Abstract Blockchain technology is getting more and more attention due to its decentralization, independence and security features. However, in wireless networks it faces a computational challenge: the proof-of-work problem. Mobile edge computing (MEC) leads to a vaild scheme by providing cloud computing capabilities to mobile devices. Non-orthogonal multiple access (NOMA) exploits the diversity properties in the power domain to further increase system throughput and spectral efficiency. In this paper, we suggest a new NOMA-based MEC wireless blockchain network to minimize system energy consumption through task offloading decision optimization, user clustering, computing resource and transmit power allocation. In order to effectively figure out this non-convex problem, we first propose a offloading decision and user clustering algorithm, and then propose a computing resource allocation algorithm based on user Quality of Service (QoS) requirements. Finally, the transmission power can be easily determined. The numerical simulation results verify that the proposed joint optimization algorithm can effectively decrease the system energy consumption.
Kithmini Godewatte Arachchige, Philip Branch, Jason But
With the development of Internet of Things (IoT) technologies, industries such as healthcare have started using low-powered sensor-based devices. Because IoT devices are typically low-powered, they are susceptible to cyber intrusions. As an emerging information security solution, blockchain technology has considerable potential for protecting low-powered IoT end devices. Blockchain technology provides promising security features such as cryptography, hash functions, time stamps, and a distributed ledger function. Therefore, blockchain technology can be a robust security technology for securing IoT low-powered devices. However, the integration of blockchain and IoT technologies raises a number of research questions. Scalability is one of the most significant. Blockchain’ scalability of low-powered sensor networks needs to be evaluated to identify the practical application of both technologies in low-powered sensor networks. In this paper, we analyse the scalability limitations of three commonly used blockchain algorithms running on low-powered single-board computers communicating in a wireless sensor network. We assess the scalability limitations of three blockchain networks as we increase the number of nodes. Our analysis shows considerable scalability variations between three blockchain networks. The results indicate that some blockchain networks can have over 800 ms network latency and some blockchain networks may use a bandwidth over 1600 Kbps. This work will contribute to developing efficient blockchain-based IoT sensor networks.
Vikram Puri, Aman Kataria, Sita Rani, Piyush Kumar Pareek
The healthcare system has become more reliant on the data collection capabilities of fast evolving IoT devices. Patient healthcare records (PHR) now contain additional information as a result. However, securing identities and guaranteeing data security have emerged as critical challenges in the healthcare system. When it comes to regulating PHR, many of the centralized and decentralized methods now in use struggle difficulties such as single point of failure, high transaction fees, slow throughput, and excessive latency. To address these concerns, a distributed ledger technology (DLT)-based framework named IOTA rather than a blockchain-based platform such as Ethereum or Polygon is proposed. The proposed framework considered the example of a hospital with several patients on the same and various floors. Furthermore, the suggested approach employs a real-time experimental setup for calculating the time and power consumption of the devices.
Mohammed K. Shakeel, P. Muthu Krishnammal, Vipul Vekariya, Shaik Vaseem Akram · 6 authors
With more and more connected devices joining IoT networks, protecting their communications is becoming more difficult. The distributed ledger technology known as blockchain has the potential to solve the security issues plaguing 5G-enabled IoT networks. This article provides a layered blockchain security strategy to protect Internet of Things networks and make their deployment simpler. Using clustering, the complex multi-layer structure is simplified. The K-unknown clusters in the IoT network are generated by use of a hybrid Evolutionary Computation Methodology involving Simulated Annealing and Genetic Algorithms. The chosen cluster chiefs have authority over local authentication and permissions. By creating a private blockchain network on a local level, cluster administrators and critical nodes can streamline their interactions. This type of blockchain also facilitates authentication on a network, but it also adds an extra layer of security and integrity. The proposed framework makes use of Hyperledger Fabric, an open-source implementation of Distributed ledger technology. The encryption of data transmitted between nodes is ensured by the use of a global distributed ledger technology, which is instated in the base stations. As opposed to previously disclosed methods, simulation results show that the proposed clustering algorithm is effective. Finally, it is shown that the envisaged portable cryptocurrency architecture achieves a better latency/capacity tradeoff than a conventional global blockchain.
