Privacy preserving personalized blockchain reliability prediction via federated learning in IoT environments

Cluster Computing - The integration of blockchain and the Internet of Things (IoT) is seen as having significant potential. In IoT Environments, Blockchain builds a trusted environment for IoT...     

Privacy protection for fog computing and the internet of things data based on blockchain

Cluster Computing - With the development of the Internet of Things (IoT) field, more and more data are generated by IoT devices and transferred over the network. However, a large amount of IoT data...     

IoT Big-Data Centred Knowledge Granule Analytic and Cluster Framework for BI Applications: A Case Base Analysis

The current rapid growth of Internet of Things (IoT) in various commercial and non-commercial sectors has led to the deposition of large-scale IoT data, of which the time-critical analytic and clustering of knowledge granules represent highly thought-provoking application possibilities. The objective of the present work is to inspect the structural analysis and clustering of complex knowledge granules in an IoT big-data environment. In this work, we propose a knowledge granule analytic and clustering (KGAC) framework that explores and assembles knowledge granules from IoT big-data arrays for a business intelligence (BI) application. Our work implements neuro-fuzzy analytic architecture rather than a standard fuzzified approach to discover the complex knowledge granules. Furthermore, we implement an enhanced knowledge granule clustering (e-KGC) mechanism that is more elastic than previous techniques when assembling the tactical and explicit complex knowledge granules from IoT big-data arrays. The analysis and discussion presented here show that the proposed framework and mechanism can be implemented to extract knowledge granules from an IoT big-data array in such a way as to present knowledge of strategic value to executives and enable knowledge users to perform further BI actions.     

Fog computing in enabling 5G-driven emerging technologies for development of sustainable smart city infrastructures

Cluster Computing - The usage of 5G-enabled IoT devices is rising exponentially as humans tend to shift towards a more automated lifestyle. A significant amount of IoT devices is expected to join...     

A fuzzy approach for optimal placement of IoT applications in fog-cloud computing

Fog-cloud computing is a promising distributed model for hosting ever-increasing Internet of Things (IoT) applications. IoT applications should meet different characteristics such as deadline, frequency rate, and input file size. Fog nodes are heterogeneous, resource-limited devices and cannot accommodate all the IoT applications. Due to these difficulties, designing an efficient algorithm to deploy a set of IoT applications in a fog-cloud environment is very important. In this paper, a fuzzy approach is developed to classify applications based on their characteristics then an efficient heuristic algorithm is proposed to place applications on the virtualized computing resources. The proposed policy aims to provide a high quality of service for IoT users while the profit of fog service providers is maximized by minimizing resource wastage. Extensive simulation experiments are conducted to evaluate the performance of the proposed policy. Results show that the proposed policy outperforms other approaches by improving the average response time up to 13%, the percentage of deadline satisfied requests up to 12%, and the resource wastage up to 26%.

     

Privacy challenges of IoT-based blockchain: a systematic review

Cluster Computing - The Internet of Things (IoT) has infiltrated extensively into our lifestyles. Nevertheless, IoT privacy remains a significant obstacle, primarily because of the large size and...     

AI-assisted bio-inspired algorithm for secure IoT communication networks

Cluster Computing - The Internet of Things (IoT) is made up of intelligent devices that interact with each other. It allows information to be gathered and shared by these devices. In addition, IoT...     

Trust management for internet of things using cloud computing and security in smart cities

Many consumers participate in the smart city via smart portable gadgets such as wearables, personal gadgets, mobile devices, or sensor systems. In the edge computation systems of IoT in the smart city, the fundamental difficulty of the sensor is to pick reliable participants. Since not all smart IoT gadgets are dedicated, certain intelligent IoT gadgets might destroy the networks or services deliberately and degrade the customer experience. A trust-based internet of things (TM-IoT) cloud computing method is proposed in this research. The problem is solved by choosing trustworthy partners to enhance the quality services of the IoT edging network in the Smart architectures. A smart device choice recommendation method based on the changing networks was developed. It applied the evolutionary concept of games to examine the reliability and durability of the technique of trust management presented in this article. The reliability and durability of the trustworthiness-managing system, the Lyapunov concept was applied.A real scenario for personal-health-control systems and air-qualitymonitoring and assessment in a smart city setting confirmed the efficiency of the confidence-management mechanism. Experiments have demonstrated that the methodology for trust administration suggested in this research plays a major part in promoting multi-intelligent gadget collaboration in the IoT edge computer system with an efficiency of 97%. It resists harmful threads against service suppliers more consistently and is ideal for the smart world's massive IoT edge computer system.

