactively anticipate and mitigate potential risks through adaptive and trust-oriented security measures [66]. Critical components of multi-level security in 6G networks may encompass diverse security measures, featuring adaptive authentication, authorization, and selective data encryption techniques [67]. This involves leveraging sustainable AI/ML algorithms for zero-touch security implementation [68], implementing energy-aware security policies, deploying distributed security measures with dynamic adjustments (e.g., moving target defence) [69], adopting zero-trust security models with fine-grained access control [70], and establishing hierarchical security architectures with security levels across a network of networks, incorporating edge-level security processing [71].…”

Section: ) Security and Privacymentioning

confidence: 99%

Design Methodology for 6G End-to-End System: Hexa-X-II Perspective

Kerboeuf,

Porambage,

Jain

et al. 2024

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

As the fifth generation (5G) mobile communication systems are commercially deployed, they bring new services, enhance user experiences, and offer various opportunities to different industries. Despite its advancements, 5G encounters several challenges. To tackle these issues, global industrial, academic, and standards organizations are actively researching on sixth generation (6G) wireless communication systems. 6G networks are envisioned as a transformative shift in the interactions between the physical, digital, and human realms, paving the way for a pervasive human-centered cyber-physical world. 6G is positioned to be a platform that offers communication and beyond communication services considering both performance and value centric technological development approaches. In this paper, we present the way forward towards the design of 6G end-to-end (E2E) system as a consolidated view of leading industry stakeholders and academia in the European level 6G flagship project Hexa-X-II. We discuss the key challenges with 5G and how 6G is expected to tackle those by introducing new technological innovations and supporting novel use case requirements. We provide a comprehensive methodology for the design of a 6G E2E system including ten principles, a blueprint, and a structured design process. The architecture design principles prioritize environmental sustainability, digital inclusiveness, and trustworthiness, considering their impact on the 6G E2E system. The blueprint is described corresponding to the infrastructure, network centric application, and application layers, as well as the pervasive functionalities and the relevant technological innovations. Following the design principles and the system blueprint, the design process is demonstrated as two-way approaches (i.e., 1) key performance and value indicators based design process. 2) top-down versus bottomup alignment process) through the lens of a collaborative robot use case. Through this use case, a special attention is given to the technological enablers that cover management and orchestration functionalities and their 6G enhancement to go beyond the limitations characterizing the previous network generation. In addition, virtual modelling aspects related to digital twining and simulations for 6G E2E system design are also discussed. INDEX TERMS 6G, end-to-end, platform, system, blueprint, network architecture, design process, use case, key value indicators, key performance indicators, collaborative robots.

show abstract

Section: ) Security and Privacymentioning

confidence: 99%

Design Methodology for 6G End-to-End System: Hexa-X-II Perspective

Kerboeuf,

Porambage,

Jain

et al. 2024

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

show abstract

“…The double Nakagami-m distribution extends the double Rayleigh distribution, which is included as a special case [26], by acting as a cascaded fading model. Additionally, a double Gamma distribution is followed by the square of a double Nakagamim distributed random variable, hk 2 . The density of this distribution can be expressed through a standard transformation of random variables as follows:…”

Section: Mmwave Channel Modelmentioning

confidence: 99%

“…The rapid proliferation of multimedia content and mobile edge computing necessitates effective content delivery and caching strategies. Integrating caching and NOMA techniques can enhance system performance and reduce latency in vehicular networks, thereby relieving pressure on backhaul links and improving overall network efficiency [2,3]. Although cache-aided NOMA holds the promise of improving spectral efficiency and QoS from a theoretical standpoint, its practical benefits in terms of managing sporadic network connectivity and reducing latency by serving frequently requested data locally are still underexplored.…”

Section: Introductionmentioning

confidence: 99%

Beamsteering-Aware Power Allocation for Cache-Assisted NOMA mmWave Vehicular Networks

Cao

et al. 2023

Electronics

View full text Add to dashboard Cite

Cache-enabled networks with multiple access (NOMA) integration have been shown to decrease wireless network traffic congestion and content delivery latency. This work investigates optimal power control in cache-assisted NOMA millimeter-wave (mmWave) vehicular networks, where mmWave channels experience double-Nakagami fading and the mmWave beamforming is subjected to beamsteering errors. We aim to optimize vehicular quality of service while maintaining fairness among vehicles, through the maximization of successful signal decoding probability for paired vehicles. A comprehensive analysis is carried out to understand the decoding success probabilities under various caching scenarios, leading to the development of optimal power allocation strategies for diverse caching conditions. Moreover, an optimal power allocation is proposed for the single-antenna case, for exploiting the cached data as side information to cancel interference. The robustness of our proposed scheme against variations in beamforming orientation is assessed by studying the influence of beamsteering errors. Numerical results demonstrate the effectiveness of the proposed cache-assisted NOMA scheme in enhancing cache utility and NOMA efficiency, while underscoring the performance gains achievable with larger cache sizes.

show abstract

“…Network planning and optimization are required for mobile network providers. There is the need to strike a balance between network operation, QoS, and radio coverage in various situations [9] The structure of radio refractive index, N, at the lower part of the atmosphere has helped in identifying the weather parameters likely to affect signal propagation and it is stated in Equation 1given as [10]…”

Section: Introductionmentioning

confidence: 99%

Validation of Key Performance Indicators of Mobile Telecommunication Operators Using Ensemble Models and Artificial Neural Networks With Nigerian Communication Commission’s Thresholds

Awofolaju,

Lasisi,

Ajewole

et al. 2024

UJEES

View full text Add to dashboard Cite

This paper presents the comparative studies among the predictive models used for the validation of the key parameter indicators of mobile network operators with the Nigerian Communication Commission’s threshold. Four Key Performance Indicators were predicted using artificial neural networks and ensemble models which include bagging and LSBoost models. The Key Performance Indicators and weather parameters for six locations in Southwestern Nigeria were employed. MATLAB R2020a was employed to develop the three models. Microsoft Excel was used in the analysis of the dataset. The bagging model gave the best average compliance of 94% and 100% for CSSR and TCH Congestion Rate respectively while the ANN model yielded the best average compliance of 76.7% and 85.2% for DCR and SDCCH Congestion Rate respectively..

show abstract

Balancing QoS and Security in the Edge: Existing Practices, Challenges, and 6G Opportunities With Machine Learning

Cited by 29 publications

References 200 publications

Design Methodology for 6G End-to-End System: Hexa-X-II Perspective

Design Methodology for 6G End-to-End System: Hexa-X-II Perspective

Beamsteering-Aware Power Allocation for Cache-Assisted NOMA mmWave Vehicular Networks

Validation of Key Performance Indicators of Mobile Telecommunication Operators Using Ensemble Models and Artificial Neural Networks With Nigerian Communication Commission’s Thresholds

Contact Info

Product

Resources

About