Blockchain Papers

Vamshi Sunku Mohan, Sriram Sankaran, Priyadarsi Nanda, Krishnashree Achuthan

No abstract is available for this record.

Robina Rabnawaz, Mohamed Abid, Naeem Aslam, Fatima Khurram Bukhari

The data traffic has increased significantly along with the quick development of smart wireless technologies, and current 5G networks are still not completely prepared to handle future huge data traffic in the areas of services, data transfer, data storage, and processing. 6G is expected to offer very high-level extended 5G capabilities, such as a Tbps data transfer rate and a sub-millisecond response time. The main objective of this study is to be aware of new technologies being enhanced day by day and provide existing research content, issues, and directions for the future regarding 6G wireless networks. Therefore, a systematic literature review of research articles is provided by categorizing the selected studies published between 2019 and 2022 in terms of enabling technologies. First, the researcher discussed the need for 6G by predicting the explosive growth of mobile traffic from 2022 to 2030. Second, 6G requirements, trends, and services are addressed and contrasted with 5G in terms of a group of key performance indicators. Third, conduct a comparative analysis of 6G challenges and gaps, such as security and privacy, the need for a decentralized network, Omnipresent service coverage, and storage efficiency. So, it is essential to develop an accurate, faster, and well-organized system for the 6G wireless network. We have presented an efficient and secure mode R6GS, which combines blockchain and 6G to improve security from the lower to upper layers while also improving storage efficiency. Cybertwin technologies are used at the edge layer of the 6G network in the proposed model R6GS to improve security. The smart contracts, IPFS and Ethereum blockchain are used in the proposed R6GS model to enhance the 6G network's data integrity and data storage. It also processes and stores massive amounts of data at various network layers, which removes the large storage capacity issue of traditional P2P and Client/Server (C/S) networks due to centralized servers in 6G technology. For the performance evaluation, the model is evaluated through expert opinion. Moreover, the proposed R6GS model also improves time efficiency through the edge layer, because if a task is available at the edge layer, there is no need to send a request to the core layer. The server at the edge layer efficiently delivers data to end nodes. Furthermore, a taxonomy is presented in this study. To the best of our knowledge, the proposed methodology worked efficiently.

Ning Yang, Daoxing Guo, Yutao Jiao, Guoru Ding · 5 authors

Unmanned aerial vehicles (UAVs) will be widely deployed due to their flexibility, mobility, and miniaturization, providing the necessary support for spectrum sharing between different communication systems in the space–air–ground-integrated IoT network (SAGIN). However, there are potential security threats to spectrum sharing among different communication systems due to the openness of a wireless network, the unreliability of node behavior, and the trust barriers of the networks. In this article, a secure spectrum sharing scheme based on lightweight UAV-blockchain (LUBC) is proposed to address the above security issues. First, a spectrum sharing model based on the overlay mode is developed to improve the spectrum efficiency of SAGIN, where UAVs relay signals from the satellite to the ground users in exchange for spectrum access opportunities and serve their own users simultaneously in the nonorthogonal multiple access (NOMA) mode. Second, a secure spectrum sharing framework based on LUBC is proposed to solve the security and privacy issues of spectrum trading in SAGIN. Then, aiming at maximizing the primary user’s throughput under the premise of meeting the minimum power allocation factor of UAV network, the spectrum auction based on NOMA is formulated as a multirelay selection optimization problem, which is solved by the blockchain-based sequential Vickrey auction mechanism. Finally, the security evaluation and numerical results are conducted to verify the security and effectiveness of the proposed spectrum sharing scheme for SAGIN.

Faisal Tariq, Muhammad R. A. Khandaker, Imran Shafique Ansari

This chapter provides an expert view on the most trending research directions that will likely shape the technological changes needed for the sixth generation (6G) mobile communication systems for the next decade. The notion of collective artificial intelligence (AI), in contrast to the hype of using conventional AI or machine learning methods in wireless systems, is a revolutionary element in 6G. Blockchain technology will likely play a major role in securing and authenticating future communication systems, thanks to the inherent advantages of the distributed ledger technology. While the technologies are expected to provide the technological leaps required for the speculative 6G vision, there are many challenges researchers and engineers will need to address in order to harvest full benefits of 6G. The chapter also presents an overview of the key concepts discussed in this book.

