Cloud Integration Research Articles

Secure Communication of the Integrated IoT and Cloud Computing

One advanced technology that is expanding quickly in the communications area is the integration of Cloud computing with the IoT. This is because it is quick, easy, and inexpensive to use. Since the information sent between the sender and recipient is vulnerable to threats and attacks through eavesdropping or unauthorized, in this paper, encryption technology is used to protect the information that is sent from the intelligent building to the smartphone-controlled, where the information sent between the two parties is encrypted by relying on the Henon map, new diffusion technique and the XoR function. Several measures were used to measure the quality of the proposed system as Histogram, NPCR, PSNR, SSIM, QIU, MAE, and Entropy, as the results proved the strength, high-security effectiveness, and robustness of the proposed system.

Research to establish 3D model of mine industrial site area from terrestrial laser scanning and Unmanned aerial vehicle data

In recent years, three-dimensional (3D) models are being built in many fields including mining. These products are often used to develop a database of smart mines which in terms can be used in the management of production in underground coal mines. Unmanned aerial vehicle (UAV) and terrestrial laser scanning (TLS) technologies are known as the two main technologies that quickly and accurately collect 3D point cloud (PC) data. This article presents the integration of a 3D point cloud produced from UAV photos and TLS to build a detailed 3D model for the ground plant at the level of +35 m in the Nui Beo underground coal mine. To collect data, a DJI Phantom 4 Advanced drone was used to take photos in three modes: a shot angle of 900, a 3D grid with a 450 angle, and a circular flight orbit with 450 and 600 shooting angles. A Faro Focus3D X130 laser scanner was used for scanning the mine shaft’s tower to fill the missing point cloud of the UAV. The PC established by both methods was evaluated for accuracy based on the control points measured by a Leica TS09 total station, which was merged by the Iterative Closest Point (ICP) algorithm. The integrated PC met the accuracy requirement of establishing a 3D model of the study area with the level of detail 3 in the CityGML standard.

Prioritized scheduling technique for healthcare tasks in cloud computing

The Internet-of-things (IoT) plays a significant role in healthcare monitoring, where the IoT Cloud integration introduces many new opportunities for real-time remote monitoring of the patient. Task scheduling is one of the major challenges in cloud environment. Solving that problem reduces delay, missed tasks, and failure rate, and increases the guarantee ratio. This paper proposes a new task scheduling and allocation technique: Prioritized Sorted Task-Based Allocation (PSTBA) for healthcare monitoring implemented in IoT cloud-based architecture. The proposed technique selects the best virtual machine to execute the health task considering multiple factors such as; the wait time of the VM and the Expected processing time (EPT) of the task as well as its criticality. An extensive simulation study is conducted using the CloudSim simulator to evaluate the performance of the proposed technique. The proposed technique is compared to the Sorted Task-Based Allocation (STBA) and FCFS techniques and it reduces the delay by 13.7% and 80.2%, the failure rate by 21% and 37.5%, and increases the guarantee ratio by 2.2% and 4.5% compared to STBA and FCFS, respectively. In analyzing the critical health tasks, the proposed PSTBA has also reduced the critical health tasks missed ratio by 15.7% and 50.9% compared to STBA and FCFS, respectively. The simulation results demonstrate that PSTBA is more effective than the STBA and FCFS techniques in terms of delay, missed critical tasks, guarantee ratio, and failure rate.

Fog Computing and Blockchain-Based Security Service Architecture for 5G Industrial IoT-Enabled Cloud Manufacturing

Recent evolution of the industrial Internet of Things empowers the classical manufacturing model with cloud computing integration for Industry 4.0. Cloud integration advances the capabilities of manufacturing systems with cloud-based controlling and real-time process monitoring, which is renowned as cloud manufacturing (CM). However, cloud integration exposes the entire manufacturing ecosystem to a new set of security risks and increments in end-to-end latency. Moving security services toward the edge eradicates message routing latency toward the cloud and eliminates the central point of failure while leveraging the entire system’s performance. We propose a blockchain and fog-computing-enabled security service architecture that operates on fog nodes at the edge of manufacturing equipment clusters. The proposed service facilitates CM equipment authentication and equipment-cloud channel privacy protection while preserving anonymity and unlinkability over the blockchain. We implemented the proposed architecture with hyperledger fabric and compared the performance advantage over the state-of-the-art solutions.

Cloud Computing and Public Sector Transformation: Revolutionizing Governmental Services and Operations

This research delves into the transformative impact of cloud computing on public sector operations and services, examining its primary focus, methodology, key findings, and overall significance. The study employs a comprehensive analysis of government agencies' adoption of cloud technologies, emphasizing the shift towards efficient and agile service delivery. The methodology involves a combination of case studies, interviews with key stakeholders, and quantitative assessments to gauge the extent of cloud integration. Key findings underscore the substantial benefits accrued by governmental bodies through cloud adoption, including enhanced scalability, costeffectiveness, and improved data accessibility. The research elucidates the role of cloud computing in fostering innovation, streamlining bureaucratic processes, and optimizing resource allocation. Moreover, it investigates the challenges and potential risks associated with the migration to cloud-based platforms, providing a balanced perspective on the implications for security, privacy, and data governance. The significance of this research lies in its contribution to the broader discourse on public sector modernization. By illuminating the tangible advantages and potential pitfalls of cloud computing adoption, the study serves as a guide for policymakers, practitioners, and technology providers involved in governmental transformations. Ultimately, this research contends that cloud computing is a pivotal catalyst for reshaping public sector operations, facilitating a paradigm shift towards more responsive, citizen-centric, and efficient governance

