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A brief study on integration of blockchain technology with 5G enabled IoT services
... The presence of competent human resources enhances the internal processes, which include the methodologies and routines through which work is accomplished. As these internal processes become more streamlined and proficient, they reinforce the organizational structure by providing feedback that can lead to the refinement of organizational hierarchies, communication flows, and decision-making protocols [67]. ...
This study used a technology–organization–environment (TOE) framework as the primary analytical tool to explore the burgeoning capabilities of blockchain technology in the area of 5G ceramic antenna development. A causal loop diagram (CLD) analysis is used to further clarify the complex dynamics and feedback mechanisms, and the impact of blockchain on the design, production, and deployment phases of ceramic antennas, which play a pivotal role in the development of 5G communications, is studied. We found that blockchain’s unique features, including its immutable ledger and decentralized architecture, have the potential to significantly improve the transparency, security, and efficiency of the ceramic antenna manufacturing process. Technology (T), organization (O), and environment (E) were used as the top factors, and the subfactors of TOE were selected and analyzed using the Analytic Hierarchy Process (AHP) by CLD. The AHP analysis was used to evaluate the relative importance of various internal and external factors affecting the adoption of blockchain technology. The integration of the TOE framework with AHP and CLD provides a comprehensive analytical tool that enhances the understanding of the complex dynamics in the 5G ceramic antenna manufacturing process. This methodological approach not only clarifies the interactions between technological, organizational, and environmental factors but also facilitates strategic decision-making through a structured evaluation of these factors. The AHP analysis showed that technical factors are the most important in the TOE analysis of 5G ceramic antenna manufacturing, with a weight of 0.427, which indicates the important role of technical factors in the development of ceramic antenna production. In addition, environmental and organizational factors were given weights of 0.302 and 0.271, respectively, confirming the importance of technological innovation and internal process optimization. In the subfactor of Technology (T), ‘Blockchain Technology’ has the highest ranking among the subfactors, with a global weight value of 0.129, emphasizing the importance of blockchain technology. This study explored the technical and organizational complexities of introducing blockchain technology into the 5G ceramic antenna manufacturing industry and, through an in-depth investigation of the potential benefits of such integration, it aims to propose new approaches to improve quality control and manufacturing efficiency. The research findings aim to contribute to the sustainable growth of the telecommunications industry by providing strategic recommendations for the application of blockchain technology in the production of 5G ceramic antennas.
Globalized delivery of manufacturing and agricultural production offer renewed attention to the health, efficiency, and validation of many vital criteria in the food and agricultural supply chain. That numbers of food safety and corruption hazards have generated an enormous need of an efficient traceability solutions which acts as an essential quality managements tools ensuring to enough product's safety within the agriculture supply chain. Block chain is the revolutionary technological method, which provid es the groundbreaking result for commodity traceableness in agriculture and in food supply chains. Today's agricultural supplying chains are complicated ecosystems mixing several stakeholders making it difficult to validate several significant requirements mainly towards nation of first origin, crop growth phases, quality standards compliance, and yield monitoring. This paper proposes a strategy that levitates the block chain and conducts business operations effectively across the agricultural supply chain for tracking crop prices and traceability. The proposed framework solution discards the need for trusted centralized authority, intermediaries and offers records of the transactions, improving efficient science and safety with high integrity and reliability. All transactions are registered and then stored in block chain's unchangeable ledger with linkages to a decentralized le network, thereby ensuring vary high degree of traceability and transparency in the supply chain ecosystem in a stable, reliable and in efficient manner.
Object tracking and motion detection are the major challenges in the real-time image and video processing applications. There are several tracking and prediction algorithms available to estimate and predict the state of a system. Kalman filter is the most widely used prediction algorithm as it is very simple, efficient and easy to implement for linear measurements. However, these types of filter algorithms are customized on hardware platforms such as Field-Programmable Gate Arrays (FPGAs) and Graphic Processing Units (GPUs) to achieve design requirements for embedded applications. In this work, a multi-dimensional Kalman filter (MDKF) algorithm is proposed for object tracking and motion detection. The numerical analysis of proposed tracking algorithm achieves competitive tracking performance in contrast with state-of-the-art tracking algorithms trained on standard benchmarks. Furthermore, MDKF is implemented on Xilinx Zynq™-7000 System-on-a chip (SoC). The implementation of MDKF on SoC performs 2× times tracking speed than that of software approach. The experimental results provide resource utilization of about 61.43% of Block RAMs (BRAMs), 90.09% of DSPs, 83.27% of Look-up tables (LUTs) and 82.35% of logic cells operating at 140 MHz with power consumption of 780 mW which outperforms previous related methods.