Changlin Yang, Alexei Ashikhmin, Xiaodong Wang, Zibin Zheng

A key constraint that limits the implementation of blockchain in Internet of Things (IoT) is its large storage requirement resulting from the fact that each blockchain node has to store the entire blockchain. This increases the burden on blockchain nodes, and increases the communication overhead for new nodes joining the network since they have to copy the entire blockchain. In order to reduce storage requirements without compromising on system security and integrity, coded blockchains, based on error correcting codes with fixed rates and lengths, have been recently proposed. This approach, however, does not fit well with dynamic IoT networks in which nodes actively leave and join. In such dynamic blockchains, the existing coded blockchain approaches lead to high communication overheads for new joining nodes and may have high decoding failure probability. This paper proposes a rateless coded blockchain with coding parameters adjusted to network conditions. Our goals are to minimize both the storage requirement at each blockchain node and the communication overhead for each new joining node, subject to a target decoding failure probability. We evaluate the proposed scheme in the context of real-world Bitcoin blockchain and show that both storage and communication overhead are reduced by 99.6\% with a maximum $10^{-12}$ decoding failure probability.

Langtian Qin, Hancheng Lu, Yuang Chen, Zhuojia Gu · 6 authors

In the traditional mobile edge computing (MEC) system, the availability of MEC services is greatly limited for the edge users of the cell due to serious signal attenuation and inter-cell interference. User-centric MEC (UC-MEC) can be seen as a promising solution to address this issue. In UC-MEC, each user is served by a dedicated access point (AP) cluster enabled with MEC capability instead of a single MEC server, however, at the expense of more energy consumption and greater privacy risks. To achieve efficient and reliable resource utilization with user-centric services, we propose an energy-efficient blockchain-enabled UC-MEC system where blockchain operations and resource optimization are jointly performed. Firstly, we design a resource-aware, reliable, replicated, redundant, and fault-tolerant (R-RAFT) consensus mechanism to implement secure and reliable resource trading. Then, an optimization framework based on alternating direction method of multipliers (ADMM) is proposed to minimize the total energy consumed by wireless transmission, consensus, and task computing, where AP clustering, computing resource allocation, and bandwidth allocation are jointly considered. Simulation results show the superiority of the proposed UC-MEC system over reference schemes, with at most 33.96% reduction in the total delay and 48.77% reduction in the total energy consumption.

Nazanin Moosavi, Hamed Taherdoost

No abstract is available for this record.

Adnan Shahid Khan, Mohd Izzat Bin Yahya, Kartinah Zen, Johari Abdullah · 8 authors

Cell-Free mMIMO is a part of technology that will be integrated with future 6G ultra-dense cellular networks to ensure unlimited wireless connectivity and ubiquitous latency-sensitive services. Cell-Free gained researchers’ interest as it offers ubiquitous communication with large bandwidth, high throughput, high data transmission, and greater signal gain. Cell-Free eliminates the idea of cell boundary in cellular communication that reduces frequent handover and inter-cell interference issues. However, the effectiveness of the current authentication protocol could become a serious issue due to the dynamic nature of Cell-Free in densely distributed, high number of users, high mobility, and frequent data exchange. Secondly, secure communication may be achieved in such a dynamic environment at the expense of high authentication overhead, high communication and computational costs. To address the above security challenges, we proposed a lightweight multifactor mutual authentication protocol for Cell-Free communication using ECC-based Deffie Hellman (ECDH). This scheme utilizes timestamping, one-way hash function, Blind-Fold Challenge scheme with public key infrastructure. The proposed cryptosystem integrates with blockchain technology using proof of staked (POS) as a consensus mechanism to ensure integrity, non-repudiation and traceability. The proposed scheme can enforce the mitigation of several major security attacks on communication links such as spoofing attacks, eavesdropping, user location privacy issues, replay attacks, denial of service attacks, and man-in-the-middle (MITM) attacks, which is one of the significant features of the scheme. Furthermore, this scheme contributes to reducing authentication, communication, and computational overheads with an average of 32.8%, 52.4% and 53.2% better performance respectively as compared baseline authentication protocols.

Zaher Haddad

No abstract is available for this record.

