Blockchain-Empowered Framework for Decentralized Network Management in 6G

Maksymyuk, Taras; Gazda, Juraj; Vološin, Marcel; Bugár, Gabriel; Horváth, Denis; Klymash, Mykhailo; Dohler, Mischa

doi:10.1109/mcom.001.2000175

Cited by 112 publications

(59 citation statements)

References 15 publications

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“…The world of mobile communications is not an exception to this list [28], [238]. Blockchain can play a cardinal role in improving (i) management and orchestration in terms of interference, resource, spectrum and mobility management [239]- [242], (ii) operations in terms of cell-free communication and 3D-networking, and (iii) business models in terms of decentralized and trustless digital markets involving various stakeholders like Infrastructure Providers (InPs), network tenants, industry verticals, Over-The-Top (OTT) providers, and edge providers [238], [243]. Further, blockchain has an immense potential to strengthen the existing service arena of mobile networks as well as set the floor for futuristic applications and use case of 6G.…”

Section: Blockchain/dltmentioning

confidence: 99%

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Alwis

Kalla

Pham

et al. 2021

IEEE Open J. Commun. Soc.

498

195

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Emerging applications such as Internet of Everything, Holographic Telepresence, collaborative robots, and space and deep-sea tourism are already highlighting the limitations of existing fifth-generation (5G) mobile networks. These limitations are in terms of data-rate, latency, reliability, availability, processing, connection density and global coverage, spanning over ground, underwater and space. The sixth-generation (6G) of mobile networks are expected to burgeon in the coming decade to address these limitations. The development of 6G vision, applications, technologies and standards has already become a popular research theme in academia and the industry. In this paper, we provide a comprehensive survey of the current developments towards 6G. We highlight the societal and technological trends that initiate the drive towards 6G. Emerging applications to realize the demands raised by 6G driving trends are discussed subsequently. We also elaborate the requirements that are necessary to realize the 6G applications. Then we present the key enabling technologies in detail. We also outline current research projects and activities including standardization efforts towards the development of 6G. Finally, we summarize lessons learned from state-of-the-art research and discuss technical challenges that would shed a new light on future research directions towards 6G.

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Section: Blockchain/dltmentioning

confidence: 99%

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Alwis

Kalla

Pham

et al. 2021

IEEE Open J. Commun. Soc.

498

195

View full text Add to dashboard Cite

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“…There are multiple applications that can be supported by blockchain technology but have different requirements in terms of speed, security, privacy, scalability, etc. [47]. Future networks should therefore support various blockchain protocols, which will need to work simultaneously while sharing the same computational capacity of MEC servers.…”

Section: Blockchain Enhancement Based On Mecmentioning

confidence: 99%

Cost-Effective Resource Allocation for Multitier Mobile Edge Computing in 5G Mobile Networks

et al. 2021

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Mobile edge computing (MEC) is currently one of the key technologies that can facilitate the evolution of the future digitized economy. MEC can provide ubiquitous computational capabilities through the multitier deployment of servers to ensure lower latencies and tighter integration with 5G, the Internet of Things, blockchains and artificial intelligence. In this paper, we propose a new approach to optimizing hardware resource allocation for edge nodes in a multitier MEC hierarchy. In addition to a centralized unit, we consider active antenna units and distributed units equipped with edge nodes of different computational capacities. A parametric Bayesian optimizer is implemented for hardware resource allocation to increase the overall computational capacity of a 5G-based MEC system. Simulation results show that for given budget constraints, the proposed solution outperforms pseudorandom resource allocation in terms of the proportion of computational tasks completed. The achievable gains are in the range of 20-40 %, depending on the task complexity and selected budget threshold.

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“…where AðtÞ is the scheduling algorithm. In formula ( 5), the information about the prehistory of the allocated shares of the wireless channel and the volumes of transmitted data for UE/M2M gateway i is aggregated in the sense of S i ðτÞ, as these parameters are given by relation (4).…”

Section: Radio Resource Allocationmentioning

confidence: 99%

“…Global trends in the telecommunication market show that wireless communication networks are becoming one of the key elements in the implementation of the Internet of Things (IoT) paradigm [2]. Due to the rapid growth of mobile data traffic, the popularity of IoT, and M2M, mobile operators are constantly focused on improving the quality of service (QoS) provision, developing 4G networks into the future software-defined heterogeneous 5G/6G networks based on Long-Term Evolution (LTE) technology [3][4][5][6]. LTE is now seen as the best technology to support MTC due to its Internet compatibility, high capacity, flexibility in radio resource management, and scalability.…”

Section: Introductionmentioning

confidence: 99%

QoS‐Aware Optimal Radio Resource Allocation Method for Machine‐Type Communications in 5G LTE and beyond Cellular Networks

Beshley

Medvetskyi

et al. 2021

Wireless Communications and Mobile Computing

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In this paper, we consider the saturation problem in the 3GPP LTE cellular system caused by the expected huge number of machine-type communication (MTC) devices, leading to a significant impact on both machine-to-machine (M2M) and human-to-machine H2H traffic. M2M communications are expected to dominate traffic in LTE and beyond cellular networks. In order to address this problem, we proposed an advanced architecture designed for 5G LTE networks to enable the coexistence of H2H/M2M traffic, supported by different priority strategies to meet QoS for each traffic. The queuing strategy is implemented with an M2M gateway that manages four queues allocated to different types of MTC traffic. The optimal radio resource allocation method in LTE and beyond cellular networks was developed. This method is based on adaptive selection of channel bandwidth depending on the QoS requirements and priority traffic aggregation in the M2M gateway. Additionally, a new simulation model is proposed which can help in studying and analyzing the mutual impact between M2M and H2H traffic coexistence in 5G networks while considering high and low priority traffics for both M2M and H2H devices. This simulator automates the proposed method of optimal radio resource allocation between the M2M and H2H traffic to ensure the required QoS. Our simulation results proved that the proposed method improved the efficiency of radio resource utilization to 13% by optimizing the LTE frame formation process.

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Blockchain-Empowered Framework for Decentralized Network Management in 6G

Cited by 112 publications

References 15 publications

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Cost-Effective Resource Allocation for Multitier Mobile Edge Computing in 5G Mobile Networks

QoS‐Aware Optimal Radio Resource Allocation Method for Machine‐Type Communications in 5G LTE and beyond Cellular Networks

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