The hybrid wireless sensor network is made up of Wireless Body Area Network (WBAN). Generally, many hospitals use cellular networks to support telemedicine. To provide the treatment to the patient on time, for this, an early diagnosis is required, for treatment. With the help of WBANs, collections and transmissions of essential biomedical data to monitor human health becomes easy. Compressor Sensing (CS) is an emerging signal compression/acquisition methodology that offers a protruding alternative to traditional signal acquisition. The proposed mechanism reduces message exchange overhead and enhances trust value estimation via response time and computational resources. It reduces cost and makes the system affordable to the patient. According to the results, the proposed scheme in terms of Compression Ratio (CR) is 18.18% to 88.11% better as compared to existing schemes. Also in terms of Percentage Root-Mean-Squared Difference (PRD) value, the proposed scheme is 18.18% to 34.21% better than with respect to existing schemes. The consensus for any new block is achieved in 24% less time than the Proof-of-Work (PoW) approach. The shallow CPU usage is required for the leader election mechanism. CPU utilization while the experiment lies in the range of 0.9% and 14%. While simulating a one-hour duration, the peak CPU utilization is 21%.
The demand for the Internet of Everything has slowed down network routing efficiency. Traditional routing policies rely on manual configuration, which has limitations and adversely affects network performance. In this paper, we propose an Internet of Things (IoT) Intelligent Edge Network Routing (ENIR) architecture. ENIR uses deep reinforcement learning (DRL) to simulate human learning of empirical knowledge and an intelligent routing closed-loop control mechanism for real-time interaction with the network environment. According to the network demand and environmental conditions, the method can dynamically adjust network resources and perform intelligent routing optimization. It uses blockchain technology to share network knowledge and global optimization of network routing. The intelligent routing method uses the deep deterministic policy gradient (DDPG) algorithm. Our simulation results show that ENIR provides significantly better link utilization and transmission delay performance than various routing methods (e.g., open shortest path first, routing based on Q-learning and DRL-based control framework for traffic engineering).
The Bitcoin system uses a fully replicated data storage mechanism in which each node keeps a full copy of the blockchain. As the number of nodes in the system increases and transactions get more complex, more and more storage space are needed to store block data. The scalability of storage has become a bottleneck, limiting the practical application of blockchain. This paper proposes a node storage scheme, called RESS, to integrate erasure coding technology into the blockchain to encode multiple blocks. Under the proposed block grouping method, nodes can reduce the times of coded block decoding. In addition, the coding scheme based on Raptor codes proposed in this paper has linear coding and decoding complexity. The rateless feature of Raptor code helps to achieve high decentralization and scalability of the Bitcoin network. RESS ensures data availability, efficiency and blockchain robustness based on achieving storage space scalability. Experimental results show that the proposed scheme reduces the storage requirements of nodes by nearly an order of magnitude.
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.
In this paper, we explore Blockchain technology can be used to build a reliable decentralised authentication system. High security for the bioacoustics signal authentication mechanism is guaranteed by using an optimised number of secured features from the bioacoustics signal rather than conventional biometric features for authentication, and by utilising a blockchain model to improve the robustness of multiple checks on the data. It allows for trustworthy authentication and the tracking of terminal activity. Then, light weighted cryptography (LWC) is developed to offer protection at each edge node and terminal. Finally, the belief propagation (BP) algorithm for retraining the features of the bioacoustics signal serves as the foundation for the catching method. It improves hit ratio while decreasing delay time. The experimental setup uses the bioacoustics signals for authentication instead of conventional biometric features, and the use of a blockchain model for data transparency improves the efficiency of multiple checks. When this happens, privacy and safety are both boosted.