Yiping Zuo, Jiajia Guo, Ning Gao, Yongxu Zhu · 6 authors

The research on the sixth-generation (6G) wireless communications for the development of future mobile communication networks has been officially launched around the world. 6G networks face multifarious challenges, such as resource-constrained mobile devices, difficult wireless resource management, high complexity of heterogeneous network architectures, explosive computing and storage requirements, privacy and security threats. To address these challenges, deploying blockchain and artificial intelligence (AI) in 6G networks may realize new breakthroughs in advancing network performances in terms of security, privacy, efficiency, cost, and more. In this paper, we provide a detailed survey of existing works on the application of blockchain and AI to 6G wireless communications. More specifically, we start with a brief overview of blockchain and AI. Then, we mainly review the recent advances in the fusion of blockchain and AI, and highlight the inevitable trend of deploying both blockchain and AI in wireless communications. Furthermore, we extensively explore integrating blockchain and AI for wireless communication systems, involving secure services and Internet of Things (IoT) smart applications. Particularly, some of the most talked-about key services based on blockchain and AI are introduced, such as spectrum management, computation allocation, content caching, and security and privacy. Moreover, we also focus on some important IoT smart applications supported by blockchain and AI, covering smart healthcare, smart transportation, smart grid, and unmanned aerial vehicles (UAVs). Moreover, we thoroughly discuss operating frequencies, visions, and requirements from the 6G perspective. We also analyze the open issues and research challenges for the joint deployment of blockchain and AI in 6G wireless communications. Lastly, based on lots of existing meaningful works, this paper aims to provide a comprehensive survey of blockchain and AI in 6G networks. We hope this survey can shed new light on the research of this newly emerging area and serve as a roadmap for future studies.

Zhaowei Ma, Xiaoming Yuan, Kai Liang, Jie Feng · 7 authors

No abstract is available for this record.

Qianqian Pan, Jun Wu, Ali Kashif Bashir, Jianhua Li · 6 authors

With the capability of establishing line-of-sight (LoS) links for devices, drones are generally utilized as aerial base stations to construct coexisting drone-terrestrial networks (CDTNs) for wireless communication. However, the established LoS links are easily blocked, thereby severely decreasing transmission performance. The intelligent reflecting surface (IRS) is a promising technology to improve data transmission in the CDTN by programming propagation channels. However, secure IRS reflection resource allocation is still an open issue. Existing IRS resource allocation methods are mainly based on a centralized third party and are vulnerable to the single point of failure. Furthermore, intelligent allocation of IRS reflection resources is also a key issue. To solve these problems, we propose a blockchain and artificial intelligence (AI) enabled configurable reflection resource allocation approach for the IRS-aided CDTN. First, we establish the IRS-aided communication framework for the CDTN, where a drone-mounted IRS is introduced to improve spatial freedom for data transmission. Second, the blockchain-based reflection resource management mechanism is proposed. In this mechanism, we design allocation transactions, the hierarchical blockchain structure, and smart-contract-enabled resource trading. Third, the AI-based reflection resource allocation mechanism is proposed, including the intelligent reflection elements assignment and deep-reinforcement-learning-driven reflection coefficient configuration. Furthermore, experimental results verify the effectiveness of our proposed approach. Finally, open issues and key challenges of the proposed approach are discussed.

Houshyar Honar Pajooh, Serge Demidenko, Saad Aslam, Muhammad Harris

Ubiquitous computing turns into a reality with the emergence of the Internet of Things (IoT) adopted to connect massive numbers of smart and autonomous devices for various applications. 6G-enabled IoT technology provides a platform for information collection and processing at high speed and with low latency. However, there are still issues that need to be addressed in an extended connectivity environment, particularly the security and privacy domain challenges. In addition, the traditional centralized architecture is often unable to address problems associated with access control management, interoperability of different devices, the possible existence of a single point of failure, and extensive computational overhead. Considering the evolution of decentralized access control mechanisms, it is necessary to provide robust security and privacy in various IoT-enabled industrial applications. The emergence of blockchain technology has changed the way information is shared. Blockchain can establish trust in a secure and distributed platform while eliminating the need for third-party authorities. We believe the coalition of 6G-enabled IoT and blockchain can potentially address many problems. This paper is dedicated to discussing the advantages, challenges, and future research directions of integrating 6G-enabled IoT and blockchain technology for various applications such as smart homes, smart cities, healthcare, supply chain, vehicle automation, etc.

Zhenqiang Sun, Fei Qi, Lei Liu, Yanxia Xing · 5 authors

Ubiquitous Internet of Things (UIoT) is required a 3-D network that stretches from space to air to earth. It involves numerous network components, such as satellites, HAPs, UAVs, terrestrial cellular networks, data centers, terrestrial gateways, as well as sharing and openness among operators. Correspondingly, wireless spectrum sharing becomes essential to energy efficiency and, thus, has to be investigated for green UIoT. Meanwhile, both blockchain and sixth-generation mobile communication technology hybrid cloud are recently intriguing technologies, and the enormous potential of combining the two has grown in prominence. For the reason of dependability and security, these two technologies are proposed to apply to spectrum sharing among UIoT devices. Particularly the blockchain’s unique smart contract technology can well complete the spectrum sharing procedure, as verified by the numerical results from our simulation study.