The commercial fifth-generation (5G) wireless communications networks have already been deployed with the aim of providing high data rates. However, the rapid growth in the number of smart devices and the emergence of the Internet of Everything (IoE) applications, which require an ultra-reliable and low-latency communication, will result in a substantial burden on the 5G wireless networks. As such, the data rate that could be supplied by 5G networks will unlikely sustain the enormous ongoing data traffic explosion. This has motivated research into continuing to advance the existing wireless networks toward the future generation of cellular systems, known as sixth generation (6G). Therefore, it is essential to provide a prospective vision of the 6G and the key enabling technologies for realizing future networks. To this end, this paper presents a comprehensive review/survey of the future evolution of 6G networks. Specifically, the objective of the paper is to provide a comprehensive review/survey about the key enabling technologies for 6G networks, which include a discussion about the main operation principles of each technology, envisioned potential applications, current state-of-the-art research, and the related technical challenges. Overall, this paper provides useful information for industries and academic researchers and discusses the potentials for opening up new research directions.
Blockchain is an underlying technology for securing many real-time applications and their data. The automobile is one such sector in which auto-manufacturers are looking forward to accepting the advantages of distributed ledger technology in autonomous vehicles or systems and improving their products, customer satisfaction, and other valuable experiences. This work aims to find the significance of blockchain technology in Autonomous Vehicles, including Autonomous Electric Vehicles (AEV), Autonomous Underwater Vehicles (AUV), Autonomous Guided Vehicles (AGV), Autonomous Aerial Vehicles (AAeV), and Autonomous Driving. In this work, a comparative analysis of blockchain-integrated autonomous vehicle systems is explored to identify the present scenario and futuristic challenges. In addition to blockchain technology, the uses and importance of sensors, architectures and infrastructure requirements, vehicle types, driving modes, vehicles target and tracking approaches, intelligent contracts, intelligent data handling, and industry-specific use cases are also explored. This study is based on the exploration of recent technologies and practices. As autonomous vehicles are expected to be the future of intelligent transportation, this paper surveys recent advances in autonomous vehicles and systems and how blockchain can help in improving user experiences and improving industry practices. Finally, limitations of work, future research directions, and challenges associated with different autonomous vehicles and systems are presented.
The continuous rise in demand, combined with the depletion of the world's fossil fuel reserves, has forced the search for alternative fuels. The biodiesel produced from Roselle is one such indigenous biodiesel with tremendous promise, and its technical ability to operate with compression ignition engines is studied in this work. To characterise the fuel blends, researchers used experimental and empirical approaches while operating at engine loads of 25, 50, 75 and 100%, and with fuel injection timings of 19°, 21°, 23°, 25°, and 27° before top dead center. Results indicate that for 20% blend with change of injection timing from 19° bTDC to 27° bTDC at full load, brake specific fuel consumption and exhaust gas temperature was increased by 15.84% and 4.60% respectively, while brake thermal efficiency decreases by 4.4 %. Also, 18.89% reduction in smoke, 5.26% increase in CO2 and 12.94% increase in NOx were observed. In addition, an empirical model for full range characterization was created. With an r-squared value of 0.9980±0.0011, the artificial neural network model constructed to characterise all 10 variables was able to predict satisfactorily. Furthermore, substantial correlation among specific variables suggested that empirically reduced models were realistic.
Advancements in image and video processing are growing over the
years for industrial robots, autonomous vehicles, indexing databases, surveillance,
medical imaging and computer-human interaction applications. One of the major
challenges in real-time image and video processing is the execution of complex
functions and high computational tasks. In this paper, the hardware acceleration
of different filter algorithms for both image and video processing is implemented
on Xilinx Zynq®-7000 System on-Chip (SoC) device. It consists of Dual-core
Cortex™-A9 processors which provide computing ability to perform I/O and processing
functions and software libraries using Vivado® High-Level Synthesis
(HLS). In the proposed work, Sobel-Feldman filter, posterize and threshold filter
algorithms are implemented for 1920 � 1080 image resolutions. The implementation
results exhibit effective resource utilization such as 45.6% of logic cells, 51%
of Look-up tables (LUTs), 29.47% of Flip-flops, 15% of Block RAMs and 23.63%
of DSP slices under 100 MHz frequency on comparing with previous works.
For current and future Internet of Things (IoT) networks, mobile edge-cloud computation offloading (MECCO) has been regarded as a promising means to support delay-sensitive IoT applications. However, offloading mobile tasks to the cloud gives rise to new security issues due to malicious mobile devices (MDs). How to implement offloading to alleviate computation burdens at MDs while guaranteeing high security in mobile edge cloud is a challenging problem. In this paper, we investigate simultaneously the security and computation offloading problems in a multiuser MECCO system with blockchain. First, to improve the offloading security, we propose a trustworthy access control mechanism using blockchain, which can protect cloud resources against illegal offloading behaviours. Then, to tackle the computation management of the authorized MDs, we formulate a computation offloading problem by jointly optimizing the offloading decisions, the allocation of computing resource and radio bandwidth, and smart contract usage. This optimization problem aims to minimize the long-term system costs of latency, energy consumption and smart contract fee among all MDs. To solve the proposed offloading problem, we develop an advanced deep reinforcement learning algorithm using a double-dueling Q-network. Evaluation results from real experiments and numerical simulations demonstrate the significant advantages of our scheme over the existing approaches.