One of the core technologies facilitating interaction today is the internet, and so the question of how much this technology must evolve is inevitable. Cue in the Web3 debate.
The major challenge is the scalability issue, which the second layer of blockchain must solve. But the transfer of micro-payment creates another problem: node idleness due to the insufficient channel balance. So that we aim to implement an atomic payment splitting network using the ethereum blockchain, which can transfer the micro-payments quickly in different paths from sender to receiver. It is the first Ethereum-based atomic payment splitting model. This model works faster than other Bitcoin-based models, and smart contracts make it easier with the help of random seeds. Again the payment splitting decreases the node idleness. The significant challenges in Bitcoin lightning-based networks are intermediary insecurity and flood, and loot attack is not happening in our system that of the random seed and smart contracts. Our resultant model guarantees that the honest intermediaries have not lost funds, and the payment split network is not a failure after the path confirmation. Using negative acknowledgment also ensures the payment’s failure in the model’s initial phase. The final payment confirmation happens only by receiving all the unique seeds within the ∆ time. The proposed model has been analyzed with different existing models, and the success ratio is better.
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.
Remote laboratories have been developed at many universities worldwide to provide students with access to apparatus and experiments via the Internet around the clock, thus giving partner institutions the opportunity to share resources, expensive equipment and specialized laboratories, whether within a single country or at regional and international levels. Universities usually implement learning management systems (LMS) such as Moodle and Blackboard to enable students to interact, carry out learning activities and access remote labs. However, remote labs generate enormous amounts of data, which is stored, processed, analyzed, and accessed using centralized systems that lack transparency, traceability, security features, trustworthiness, and reliability. In addition, they are vulnerable to the single point of failure problem due to centralization. The application of blockchain technology in remote labs is proposed as a promising solution for future online learning as it combines a new pedagogical approach with various state-of-the-art technologies in an era that embraces Education 4.0 as the education norm. Furthermore, a novel blockchain-based framework for remote labs allows data streaming and transfer in a decentralized, transparent, traceable, reliable, secure, and trustful manner, where only authorized peers can join or access the network, thereby providing privacy of students’ data files and reports. An initial pilot of an Ethereum-based remote lab show promising result for effective management of online experiments, originally hosted in a Moodle LMS.
The blockchain is a distributed storage system of digital assets. This decentralized, non-copyable technology stems from universal standard password algorithm and the consensus mechanism of the game theory. The development of quantum computing poses threat to traditional algorithms of blockchain encryption, including symmetric encryption and hash encryption. Focusing on the traditional blockchain consensus mechanism, this paper designs a new blockchain consensus mechanism, based on the stochasticity, irreversibility, and uncertainty of quantum measurement. In the proposed consensus mechanism, complex calculations and intractability mathematical problems are abandoned. In this way, a huge amount of computing resources is saved, less energy is consumed, the time delay is shortened, and the throughput is increased. The proposed quantum consensus mechanism can withstand 51% attacks.
), security and energy efficiency achievements are the major issues in the WBAN-IoT environment. Existing schemes for these three issues fail to achieve them since nodes are resource constrained and hence delay and the energy consumption is minimized. In this paper, a blockchain-assisted delay and energy aware healthcare monitoring (B-DEAH) system is presented in the WBAN-IoT environment. Both body sensors and environment sensors are deployed with dual sinks for emergency and periodical packet transmission. Various processes are involved in this paper, and each process is described as follows: Key registration for patients using an extended version of the PRESENT algorithm is proposed. Cluster formation and cluster head selection are implemented using spotted hyena optimizer. Then, cluster-based routing is established using the MOORA algorithm. For data transmission, the patient block agent (PBA) is deployed and authenticated using the four Q curve asymmetric algorithm. In PBA, three entities are used: classifier and queue manager, channel selector and security manager. Each entity is run by a special function, as packets are classified using two stream deep reinforcement learning (TS-DRL) into three classes: emergency, non-emergency and faulty data. Individual packets are put into a separate queue, which is called emergency, periodical and faulty. Each queue is handled using Reyni entropy. Periodical packets are forwarded by a separate channel without any interference using a multi objective based channel selection algorithm. Then, all packets are encrypted and forwarded to the sink nodes. Simulation is conducted using the OMNeT++ network simulator, in which diverse parameters are evaluated and compared with several existing works in terms of network throughput for periodic (41.75 Kbps) and emergency packets (42.5 Kbps); end-to-end delay for periodic (0.036 s) and emergency packets (0.028 s); packet loss rate (1.1%); residual energy in terms of simulation rounds based on periodic (0.039 J) and emergency packets (0.044 J) and in terms of simulation time based on periodic (8.35 J) and emergency packets (8.53 J); success rate for periodic (87.83%) and emergency packets (87.5%); authentication time (3.25 s); and reliability (87.83%).