Xiaoou Liu, Xiaoyi Chen, Qi Bi, Wei Liang · 6 authors

No abstract is available for this record.

Runze Cheng, Yao Sun, Lina Mohjazi, Ying‐Chang Liang · 5 authors

In a space-air-ground integrated network (SAGIN), managing resources for the growing number of highly-dynamic and heterogeneous radios is a challenging task. Symbiotic communication (SC) is a novel paradigm, which leverages the analogy of the natural ecosystem in biology to create a radio ecosystem in wireless networks that achieves cooperative service exchange and resource sharing, i.e., service/resource trading, among numerous radios. As a result, the potential of symbiotic communication can be exploited to enhance resource management in SAGIN. Despite the fact that different radio resource bottlenecks can complement each other via symbiotic relationships, unreliable information sharing among heterogeneous radios and multi-dimensional resources managing under diverse service requests impose critical challenges on trusted trading and intelligent decision-making. In this article, we propose a secure and smart symbiotic SAGIN (S^4) framework by using blockchain for ensuring trusted trading among heterogeneous radios and machine learning (ML) for guiding complex service/resource trading. A case study demonstrates that our proposed S^4 framework provides better service with rational resource management when compared with existing schemes. Finally, we discuss several potential research directions for future symbiotic SAGIN.

Chamitha de Alwis, Pardeep Kumar, Quoc‐Viet Pham, Kapal Dev · 7 authors

Sixth-generation mobile networks (6G) are expected to reach extreme communication capabilities to realize emerging applications demanded by the future society. This paper focuses on six technological directions towards 6G, namely, intent-based networking, THz communication, artificial intelligence, distributed ledger technology/blockchain, smart devices and gadget-free communication, and quantum communication. These technologies will enable 6G to be more capable of catering to the demands of future network services and applications. Each of these technologies is discussed highlighting recent developments, applicability in 6G, and deployment challenges. It is envisaged that this work will facilitate 6G related research and developments, especially along the six technological directions discussed in the paper.

Anshuman Kalla, Chamitha de Alwis, Pawani Porambage, Gürkan Gür · 5 authors

No abstract is available for this record.

Fengxiao Tang, Cong Wen, Linfeng Luo, Ming Zhao · 5 authors

In the future era of intelligent networks, communication technology and network architecture need to be further developed to provide users with high-quality services. The Space-Air-Ground Integrated Networks (SAGIN) is seen as a potential architecture to provide ubiquitous communication and drive the era of the intelligent global network. The space and air segments in SAGIN can assist in offloading traffic from the ground segment. However, in a highly dynamic and heterogeneous network like SAGIN, offloading decisions are easily affected by the incorporated/malicious nodes. How to ensure security and improve network performance becomes a critical problem. In this paper, we address the above problem by jointly using blockchain and federated reinforcement learning (FRL). Firstly, we propose a blockchain-based secure federated learning framework that combines topology information chain and model chain to assist traffic offloading. Then, we propose a node security evaluation and an enhanced practical byzantine fault tolerance (EPBFT) algorithm to secure the traffic offloading process. Furthermore, we describe the traffic offloading problem as a Markov decision problem (MDP) and employ the Blockchain-based Federated Asynchronous Advantage Actor-Critic (BFA3C) algorithm to solve this problem. Finally, the simulation results show that the BFA3C-based algorithm used in SAGIN with/without malicious nodes achieves superior performance in terms of latency and security.

Yitong Wang, Jun Zhao

With the advances of the Internet of Things (IoT) and 5G/6G wireless communications, the paradigms of mobile computing have developed dramatically in recent years, from centralized mobile cloud computing to distributed fog computing and mobile edge computing (MEC). MEC pushes compute-intensive assignments to the edge of the network and brings resources as close to the endpoints as possible, addressing the shortcomings of mobile devices with regard to storage space, resource optimisation, computational performance and efficiency. Compared to cloud computing, as the distributed and closer infrastructure, the convergence of MEC with other emerging technologies, including the Metaverse, 6G wireless communications, artificial intelligence (AI), and blockchain, also solves the problems of network resource allocation, more network load as well as latency requirements. Accordingly, this paper investigates the computational paradigms used to meet the stringent requirements of modern applications. The application scenarios of MEC in mobile augmented reality (MAR) are provided. Furthermore, this survey presents the motivation of MEC-based Metaverse and introduces the applications of MEC to the Metaverse. Particular emphasis is given on a set of technical fusions mentioned above, e.g., 6G with MEC paradigm, MEC strengthened by blockchain, etc.