Industry 4.0 involves innovations with upcoming digital technologies, and blockchain is one of them. Blockchain can be incorporated to improve security, privacy, and data transparency both for small and large enterprises. Industry 4.0 is a synthesis of the new production methods that allow manufacturers to achieve their target more rapidly. Research has been conducted on various Industry 4.0 technologies like Artificial Intelligence (AI), Internet of Things (IoT), Big data, and Blockchain, and how they could create significant interruptions in recent years. These technologies provide various possibilities in the world of manufacturing and supply chain. Blockchain is a technology that has gained much recognition and can enhance the manufacturing and supply chain environment. Various fields now have fascinating insights into the advantages of blockchain. Several research articles on “Blockchain” and “Industry 4.0″ from Google Scholar, Scopus, and other relevant sources are identified and reviewed for this study. This paper discusses the major potential of Blockchain in Industry 4.0. Various drivers, enablers, and associated capabilities of Blockchain technology for Industry 4.0 are discussed for insights. Different Industry 4.0 spheres/sub-domains for Blockchain technology realisation are also discussed. Finally, we have identified and studied fourteen significant applications of Blockchain in Industry 4.0. It is a range of new developments and hope for immense opportunities that are changing Industry 4.0. This technology would work to achieve amplified outcomes and work individually to enhance the process.
The IoT, or Internet of Things has been a major talking point amongst technology enthusiasts in recent years. The internet of thing (IoT) has been emerged and evolved rapidly, making the world’s fabric around us smarter and more responsive. The smart home use one such transformation of IoT, which seems to be the wave of the future. However, with the increasing wide adoption of IoT, data security, and privacy concerns about how our data is collected and shared with others, has also risen. To solve these challenges, an approach to data privacy and security in a smart home using blockchain technology is proposed in this paper. We propose authentication scheme that combines attribute-based access control with smart contracts and edge computing to create a secure framework for IoT devices in smart home systems. The edge server adds scalability to the system by offloading heavy processing activities and using a differential privacy method to aggregate data to the cloud securely and privately. We present several aspects of testing and implementing smart contracts, the differential private stochastic gradient descent algorithm, and system architecture and design. We demonstrate the efficacy of our proposed system by fully examining its security and privacy goals in terms of confidentiality, integrity, and availability. Finally, we undertake a performance evaluation to demonstrate the proposed scheme’s feasibility and efficiency.
Reconfigurable computing is a potential paradigm which has been effectively performing mostly in the developments of devices likely Field Programmable Gate Arrays (FPGAs). This paper illustrates the reconfigurable architecture of FPGA and its types. Most widely used high-speed computation fabrics utilized in reconfigurable computing are FPGAs. This paper demonstrates the architectures used in reconfigurable computing and shows the various advantages of using reconfigurable computing design over conventional Application-Specific Integrated Circuits for achieving high level of performance for a desired application. The survey deals with the architecture of FPGAs and their types in detail. This paper also explains the highlights and challenges of fine-grained and coarse-grained architectures. FPGAs have supported partial reconfiguration over the few years. This survey also includes the partial reconfiguration techniques and the various applications of reconfigurability.
Embedded intelligence (EI) is an emerging research field and has the objective to incorporate machine learning algorithms and intelligent decision-making capabilities into mobile and embedded devices or systems. There are several challenges to be addressed to realize efficient EI implementations in hardware such as the need for: (1) high computational processing; (2) low power consumption (or high energy efficiency); and (3) scalability to accommodate different network sizes and topologies. In recent years, an emerging hardware technology which has demonstrated strong potential and capabilities for EI implementations is the FPGA (field programmable gate array) technology. This paper presents an overview and review of embedded intelligence on FPGA with a focus on applications, platforms and challenges. There are four main classification and thematic descriptors which are reviewed and discussed in this paper for EI: (1) EI techniques including machine learning and neural networks, deep learning, expert systems, fuzzy intelligence, swarm intelligence, self-organizing map (SOM) and extreme learning; (2) applications for EI including object detection and recognition, indoor localization and surveillance monitoring, and other EI applications; (3) hardware and platforms for EI; and (4) challenges for EI. The paper aims to introduce interested researchers to this area and motivate the development of practical FPGA solutions for EI deployment.
Car-sharing systems can solve various urban problems by providing shared vehicles to people and reducing the operation of personal vehicles. With the development of the Internet of Things, people can easily use a shared car through simple operations on their mobile devices. However, the car-sharing system has security problems. Sensitive information, such as the user’s identity, location information, and access code, is transmitted through a public channel for car-sharing. Hence, an attacker can access this information for illegal purposes, making the establishment of a secure authentication protocol essential. Furthermore, the traditional car-sharing system is established on the centralized structure, so there is a single point of failure. Thus, the design of a decentralized car-sharing scheme is vital for solving the centralized problem. This study designed a decentralized car-sharing scheme using blockchain. Specifically, blockchain technology was used to provide a decentralization car-sharing service and ensure data integrity. The participant entities of the proposed system can be authenticated anonymously. The proposed car-sharing system can be secured against various attacks and provide mutual authentication using informal analysis, automated validation of internet security protocols and applications (AVISPA) simulation, and BAN logic analysis. The computation costs and communication costs of the proposed scheme were also analyzed.
