Considering the computation resources available with sensor devices and the value and validity of Cognitive Wireless Communication Network (CWCN), traditional blockchain is not feasible for CWCN. Further, considering the security and privacy for CWCN that can directly impact human life (as in the case of ambient assisted living applications), blockchain provides a good solution for such applications, however, with some simplicity in the computation of Proof of Work (PoW). Therefore, the fourth objective solution comes up with a simplified energy-efficient blockchain implementation for CWCN that consumes less energy in computation time. The energy-hungry blockchain has been implemented on resource-constrained CWCN for ambient assisted living applications specialized for elderly care. The process includes a collection of physical environmental parameters on a single board computer-based CWCN. The implementation includes possible simplification in the most energy-consuming process, i.e., the mining process, which makes it energy efficient in computation time as energy consumption is a computation time factor.
To bridge the current gap between the Blockchain expectancies and their intensive computation constraints, the present paper advances a lightweight processing solution, based on a load-balancing architecture, compatible with the lightweight/embedding processing paradigms. In this way, the execution of complex operations is securely delegated to an off-chain general-purpose computing machine while the intimate Blockchain operations are kept on-chain. The illustrations correspond to an on-chain Tezos configuration and to a multiprocessor ARM embedded platform (integrated into a Raspberry Pi). The performances are assessed in terms of security, execution time, and CPU consumption when achieving a visual document fingerprint task. It is thus demonstrated that the advanced solution makes it possible for a computing intensive application to be deployed under severely constrained computation and memory resources, as set by a Raspberry Pi 3. The experimental results show that up to nine Tezos nodes can be deployed on a single Raspberry Pi 3 and that the limitation is not derived from the memory but from the computation resources. The execution time with a limited number of fingerprints is 40% higher than using a classical PC solution (value computed with 95% relative error lower than 5%).
Blockchain technology has gained immense popularity over the last decade. It has transformed several industries by enabling processes to work in a secure and decentralized manner. Blockchain consists of blocks that are linked together through cryptography. Blockchain is a distributed ledger that contains a set of sequenced blocks of data. Each block records transaction data in a transparent, immutable, and secure fashion. Consensus algorithm is the key part of this technology as it is used for the decision-making process among nodes in the blockchain network. Nodes in the verifying network use consensus algorithm to reach mutual agreement about state of the blockchain whenever a new block is added. This makes it possible to accept any transaction in the blockchain. Many consensus algorithms have been proposed in the literature each having its own performance and security characteristics. In this paper, we present a pattern for one of the most widely used blockchain consensus algorithms, which is the Proof of Work (PoW) algorithm. This paper is a part of our project on blockchain architecture and patterns.
Bruno M. G. Rosa, Salzitsa Anastasova, Guang‐Zhong Yang
Implantable devices represent the future of remote medical monitoring and administration of both chemical and physical therapies to the patients. Although some of these devices are already in the market, the security mechanisms deployed inside them to withstand deliberate external influence are still decades away from the robust digital data security schemes employed in modern distributed networks these days. Medical data theft, spoofing, and disclosure pose serious threats that can ultimately lead to individual and social stigmas or even death. In this article, we present a small-form and batteryless implantable device with acquisition channels for biopotential (30-dB gain and 16-Hz bandwidth), arterial pulse oximetry, and temperature (0.12°C accuracy) recordings, suitable for cardiovascular, neuronal, and endocrine parameters assessment. The proposed device is powered by the near-field communication (NFC) interface with an external mobile phone, with a power consumption of 0.9 mW and achieving the full operation for distances close to 1 cm under the skin. In situ encryption of the acquired physiological signals is performed by a lightweight and short-term symmetric-key distribution scheme with data stream hopping, in order to ensure secure data transference over the air between the patient and trusted entities only, complemented by data storage, processing, and recovery through a medical blockchain type of network that involves the main stakeholders inside a medical community.