     

Data assimilation and multisource decision-making in systems biology based on unobtrusive Internet-of-Things devices

Biological and medical diagnoses depend on high-quality measurements. A wearable device based on Internet of Things (IoT) must be unobtrusive to the human body to encourage users to accept continuous monitoring. However, unobtrusive IoT devices are usually of low quality and unreliable because of the limitation of technology progress that has slowed down at high peak. Therefore, advanced inference techniques must be developed to address the limitations of IoT devices. This review proposes that IoT technology in biological and medical applications should be based on a new data assimilation process that fuses multiple data scales from several sources to provide diagnoses. Moreover, the required technologies are ready to support the desired disease diagnosis levels, such as hypothesis test, multiple evidence fusion, machine learning, data assimilation, and systems biology. Furthermore, cross-disciplinary integration has emerged with advancements in IoT. For example, the multiscale modeling of systems biology from proteins and cells to organs integrates current developments in biology, medicine, mathematics, engineering, artificial intelligence, and semiconductor technologies. Based on the monitoring objectives of IoT devices, researchers have gradually developed ambulant, wearable, noninvasive, unobtrusive, low-cost, and pervasive monitoring devices with data assimilation methods that can overcome the limitations of devices in terms of quality measurement. In the future, the novel features of data assimilation in systems biology and ubiquitous sensory development can describe patients’ physical conditions based on few but long-term measurements.     

Middleware-based multi-agent development environment for building and testing distributed intelligent systems

The spread of the Internet of Things (IoT) is demanding new, powerful architectures for handling the huge amounts of data produced by the IoT devices. In many scenarios, many existing isolated solutions applied to IoT devices use a set of rules to detect, report and mitigate malware activities or threats. This paper describes a development environment that allows the programming and debugging of such rule-based multi-agent solutions. The solution consists of the integration of a rule engine into the agent, the use of a specialized, wrapping agent class with a graphical user interface for programming and testing purposes, and a mechanism for the incremental composition of behaviors. Finally, a set of examples and a comparative study were accomplished to test the suitability and validity of the approach. The JADE multi-agent middleware has been used for the practical implementation of the approach.

     

High Power Magnetic Field Energy Harvesting through Amplified Magneto‐Mechanical Vibration

Internet of Things (IoT) is driving the development of new generation of sensors, communication components, and power sources. Ideally, IoT sensors and communication components are expected to be powered by sustainable energy source freely available in the environment. Here, a breakthrough in this direction is provided by demonstrating high output power energy harvesting from very low amplitude stray magnetic fields, which exist everywhere, through magnetoelectric (ME) coupled magneto‐mechano‐electric (MME) energy conversion. ME coupled MME harvester comprised of multiple layers of amorphous magnetostrictive material, piezoelectric macrofiber composite, and magnetic tip mass, interacts with an external magnetic field to generate electrical energy. Comprehensive experimental investigation and a theoretical model reveal that both the magnetic torque generated through magnetic loading and amplification of magneto‐mechanical vibration by ME coupling contributes toward the generation of high electrical power from the stray magnetic field around power cables of common home appliances. The generated electrical power from the harvester is sufficient for operating microsensors (gyro, temperature, and humidity sensing) and wireless data transmission systems. These results will facilitate the deployment of IoT devices in emerging intelligent infrastructures.     

Auto-scaling techniques for IoT-based cloud applications: a review

Cluster Computing - Cloud and IoT applications have inquiring effects that can strongly influence today’s ever-growing internet life along with necessity to resolve numerous challenges for...     

Research on sports training model based on intelligent data aggregation processing in internet of things

Cluster Computing - In order to improve the visual level of physical training and promote the optimization of sports training, the computer multimedia technology and Internet of things (IoT) are...     

A multi-layer trust-based middleware framework for handling interoperability issues in heterogeneous IOTs

Cluster Computing - Traditional wireless technologies have evolutionary converged to Internet of Thing (IoT) for devices and service interactions. In the past decade, the academia, industry 4.0 and...     

Multi-objective Task Scheduling in cloud-fog computing using goal programming approach

Cluster Computing - Fog Computing continues to extend its usage by solving cloud computing challenges about Internet of Things (IoT). Fog nodes as a processing resource, can perform tasks generated...     

Security framework for smart cyber infrastructure

Cluster Computing - The rapid deployment of the Internet of Things (IoT) devices have led to the development of innovative information services, unavailable a few years ago. To provide these...     

Lattice-based cryptosystems for the security of resource-constrained IoT devices in post-quantum world: a survey

Cluster Computing - The concept of the Internet of Things (IoT) arises due to the change in the characteristics and numbers of smart devices. Communication of things makes it important to ensure...     

IoTSteg: ensuring privacy and authenticity in internet of things networks using weighted pixels classification based image steganography

Cluster Computing - Internet of Things (IoT) networks are considered the great challenging by emerging technologies that try to solve the problems in modern life, while securing the information...     

A secure authentication technique for connecting different IoT devices in the smart city infrastructure

Cluster Computing - Recently the IoT technology is widely used in the field of smart cities, smart banking, and smart transportation system, etc. Various sensors can be installed in an open...