As of today, the fifth generation (5G) mobile communication system has been rolled out in many countries and the number of 5G subscribers already reaches a very large scale. It is time for academia and industry to shift their attention towards the next generation. At this crossroad, an overview of the current state of the art and a vision of future communications are definitely of interest. This article thus aims to provide a comprehensive survey to draw a picture of the sixth generation (6G) system in terms of drivers, use cases, usage scenarios, requirements, key performance indicators (KPIs), architecture, and enabling technologies. First, we attempt to answer the question of “Is there any need for 6G?" by shedding light on its key driving factors, in which we predict the explosive growth of mobile traffic until 2030, and envision potential use cases and usage scenarios. Second, the technical requirements of 6G are discussed and compared with those of 5G with respect to a set of KPIs in a quantitative manner. Third, the state-of-the-art 6G research efforts and activities from representative institutions and countries are summarized, and a tentative roadmap of definition, specification, standardization, and regulation is projected. Then, we identify a dozen of potential technologies and introduce their principles, advantages, challenges, and open research issues. Finally, the conclusions are drawn to paint a picture of “What 6G may look like?". This survey is intended to serve as an enlightening guideline to spur interests and further investigations for subsequent research and development of 6G communications systems.
5G mobile communication systems promote the mobile network to not only interconnect people, but also interconnect and control the machine and other devices. 5G-enabled Internet of Things (IoT) communication environment supports a wide-variety of applications, such as remote surgery, self-driving car, virtual reality, flying IoT drones, security and surveillance and many more. These applications help and assist the routine works of the community. In such communication environment, all the devices and users communicate through the Internet. Therefore, this communication agonizes from different types of security and privacy issues. It is also vulnerable to different types of possible attacks (for example, replay, impersonation, password reckoning, physical device stealing, session key computation, privileged-insider, malware, man-in-the-middle, malicious routing, and so on). It is then very crucial to protect the infrastructure of 5G-enabled IoT communication environment against these attacks. This necessitates the researchers working in this domain to propose various types of security protocols under different types of categories, like key management, user authentication/device authentication, access control/user access control and intrusion detection. In this survey paper, the details of various system models (i.e., network model and threat model) required for 5G-enabled IoT communication environment are provided. The details of security requirements and attacks possible in this communication environment are further added. The different types of security protocols are also provided. The analysis and comparison of the existing security protocols in 5G-enabled IoT communication environment are conducted. Some of the future research challenges and directions in the security of 5G-enabled IoT environment are displayed. The motivation of this work is to bring the details of different types of security protocols in 5G-enabled IoT under one roof so that the future researchers will be benefited with the conducted work.
Blockchain is a new generation of secure information technology that is fueling business and industrial innovation. Many studies on key enabling technologies for resource organization and system operation of blockchain-secured smart manufacturing in Industry 4.0 had been conducted. However, the progression and promotion of these blockchain applications have been fundamentally impeded by various issues in scalability, flexibility, and cybersecurity. This survey discusses how blockchain systems can overcome potential cybersecurity barriers to achieving intelligence in Industry 4.0. In this regard, eight cybersecurity issues are identified in manufacturing systems. Ten metrics for implementing blockchain applications in the manufacturing system are devised while surveying research in blockchain-secured smart manufacturing. This study reveals how these cybersecurity issues have been studied in the literature. Based on insights obtained from this analysis, future research directions for blockchain-secured smart manufacturing are presented, which potentially guides research on urgent cybersecurity concerns for achieving intelligence in Industry 4.0.
The manufacturing paradigm with the incorporation of modern emerging technologies such as cloud computing, IoT, cyber-physical systems (CPS), industrial automation as well as the service-oriented manufacturing process has paved the way to build a world where the smart industry or Industry 4.0 is a reality. However, these technological revolutions aren't ready for existing manufacturing platforms that suffer from security and reliability issues mainly because of its dependency on the trust of the central controller. Therefore the main purpose of this study is to orchestrate the development of a distributed decentralized peer to peer connected system architecture that will improve the reliability of the manufacturing process by providing a secure and immutable control information exchange platform. In that regard, we adopt blockchain, the core technology behind the development of cryptocurrencies because of its salient properties which include security, immutability, auditability, anonymity, and decentralization. In this paper, we present a blockchain-based system architecture with the help of clustering and authentication mechanisms to facilitate the development of a decentralized and highly secured system for advanced manufacturing. To evaluate the performance of the proposed system, we conducted a numerical analysis that shows that our proposed methodologies can bring more advantages to advanced manufacturing beyond security and reliability.
The exponential growth of urbanization has impacted the living and working conditions of people in various sectors such as, education, health, and transport. Nevertheless, it also has a negative impact on citizens’ life as they encounter issues like pollution, traffic congestion, environmental resource limitations. Thus, the idea of a smart city was developed to enhance the services provided by transportation, health, energy, and education sectors. However, to provide such services, the smart city uses IoT devices to collect the data and draw conclusions from the data to manage resources effectively. But such a centralized network produces various challenges such as security, privacy, trust, and cost. Blockchain technology, because of its salient features such as transparency and decentralization, can be used to address these challenges. This paper presents a technical review of using blockchain as a solution for Internet of Things (IoT) based smart cities. It also presents the current challenges faced by blockchain technology.