This work investigates the dynamic spectrum sharing in the 6G enhanced ultra-reliable and low latency communications (eURLLC) services, as more and more Internet of Things (IoT) devices need to communicate between each other in the limited spectrum. We combine blockchain technology with 6G hybrid cloud to realize the spectrum sharing between IoT devices. Due to blockchain's distributed storage and credibility, blockchain based dynamic spectrum sharing can achieve flexible, feasible and much more efficient spectrum allocation. In this paper, we analyze the process of spectrum sharing, and a radio spectrum resource sharing structure in eURLLC based on reinforcement learning (RL) is proposed, including resource classification, resource scheduling, overall model, and neural network optimization. In this design, we integrate blockchain with hybrid cloud to build a public management platform to register and manage the information of IoT devices using the unified coding and identification standards.
Vikas Goel, Narendra Kumar, Amit Kumar Gupta, Sachin Kumar
In recent times, the two technologies, artificial intelligence (AI) and blockchain, are the most trending and disruptive in all technologies. Undoubtedly both technologies are covering all the areas of engineering and science with an exceptional rate. These technologies offer various degrees of technological complexity and multi-dimensional business implications. Blockchain is an open, distributed ledger technology that records all the transactions done. These distributed ledger technologies have disrupted the evolving technology sector. Blockchain can authorize and automate payment transactions in cryptocurrency. Also, blockchain has provided access to a shared ledger (block) of data, digital transactions, and logs in an environment that is decentralized, secure, and trusted. Blockchain governs the interactions among distributed participants with the capability of no intermediary or a trusted third party. Blockchain technology is evolving day by day with a fast-passed pace. Now, it is possible to integrate blockchain with many other evolving technologies like robotics with AI services. AI provides intelligence and decision-making capabilities like humans to machines. Data is the main constituent to develop AI and machine learning. Now, AI has a wide variety of uses from finance (stock trading) to web (chatbots) to advanced technology (self-driving cars). Before the advent of big data, AI was a conceptual model. Artificial intelligence (AI) works significantly as a strong analytic tool to analyze big data in a scalable, accurate, and real-time. By using artificial intelligence, the design and development of tools for big data analysis has certain issues like centralized architecture, security, privacy, resource constraints, and lack of enough training data. There is rarely today any human activity, machine control, and business logic that is not considered artificial intelligence in future years and decades. On the contrary, blockchain considers decentralized architecture as an emerging technology. Among the various distributed nodes of the IoT network, secure sharing of data and resources is provided by the blockchain. It is expected to remove centralized control and may overcome the other existing challenges in AI. In this chapter, we consider, emphasize, and analyze how blockchain implementation is supported or enhanced via various AI techniques. We will further review how artificial intelligence may be exploited to achieve the goal of blockchain 2.0. There seem to be numerous possibilities in the alliance of AI and blockchain in Industry 4.0.
The sixth generation (6G) systems are generally recognized to be established on ubiquitous Artificial Intelligence (AI) and distributed ledger such as blockchain. However, the AI training demands tremendous computing resource, which is limited in most 6G devices. Meanwhile, miners in Proof-of-Work (PoW) based blockchains devote massive computing power to block mining, and are widely criticized for the waste of computation. To address this dilemma, we propose an Evolved-Proof-of-Work (E-PoW) consensus that can integrate the matrix computations, which are widely existed in AI training, into the process of brute-force searches in the block mining. Consequently, E-PoW can connect AI learning and block mining via the multiply used common computing resource. Experimental results show that E-PoW can salvage by up to 80 percent computing power from pure block mining for parallel AI training in 6G systems.