Security is one of the primary issues in any wireless network deployment, because, wireless nodes are susceptible to a wide-variety of internal & external attacks. These include improper authentication & access control, distributed denial of service (DDoS), sybil, spoofing, spying, masquerading, etc. Securing networks against these attacks requires an immutable, transparent, traceable, and distributed computing security model, that has minimum overheads. Most of these characteristics are fulfilled via use of blockchains, which assist in low-complexity deployment of security & hashing models. But the delay needed to scale these blockchains increases exponentially w.r.t. chain length, due to which researchers split the main blockchain into multiple sidechains. A wide variety of models are proposed by researchers for sidechain formation, and most of them are consensus dependent, which limits the scalability. Moreover, energy needed to mine blocks for these sidechains depends directly on the consensus model, encryption model, hash rules, and length of the blockchain. Thus, models proposed for sidechain formation are context-specific, and have limited scalability performance when used for multiple blockchain types. To overcome these limitations, and maintain high security performance, this text proposes design of a Low-power hybrid Consensus Method for QoS-aware Sidechain-based IoT Networks via Augmented Bioinspired computing Models. This method uses a combination of Proof-of-Work (PoW), Proof-of-Stake (PoS) & Proof-of-Authority (PoA) based consensus models, which assists in reducing its mining delay. The PoW model allows selection of nodes with higher performance, PoS allows selection of nodes with higher stake, and PoA ensures better control of IoT devices. Selection of these consensus models is done via use of an Improved Genetic Algorithm (IGA) model, that evaluates the power needed for mining, and minimizes it using a rule-based method. This is combined with a sidechain creation model, that assists in improving QoS performance via dynamically splitting the main blockchain into performance-specific sidechains. These sidechains are categorized into low-power, low-delay, and high-throughput sidechains, which are formed via Elephant Herding Optimization (EHO) model. Due to combination of IGA for consensus selection, and EHO for sidechain creation, the proposed model is able to reduce energy needed for mining by 15.4% when compared with various state-of-the-art models. It is also able to improve mining speed by 5.3%, while maintaining high security performance under different IoT Network attacks. Due to this performance enhancement, the proposed model is capable of being deployed for a wide variety of low-delay healthcare IoT, high-throughput industrial IoT, and low energy home IoT application deployments.
The examination investigates the joining of quantum-safe cryptographic calculations into blockchain innovation, zeroing in on grid-based cryptography and hash-based marks. Because of the inescapable danger presented by quantum processing, this study proposes a quantum-safe blockchain system intended to upgrade the security and flexibility of circulated records. The cross-section-based cryptography calculation uses the computational intricacy of grid issues, offering protection from quantum goes like Shor's calculation. Simultaneously, hash-based marks give lightweight and quantum-safe choices for advanced marks, supporting the general validity of blockchain exchanges. The examination includes a multi-staged approach, incorporating a complete writing survey, hypothetical system improvement, algorithmic execution, and exhaustive investigation of versatility, execution, and information security. Reproduction results will illuminate ensuing equipment executions, approving the down-to-earth attainability of the proposed quantum-safe blockchain. Besides, the review digs into moral and administrative contemplations, adding to the foundation of capable rules for quantum-safe blockchain innovation. Insights into the performance of lattice-based cryptography and hash-based signatures, as well as the provision of a blueprint for future research in quantum-resistant distributed ledger systems, are among the anticipated contributions. The powerful idea of quantum advancements and blockchain requires continuous investigation, and the exploration makes way for future examinations concerning quantum-safe agreement components, upgraded Quantum Key Dispersion, and interdisciplinary coordinated efforts.