Increasingly, blockchain technology is attracting significant attentions in various agricultural applications. These applications could satisfy the diverse needs in the ecosystem of agricultural products, e.g., increasing transparency of food safety and IoT based food quality control, provenance traceability, improvement of contract exchanges, and transactions efficiency. As multiple untrusted parties, including small-scale farmers, food processors, logistic companies, distributors and retailers, are involved into the complex farm-to-fork pipeline, it becomes vital to achieve optimal trade-off between efficiency and integrity of the agricultural management systems as required in contexts. In this paper, we provide a survey to study both techniques and applications of blockchain technology used in the agricultural sector. First, the technical elements, including data structure, cryptographic methods, and consensus mechanisms are explained in detail. Secondly, the existing agricultural blockchain applications are categorized and reviewed to demonstrate the use of the blockchain techniques. In addition, the popular platforms and smart contract are provided to show how practitioners use them to develop these agricultural applications. Thirdly, we identify the key challenges in many prospective agricultural systems, and discuss the efforts and potential solutions to tackle these problems. Further, we conduct an improved food supply chain in the post COVID-19 pandemic economy as an illustration to demonstrate an effective use of blockchain technology.
Smart Home automation is increasingly gaining popularity among current applications of Internet of Things (IoT) due to the convenience and facilities it provides to the home owners. Sensors are employed within the home appliances via wireless connectivity to be accessible remotely by home owners to operate these devices.With the exponential increase of smart home IoT devices in the marketplace such as door locks, light bulbs, power switches etc, numerous security concerns are arising due to limited storage and processing power of such devices, making these devices vulnerable to several attacks. Due to this reason, security implementations in the deployment of these devices has gained popularity among researchers as a critical research area. Moreover, the adoption of traditional security schemes has failed to address the unique security concerns associated with these devices. Blockchain, a decentralised database based on cryptographic techniques, is gaining enormous attention to assure security of IoT systems. The blockchain framework within an IoT system is a fascinating substitute to the traditional centralised models, which has some significant concerns in fulfilling the demand of smart homes security. In this article, we aim to examine the security of smart homes by instigating the adoption of blockchain and exploring some of the currently proposed smart home architectures using blockchain technology. To present our findings, we describe a simple secure smart home framework based on a refined version of blockchain called Consortium blockchain.We highlight the limitations and opportunities of adopting such an architecture.We further evaluate our model and conclude with the results by designing an experimental testbed using a few household IoT devices commonly available in the marketplace.
Due to the proliferation of ICT during the last few decades, there is an exponential increase in the usage of various smart applications such as smart farming, smart healthcare, supply-chain & logistics, business, tourism and hospitality, energy management, etc. However, for all the aforementioned applications, security and privacy are major concerns keeping in view of the usage of the open channel, i.e., the Internet for data transfer. Although many security solutions and standards have been proposed over the years to enhance the security levels of the aforementioned smart applications, the existing solutions are either based upon centralized architecture (having a single point of failure) or having high computation and communication costs. Moreover, most of the existing security solutions have focussed only on a few aspects and fail to address scalability, robustness, data storage, network latency, auditability, immutability, and traceability. To handle the aforementioned issues, blockchain technology can be one of the solutions. Motivated from these facts, in this paper, we present a systematic review of various blockchain-based solutions and their applicability in various Industry 4.0-based applications. Our contributions in this paper are four fold. Firstly, we explored the current state-of-the-art solutions in the blockchain technology for smart applications. Then, we illustrated the reference architecture used for the blockchain applicability in various Industry 4.0 applications. Then, the merits and demerits of the traditional security solutions are also discussed in comparison to their countermeasures. Finally, we provided a comparison of existing blockchain-based security solutions using various parameters to provide deep insights to the readers about its applicability in various applications.
The Internet of Things (IoT) became widely
utilized during last years, due to the large number of object
that are connected to it - not only computers, but also humans,
sensors and actuators. In the near future, a large number of
objects will communicate to each other in a way never
experienced before by the humankind. Connecting all these
objects together will come with a wide area of challenges.
One of the most important issues concerns trust. In majority of
cases, centralized architectures are used to solve the problem,
but the enormous number of object that can be connected in
IoT will make almost impossible to manage and implement
these solutions. Blockchain technology offers powerful
solutions for decentralized architectures, which can be the
future of IoT systems. A strong solution needs to be flexible to
changes and must offer powerful resources to be successful. A
hardware platform that uses FPGAs is suitable for those
systems. In this paper we propose a solution for securing IoT
systems using blockchain technology, implemented on a FPGA
based architecture.