The adoption of Internet of Things (IoT) technology across many applications, such as autonomous systems, communication, and healthcare, is driving the market’s growth at a positive rate. The emergence of advanced data analytics techniques such as blockchain for connected IoT devices has the potential to reduce the cost and increase in cloud platform adoption. Blockchain is a key technology for real-time IoT applications providing trust in distributed robotic systems running on embedded hardware without the need for certification authorities. There are many challenges in blockchain IoT applications such as the power consumption and the execution time. These specific constraints have to be carefully considered besides other constraints such as number of nodes and data security. In this paper, a novel approach is discussed based on hybrid HW/SW architecture and designed for Proof of Work (PoW) consensus which is the most used consensus mechanism in blockchain. The proposed architecture is validated using the Ethereum blockchain with the Keccak 256 and the field-programmable gate array (FPGA) ZedBoard development kit. This implementation shows improvement in execution time of 338% and minimizing power consumption of 255% compared to the use of Nvidia Maxwell GPUs.
Shakila Zaman, Muhammad R. A. Khandaker, Risala Tasin Khan, Faisal Tariq · 5 authors
The Internet-of-Things (IoT) is an emerging technology that connects and integrates a massive number of smart physical devices with virtual objects operating in diverse platforms through the internet. Due to massive size and physical spread of many applications such as smart healthcare, IoT is increasingly implemented in distributed setting. This distributed nature of implementation of the entities connected to the IoT networks are exposed to an unprecedented level of privacy and security threats. This is particularly severe for IoT healthcare system as it involves huge volume of sensitive and personal data. Although blockchain has posed to be the solution in this scenario thanks to its inherent distributed ledger technology (DLT), it suffers from a major drawback of rapidly increasing storage and computation requirements with the increase in network size which makes its implementation impractical. This paper proposes a holochain-based security and privacy-preserving framework for IoT healthcare systems that overcomes the scalability challenge and is particularly suited for resource constrained IoT scenarios. Through thorough analysis and performance results, we have demonstrated that the holochain based IoT healthcare solution outperforms blockchain based solution in terms of resource requirements while ensuring appropriate level of privacy and security.
As Internet of Things (IoT) revolutionized over the years, it has become a crucial part in many application such as smart city and smart transportation, ensuring smooth functioning of the human life in a more reliable manner. As the amount of data that is to be collected, stored and analyzed increases, there is need for a system that perform these tasks in a more efficient manner. Artificial intelligence plays a crucial part in delivering these requirements. But when AI is involved, it will also result in the use of big tools that are necessary for tackling the issue at hand. Hence in order to ensure that AI can function in a smooth manner, blockchain support is introduced such that it develops a decentralized architecture. Block chain will provide a safe and secure environment to share the information and resources and can also address the drawbacks of Artificial intelligence. The purpose of this proposed work is to develop a hybrid architecture, combining the advantages of blockchain and artificial intelligence to enable big data analysis. We have performed an analysis and results have been observed to conclude the impact of blockchain in Artificial Intelligence in the aspect of latency and accuracy. The results indicate that the proposed architecture excels over the other architectures and can also overcome some of the challenges prevalent.
Amirhossein Adavoudi Jolfaei, Seyed Farhad Aghili, Dave Singelée
Recently, blockchain-based Internet of Medical Things (IoMT) has started to receive more attention in the healthcare domain as it not only improves the care quality using real-time and continuous monitoring but also minimizes the cost of care. However, there is a clear trend to include many entities in IoMT systems, such as IoMT sensor nodes, IoT wearable medical devices, patients, healthcare centers, and insurance companies. This makes it challenging to design a blockchain framework for these systems where scalability is a most critical factor in blockchain technology. Motivated by this observation, in this survey we review the state-of-the-art in blockchain-IoMT systems. Comparison and analysis of such systems prove that there is a substantial gap, which is the negligence of scalability. In this survey, we discuss several approaches proposed in the literature to improve the scalability of blockchain technology, and thus overcoming the above mentioned research gap. These approaches include on-chain and off-chain techniques, based on which we give recommendations and directions to facilitate designing a scalable blockchain-based IoMT system. We also recommended that a designer considers the well-known trilemma along with the various dimensions of a scalable blockchain system to prevent sacrificing security and decentralization as well. Moreover, we raise several research questions regarding benchmarking; addressing these questions could help designers determining the existing bottlenecks, leading to a scalable blockchain.