Peter Nimbe, Benjamin Asubam Weyori, Jacob Kofi Mensah, Anokye Acheampong Amponsah · 6 authors
Quantum blockchain is a distributed database that is decentralized, encrypted, and based on quantum information theory and computation. This comes as a result of the recent progress made in quantum computing and the need for quantum equivalents of classical blockchains. Algorithms, frameworks, models, tools, architectures, and databases, of which quantum blockchain is a part, are still being standardized. Recently, the growth of quantum information theory and computation has resulted in a rise in the number of research ongoing in this domain. This chapter presents an insight into quantum blockchain using the PRISMA technique with results registered and analyzed. The literature is analyzed based on some parameters or categorizations accompanied by graphical and tabular representations.
Meng Li, Pan Pei, F. Richard Yu, Pengbo Si · 7 authors
Driven by numerous emerging mobile devices and various Quality-of-Service (QoS) requirements, mobile-edge computing (MEC) has been recognized as a prospective paradigm to promote the computation capability of mobile devices, as well as reduce energy overhead and service latency of applications for the Internet of Things (IoT). However, there are still some open issues in the existing research works: 1) limited network and computing resource; 2) simple or nonintelligent resource management; and 3) ignored security and reliability. In order to cope with these issues, in this article, 6G and blockchain technology are considered to improve network performance and ensure the authenticity of data sharing for the MEC-enabled IoT. Meanwhile, a novel intelligent optimization method named as collective reinforcement learning (CRL) is proposed and introduced, to realize intelligent resource allocation, meet distributed training results sharing, and avoid excessive consumption of system resources. Based on the designed network model, a cloud–edge collaborative resource allocation framework is formulated. By joint optimizing the offloading decision, block interval, and transmission power, it aims to minimize the consumption overheads of system energy and latency. Then, the formulated problem is designed as a Markov decision process, and the optimal strategy can be obtained by the CRL. Some evaluation results reveal that the system performance based on the proposed scheme outperforms other existing schemes obviously.
This paper reviews the important application areas of blockchain in Wireless Sensor Networks (WSN) and Internet of Things (IoT) applications. We identify areas where current IoT processes can be enhanced through the use of this new technology with emphasis on the issues addressed in Wireless Body Sensor Networks. This use case is discussed in detail, identifying a suitable blockchain architecture for an industry that is averse to risk, gathering security challenges in this architecture, and providing existing blockchain solutions for these challenges.
In this era, the ultimate vision is to transform current technologies into intelligent global environments to facilitate everyday transactions. The emerging Industry 4.0 has introduced promising potential technologies that have expedited the transition of Internet of Things (IoT) into the Internet of Everything (IoE), utilizing the advances in artificial intelligence. Such a transition implies that sensitive data can be effortlessly accessed via the open network used by various domains such as military, business, transportation, medical, and education, leading to potential security concerns. Although a blockchain, along with the above fields, already employs a fast network such as 5G, the explosive growth in the development and implementation of various Industry 4.0-related domains requires significantly faster networking speeds and a secure mechanism for data transfer. This exhibits the need for 6G to meet the requirements of real-time applications, as shown in the graphical representation of the abstract. The bulk of this work was performed on a blockchain, but some methodology was needed that fulfilled security at different levels, such as the process level, data level, and infrastructure level. Our contribution in this work was twofold: first, at the process level, a novel smart contract mechanism was described; and second, at the data level, a digital signature methodology was employed that allowed anonymization to authenticate and secure the blockchain without encryption.