This study formulates the problem of radio resource and data transmission strategy in a dense HetNet enhanced with mobile cloud computing and mobile edge computing technologies as a combinatorial optimisation problem. An ant colony optimisation (ACO)-based energy-aware algorithm is proposed as solution approach, which consists of a data transmission management scheme and a physical resource blocks/bandwidth allocation scheme. Simulation results show that compared with baseline approaches [(greedy and data split multiple user equipment (UEs) algorithms]), the proposed ACO-based algorithm achieves: (i) about 99% of reduction in terms of transmission delay under varying data file sizes (resp. varying number of UEs in the network); (ii) about 99% of reduction in terms of transmission energy dissipated by an UE during transmission of a file under varying data file sizes (resp. varying number of UEs in the network); (iii) improved performance with an increase in the number of small base stations in the network, (iv) significant reduction in the energy transmitted (by the UE) during transmission of big data files to the cloud storage; and (v) some stability irrespective of the variation in network conditions such as increasing the number of active UEs or increasing the number of UEs in the network.
Blockchain, the technology of the future neutrally facilitated the financial transactions in cryptocurrencies by strictly eliminating the need for a governing authority or a management that was required to authorize the transactions based on trust and transparency. The Blockchain Network also follows the principle of absolute privacy and anonymity on the identification of the users associated in a transaction. Since the time of its inception, the Blockchain Technology has undergone research that has demonstrated some various kinds of methods to sort out the access control system of the conventional system. In recent years Blockchain has also shown optimum reliability in multiple sectors such as Smart Home, Healthcare, Banking, Information Storage Management, Security and etc. This work in terms is further concerned to the sector of Smart Healthcare, which has grown to a much affluence regarding the efficient technique of serving and dictating medical health care to the patients with the point of maintaining privacy of the patients’ data and also the process of laying out real time accurate and trusted data to the medical practitioners. But in the scenario of Smart Healthcare, the primary concern arises in the fact of Privacy and Security of the data of the patients due to the interoperability of multiple stakeholders in the process. Also, there has been a fact of determining accurate and proper data to the doctors if the concerned subject is out of reach from the in hand medical service. Therefore, this Concern of privacy and also mitigation of the accurate data has been very much managed in the work by regulating, a monitoring and sensing paradigm with accordance to the IOT and the Blockchain as a transaction and access management system and also an appropriate medium for laying out accurate and trusted data for serving with deliberate medical care and benefits to the patients across.
The Internet of Things (IoT) is poised to transform human life and unleash enormous economic benefit. However, inadequate data security and trust of current IoT are seriously limiting its adoption. Blockchain, a distributed and tamper-resistant ledger, maintains consistent records of data at different locations, and has the potential to address the data security concern in IoT networks. While providing data security to the IoT, Blockchain also encounters a number of critical challenges inherent in the IoT, such as a huge number of IoT devices, non-homogeneous network structure, limited computing power, low communication bandwidth, and error-prone radio links. This paper presents a comprehensive survey on existing Blockchain technologies with an emphasis on the IoT applications. The Blockchain technologies which can potentially address the critical challenges arising from the IoT and hence suit the IoT applications are identified with potential adaptations and enhancements elaborated on the Blockchain consensus protocols and data structures. Future research directions are collated for effective integration of Blockchain into the IoT networks.
Internet of Things (IoT) and cloud computing are increasingly integrated, in the sense that data collected from IoT devices (generally with limited computational and storage resources) are being sent to the cloud for processing, etc., in order to inform decision making and facilitate other operational and business activities. However, the cloud may not be a fully trusted entity, like leaking user data or compromising user privacy. Thus, we propose a privacy-preserving and user-controlled data sharing architecture with fine-grained access control, based on the blockchain model and attribute-based cryptosystem. Also, the consensus algorithm in our system is the Byzantine fault tolerance mechanism, rather than Proof of Work.
With the development towards the next generation cellular networks, i.e., 5G, the focus has shifted towards meeting the higher data rate requirements, potential of micro cells and millimeter wave spectrum. The goals for next generation networks are very high data rates, low latency and handling of big data. The achievement of these goals definitely require newer architecture designs, upgraded technologies with possible backward support, better security algorithms and intelligent decision making capability. In this survey, we identify the opportunities which can be provided by 5G networks and discuss the underlying challenges towards implementation and realization of the goals of 5G. This survey also provides a discussion on the recent developments made towards standardization, the architectures which may be potential candidates for deployment and the energy concerns in 5G networks. Finally, the paper presents a big data perspective and the potential of machine learning for optimization and decision making in 5G networks.
With the explosive growth of IoT (Internet of Things) devices and massive data produced at the edge of the network, the traditional centralized cloud computing model has come to a bottleneck due to the bandwidth limitation and resources constraint. Therefore, edge computing, which enables storing and processing data at the edge of the network, has emerged as a promising technology in recent years. However, the unique features of edge computing, such as content perception, real-time computing, and parallel processing, has also introduced several new challenges in the field of data security and privacy-preserving, which are also the key concerns of the other prevailing computing paradigms, such as cloud computing, mobile cloud computing, and fog computing. Despites its importance, there still lacks a survey on the recent research advance of data security and privacy-preserving in the field of edge computing. In this paper, we present a comprehensive analysis of the data security and privacy threats, protection technologies, and countermeasures inherent in edge computing. Specifically, we first make an overview of edge computing, including forming factors, definition, architecture, and several essential applications. Next, a detailed analysis of data security and privacy requirements, challenges, and mechanisms in edge computing are presented. Then, the cryptography-based technologies for solving data security and privacy issues are summarized. The state-of-the-art data security and privacy solutions in edge-related paradigms are also surveyed. Finally, we propose several open research directions of data security in the field of edge computing.