Saikat Samanta, Achyuth Sarkar, Yaka Bulo

No abstract is available for this record.

Arash Heidari, Mohammad Ali Jabraeil Jamali, Nima Jafari Navimipour, Shahin Akbarpour

The number of Internet of Things (IoT)-related innovations has recently increased exponentially, with numerous IoT objects being invented one after the other. Where and how many resources can be transferred to carry out tasks or applications is known as computation offloading. Transferring resource-intensive computational tasks to a different external device in the network, such as a cloud, fog, or edge platform, is the strategy used in the IoT environment. Besides, offloading is one of the key technological enablers of the IoT, as it helps overcome the resource limitations of individual objects. One of the major shortcomings of previous research is the lack of an integrated offloading framework that can operate in an offline/online environment while preserving security. This paper offers a new deep Q-learning approach to address the IoT-edge offloading enabled blockchain problem using the Markov Decision Process (MDP). There is a substantial gap in the secure online/offline offloading systems in terms of security, and no work has been published in this arena thus far. This system can be used online and offline while maintaining privacy and security. The proposed method employs the Post Decision State (PDS) mechanism in online mode. Additionally, we integrate edge/cloud platforms into IoT blockchain-enabled networks to encourage the computational potential of IoT devices. This system can enable safe and secure cloud/edge/IoT offloading by employing blockchain. In this system, the master controller, offloading decision, block size, and processing nodes may be dynamically chosen and changed to reduce device energy consumption and cost. TensorFlow and Cooja’s simulation results demonstrated that the method could dramatically boost system efficiency relative to existing schemes. The findings showed that the method beats four benchmarks in terms of cost by 6.6%, computational overhead by 7.1%, energy use by 7.9%, task failure rate by 6.2%, and latency by 5.5% on average.

Saurabh Singh, C. Rajesh Babu, Kadiyala Ramana, In-Ho Ra · 5 authors

Fifth-generation (5G) technology is anticipated to allow a slew of novel applications across a variety of industries. The wireless communication of the 5G and Beyond-5G (B5G) networks will accommodate a wide variety of services and user expectations, including intense end-user connectivity, sub-1 ms delay, and a transmission rate of 100 Gbps. Network slicing is envisioned as an appropriate technique that can meet these disparate requirements. The intrinsic qualities of a blockchain, which has lately acquired prominence, mean that it is critical for the 5G network and B5G networks. In particular, the incorporation of blockchain technology into B5G enables the network to effectively monitor and control resource utilization and sharing. Using blockchain technology, a network-slicing architecture referred to as the Blockchain Consensus Framework is introduced that allows resource providers to dynamically contract resources, especially the radio access network (RAN) schedule, to guarantee that their end-to-end services are effortlessly executed. The core of our methodology is comprehensive service procurement, which offers the fine-grained adaptive allocation of resources through a blockchain-based consensus mechanism. Our objective is to have Primary User-Secondary User (PU-SU) interactions with a variety of services, while minimizing the operation and maintenance costs of the 5G service providers. A Blockchain-Enabled Network Slicing Model (BENS), which is a learning-based algorithm, is incorporated to handle the spectrum resource allocation in a sophisticate manner. The performance and inferences of the proposed work are analyzed in detail.

Meng Li, F. Richard Yu, Pengbo Si, Yanhua Zhang · 5 authors

Artificial intelligence (AI)-enabled Internet of Things (IoT) has attracted great interests. The accuracy of data training model in AI is vital for further development of IoT. In addition, with the increasing number of intelligent IoT devices, the amounts of data available for transmission, learning and training can lead to serious communication burdens and data reliability issues. In order to address these issues, we study novel network architectures in future 6G networks to support the intelligent IoT. Moreover, inspired by the collective learning of humans, we introduce and adopt a novel method named as collective reinforcement learning (CRL) in the intelligent IoT to realize the sharing of learning and training results. To ensure security and privacy, as well as improve computing efficiency, blockchain, mobile edge computing (MEC) and cloud computing are applied to protect data security and enrich computing resources. On this basis, we formulate an optimization problem in the intelligent IoT based on the proposed framework to optimize transmission latency and energy consumption. Simulation results demonstrate that the system performance has improved significantly. At last, some research challenges and open issues are pointed out to the intelligent IoT in future networks.