The blockchain technology is quickly becoming the most disruptive technology of recent times. This technology has generated a lot of buzz and optimism, and it has gained a lot of attention from both the public and private sectors. Information can be transferred using blockchain technology in a manner that is confidential, safe, reliable, and open to scrutiny. This analysis focuses on the ways in which blockchain technology can be used to solve problems related to scalability and give solutions in the context of the healthcare industry. In light of this, the proposed solutions can be categorized into two primary categories: storage optimization and blockchain redesign. However, there are still several restrictions, such as the block size, the enormous volume of data and transactions, the number of nodes, and the obstacles posed by the protocol. It has seen widespread application in decentralized crypto currencies like Bitcoin and Ethereum, for example. An example of a public blockchain application that was successful, Bitcoin, was the impetus for a significant increase in research and development into blockchain technology. Nevertheless, scalability continues to be a significant obstacle. According to the facts that we've compiled, the primary causes of scalability issues appear to be bottlenecks in the transaction throughput, the network latency, and the consensus methods. On the other side, the potential for scalability includes the application of techniques like as sharding, hybrid systems, and off-chain computations. We also examine the consequences of these findings as well as prospective paths for future study to help solve the scalability problems that blockchain-based systems provide.
The combination of blockchain technology and Internet of Things (IoT) technology has brought many significant advantages and new development directions. With the development of embedded technology and 5G communication technology, the performance limitations and network limitations that are traditionally believed to restrict the application of blockchain technology to IoT devices have been broken. The development of "blockchain + 5G + IoT" provides reliable data from the source for the blockchain, linking the credible mapping of physical assets and digital assets. However, at the beginning of the blockchain design, the application of the IoT was not fully considered, so there have been some obvious defects in applying the blockchain technology in the IoT. In the Byzantine fault tolerance (BFT) consensus algorithm of traditional blockchain, the entire blockchain network will become paralyzed when more than 1/3 of the nodes in the network are offline. However, in IoT applications, this situation is likely to occur and greatly limits the security and stability of the application of blockchain technology in the IoT. In order to solve this problem, we proposed an IoT adaptive dynamic blockchain networking method based on discrete heartbeat signals. The feature of the method is to set a different monitoring time for each group of nodes, that is, discrete heartbeat signals monitoring. When the number of nodes gradually decreases, the IoT adaptive dynamic blockchain network can dynamically adapt to this process. Even when more than 1/3 of the IoT are offline, the adaptive dynamic IoT blockchain network can maintain stable running. This method also has the advantages of a short network expectation recovery time and avoids instantaneous system paralysis caused by the thundering herd effect. This research improves the security and stability of the application of blockchain technology in the IoT, and provides the necessary technical foundation for the better combination of blockchain technology and IoT technology.
Sudip Maitra, Venkata P. Yanambaka, Deepak Puthal, Ahmed Abdelgawad · 5 authors
Abstract The modern era of information and technology leverages connectivity and information sharing for enhancing applications and reducing human intervention. The proliferation of Internet of Things (IoT) in almost all aspects of modern life raises major challenges of security and privacy in health care services and the pharmaceutical industry. Blockchain has emerged as a secure technology in a trustless network without central governance. The inherent attributes it provides can solve the security and privacy challenges related to IoT and extend its capabilities. However, traditional instances of Blockchain are not suited for the IoT environment for reasons such as computationally expensive consensus process. Proof of authentication is a lightweight consensus algorithm that can be implemented in the IoT environment. This paper presents an IoT‐friendly Blockchain scheme implemented to evaluate the feasibility of medical supply and drug transportation to aid security and mitigate privacy issues which are fault‐tolerant, transparent, and traceable. The proof of concept implementation on portable single board computer demonstrates proof of authentication consensus algorithm executed with block validation and block addition in 30 and 40 ms while consuming 45 and 60mJ, respectively. Additionally, the network performance of the proposed architecture was presented and evaluated in the application context.