The present study is aimed to discover and equate effect of daok biodiesel-diesel and daok biodiesel-antioxidant additive catechol-diesel blends on performance and emission characteristics (PEC) of a direct-injection diesel engine. Tests are conducted on daok biodiesel percentage of 10, 20, 40, 60 and 100% at variable engine loads and compression ratios (CRs) with 1500 rpm. At First, several pilot experiments are conducted among the doak biodiesel-diesel blends and found B20 as the optimum blend based on PEC of the engine. At rated speed of 1500 rpm, compression ratio is altered for the blend B20 and identified better engine PEC at CR 17.5. Then, 0.5, 1.5 and 2.5% of antioxidant catechol (CAT) additive is blended with B20 and investigated the PEC of the engine operating at CR17.5. Tested fuel blends indicated that the 2.5% of CAT in B20 blend produced better performance and yielded 6.45% rise in BTE, while 1.5% of CAT in B20 blend diminished CO and HC emissions by 26.08%, and 18.75% respectively as compared to B20 blend. It was also shown that adding CAT at a concentration of 0.5%–2.5% in a B20 biodiesel blend is sufficient for a considerable improvement in oxidation stability without affecting the physicochemical qualities. As a result, a low-cost CAT additive in daok biodiesel and diesel fuel can be used in direct injection diesel engines without requiring any additional engine configuration changes.
Zinc oxide nano additives of 250 ppm, 500 ppm, and 1000 ppm were blended with diesel fuel. The prepared fuels which were designated as DF-250 ppm ZnO, DF-500 ppm ZnO, and DF - 1000 ppm ZnO were tested for engine characteristics along with diesel fuel (DF) in a standard bench-scale engine. All the tests were carried out at different speeds of the engine ranging between 2000 and 3000 rpm with unvarying engine load and advanced injection timing. The outcomes from these experiments exhibited higher brake thermal efficiency and cylinder pressure for fuels with ZnO nano additives than that of diesel fuel. The emission gas temperature and brake-specific fuel consumption were noticed to be lower for fuels blended with ZnO nano additive than those of diesel fuel. The level of SPM emissions also increased in compression ratio from CR = 15.5 to CR = 16.5, but starting from CR of 17.5, the SPM emissions for all the investigated fuels were relatively constant with a slight decrease at the maximum compression ratio. In addition, at all test conditions, NO and SO2 emissions from the engine tail pipe were higher with ZnO mixed diesel fuel.
Plastics are one of the major pollutants to the environment. An investigation is carried out in converting low density polyethylene (LDPE) to oil by pyrolysis method with the aid of catalyst for the use in internal combustion engines. Experiments were conducted at different speeds (1200, 1500 and 1800 rpm) and variable loads (low, medium and full) with constant compression ratio engine to evaluate the performance and ecological parameters. Plastic pyrolyzed oil (PPO) is blended with diesel fuel in 20:80 volume proportion to get D80PO20 blended mixture which is employed in engine in order to assess its characteristics. Encouraging outcomes have been obtained as cylinder pressure in combustion is of same order as that of diesel fueled engine. The results showed that increasing engine speeds resulted in higher cylinder pressure and brake thermal efficiency. Also, high nitrogen oxide (NOX) and low brake specific energy consumption (BSFC) has been identified. Lower smoke (BSN) and NOX emissions are noticed from engine tail pipe with D80PO20 blended mixture.
Nowadays, many disruptive Internet of things (IoT) applications emerge, such as augmented/virtual reality (AR/VR) online games, autonomous driving, and smart everything, which are massive in number, data-intensive, computation-intensive, and delay-sensitive. Due to the mismatch between the fifth generation (5G) and the requirements of such massive IoT-enabled applications, there is a need for technological advancements and evolutions for wireless communications and networking toward the sixth generation (6G) networks. 6G is expected to deliver extended 5G capabilities at a very high level, such as Tbps data rate, sub-ms latency, cm-level localization, and so on, which will play a significant role in supporting massive IoT devices to operate seamlessly with highly diverse service requirements. Motivated by the aforementioned facts, in this paper, we present a comprehensive survey on 6G-enabled massive IoT. First, we present the drivers and requirements by summarizing the emerging IoT-enabled applications and the corresponding requirements, along with the limitations of 5G. Second, visions of 6G are provided in terms of core technical requirements, use cases, and trends. Third, a new network architecture provided by 6G to enable massive IoT is introduced, i.e., space-air-ground-underwater/sea networks enhanced by edge computing. Fourth, some breakthrough technologies, such as machine learning and blockchain, in 6G are introduced, where the motivations, applications, and open issues of these technologies for massive IoT are summarized. At last, a use case of fully autonomous driving is presented to show 6G supports massive IoT.
After smart grid, Internet of Energy (IoE) has emerged as a popular technology in the energy sector by integrating different forms of energy. IoE uses Internet to collect, organize, optimize and manage the networks energy information from different edge devices in order to develop a distributed smart energy infrastructure. Sensors and communication technologies are used to collect data and to predict demand and supply by consumers and suppliers respectively. However, with the development of renewable energy resources, Electric Vehicles (EVs), smart grid and Vehicle-to-grid (V2G) technology, the existing energy sector started shifting towards distributed and decentralized solutions. Moreover, the security and privacy issues because of centralization is another major concern for IoE technology. In this context, Blockchain technology with the features of automation, immutability, public ledger facility, irreversibility, decentralization, consensus and security has been adopted in the literature for solving the prevailing problems of centralized IoE architecture. By leveraging smart contracts, blockchain technology enables automated data exchange, complex energy transactions, demand response management and Peer-to-Peer (P2P) energy trading etc. Blockchain will play vital role in the evolution of the IoE market as distributed renewable resources and smart grid network are being deployed and used. We discuss the potential and applications of blockchain in the IoE field. This article is build on the literature research and it provides insight to the end-user regarding the future IoE scenario in the context of blockchain technology. Lastly this article discusses the different consensus algorithm for IoE technology.
As the great prevalence of various Internet of Things (IoT) terminals, how to solve the problem of isolated information among different IoT platforms attracts attention from both academia and industry. It is necessary to establish a trusted access system to achieve secure authentication and collaborative sharing. Therefore, this paper proposes a distributed and trusted authentication system based on Blockchain and edge computing, aiming to improve authentication efficiency. This system consists of Physical network layer, Blockchain edge layer and Blockchain network layer. Through the Blockchain network, an optimized practical Byzantine fault tolerance (PBFT) consensus algorithm is designed to construct a consortium Blockchain for storing authentication data and logs. It guarantees trusted authentication and achieves activity traceability of terminals. Furthermore, edge computing is applied in Blockchain edge nodes, to provide name resolution and edge authentication service based on smart contracts. Meanwhile, an asymmetric cryptographic algorithm is designed, to prevent connection between nodes and terminals from being attacked. And a caching strategy based on edge computing is proposed to improve hit ratio. Our proposed authentication mechanism is evaluated with respect to communication and computation costs. Simulation results show that the caching strategy outperforms existing edge computing strategies by 6%-12% in terms of average delay, and 8%-14% in hit ratio.
Wireless Virtualization (WiVi) is emerging as a new paradigm to provide high speed communications and meet Quality-of-Service (QoS) requirements of users while reducing the deployment cost of wireless infrastructure for future wireless networks. In WiVi, Wireless Infrastructure Providers (WIPs) sublease their RF channels through slicing to Mobile Virtual Network Operators (MVNOs) based on their Service Level Agreements (SLAs) and the MVNOs independently provide wireless services to their end users. This paper investigates the wireless network virtualization by leveraging both Blockchain technology and machine learning to optimally allocate wireless resources. To eliminate double spending (aka over-committing) of WIPs' wireless resources such as RF channels, Blockchain - a distributed ledger - technology is used where a reputation is used to penalize WIPs with past double spending habit. The proposed reputation based approach helps to minimize extra delay caused by double spending attempts and Blockchain operations. To optimally predict the QoS requirements of MVNOs for their users, linear regression - a machine learning approach - is used that helps to minimize the latency introduced due to (multiple wrong) negotiations for SLAs. The performance evaluation of the proposed approach is carried out by using numerical results obtained from simulations. Results have shown that the joint Blockchain and machine learning based approach outperforms the other approaches.
The rapid increase in the number and diversity of smart devices connected to the Internet has raised the issues of flexibility, efficiency, availability, security, and scalability within the current IoT network. These issues are caused by key mechanisms being distributed to the IoT network on a large scale, which is why a distributed secure SDN architecture for IoT using the blockchain technique (DistBlockNet) is proposed in this research. It follows the principles required for designing a secure, scalable, and efficient network architecture. The DistBlockNet model of IoT architecture combines the advantages of two emerging technologies: SDN and blockchains technology. In a verifiable manner, blockchains allow us to have a distributed peer-to-peer network where non-confident members can interact with each other without a trusted intermediary. A new scheme for updating a flow rule table using a blockchains technique is proposed to securely verify a version of the flow rule table, validate the flow rule table, and download the latest flow rules table for the IoT forwarding devices. In our proposed architecture, security must automatically adapt to the threat landscape, without administrator needs to review and apply thousands of recommendations and opinions manually. We have evaluated the performance of our proposed model architecture and compared it to the existing model with respect to various metrics. The results of our evaluation show that DistBlockNet is capable of detecting attacks in the IoT network in real time with low performance overheads and satisfying the design principles required for the future IoT network.