A novel coupling cloud decision-making framework for investigating population-economy-water consumption nexus in the Inner Mongolia reaches of the Yellow River, China

Rapid urbanization, increased population and exacerbated water consumption, have been the huge challenges for the sustainable socio-economic development. Investigating the interaction of population-economy-water consumption (PEW) is important for promoting the regional high-quality development. PEW studies based on data with small sample sizes have inevitably uncertainties, especially in ecologically fragile areas. However, existing studies still fail to consider these uncertainties. To overcome the above shortcoming, this study proposed a coupling cloud integration algorithm (CCIA) drawing on the advantages of coupling coordination degree and cloud models. A novel coupling cloud decision-making framework combining CCIA and technique for order of preference by similarity to ideal solution (TOPSIS) model was developed to determine the coupling coordination level of PEW. The Inner Mongolia reaches of the Yellow River (IMYR), a typical ecologically fragile area, was served as the study area. Results showed that PEW nexus evolved from seriously uncoordinated development to barely coordinated development in IMYR. Cities with the seriously uncoordinated development disappeared, and cities with barely coordinated development increased by 71.43% from 2001 to 2020. Coupling coordination levels had remarkable spatial difference influenced by geographical features and ecological environment, showing that southeastern IMYR was higher than northwestern IMYR. Our findings highlight the insufficient ecological water consumptions have posed potential threats to the high-quality development in IMYR. Effective measures should be formulated to relieve its impact on IMYR, and promote sustainable development in ecologically fragile areas.

Efficiency of integration between sensor networks and clouds

Numerous wireless sensor networks (WSN) applications include monitoring and controlling various conditions in the environment, industry, healthcare, medicine, military affairs, agriculture, etc. The life of sensor nodes largely depends on the power supply type, communication ability, energy storage capacity and energy management mechanisms. The collection and transmission of sensor data streams from sensor nodes lead to the depletion of their energy. At the same time, the storage and processing of this data require significant hardware resources. Integration between clouds and sensor networks is an ideal solution to the limited computing power of sensor networks, data storage and processing. One of the main challenges facing systems engineers is to choose the appropriate protocol for integrating sensor data into the cloud structure, taking into account specific system requirements. This paper presents an experimental study on the effectiveness of integration between sensor networks and the cloud, implemented through three protocols HTTP, MQTT and MQTT-SN. A model for studying the integration of sensor network - Cloud with the communication models for integration - request-response and publish- subscribe, implemented with HTTP, MQTT and MQTT-SN. The influence of the number of transmitted data packets from physical sensors to the cloud on the transmitted data delay to the cloud, the CPU and memory load was studied. After evaluating the results of sensor network and cloud integration experiments, the MQTT protocol is the most efficient in terms of data rate and power consumption.

UAV and TLS point cloud integration for the surface plant infrastructure of underground coal mines

The surface plant infrastructure (SPI) of underground coal mines is one of important sets of underground mines as it includes essential objects, such as office buildings, structures and equipment used to load, receive, sort or process minerals; receive and discharge waste rocks; provide ventilation for tunnels and energy for mining operations. The measurement and collection of spatial data of SPI are important to ensure the safe and effective management and operation of mining activities in underground mines. A rapid development in geospatial technologies has facilitated the acquisition of geospatial data in the mining industry. Unmanned Aerial Vehicle (UAV) photogrammetry and Terrestrial Laser Scanning (TLS) are two of the typical geospatial technologies, which have made significant contributions to the field of geospatial data collection. While UAV photogrammetry allows to create dense point clouds with centimeter - level accuracy in a short time and large areas, TLS technology can produce dense point clouds with millimeter - level accuracy. However, the latter is time - consuming and expensive while performing on a large area. The integration of UAV and TLS data can be seen as a reasonable solution to gain the advantages of both and avoid the disadvantages of each technology. This paper presents the results of an integrated study of point cloud data generated by UAV and TLS for the plant infrastructure of the underground coal mine. Featuring structures in the study area include mineshaft tower, office and factory buildings. The results show that the UAV and TLS integrated point cloud data has millimeter - level accuracy for important objects such as mineshaft towers, while ancillary structures in the study area have centimeter - level accuracy.

On Computational Offloading in Massive MIMO-Enabled Next-Generation Mobile Edge Computing

Next-generation wireless communication networks are expected to support massive connectivity with high data rate, low power consumption, and computational latency. However, it can significantly enhance the existing network complexity, which results in high latency. To ease this situation, mobile edge cloud and massive multiple input and multiple output (MIMO) have recently emerged as the effective solutions. Mobile edge cloud has the ability to overcome the constraints of low power and finite computational resources in next-generation communication systems by allowing devices to offload their extensive computation to maximize the computation rate. On the other hand, MIMO can enhance network spectral efficiency by using large number of antenna elements. The integration of mobile edge cloud with massive MIMO also helps to increase the energy efficiency of the devices; as a result, more bits are computed with minimal energy consumption. In this work, a mathematical model is formulated by considering the devices’ energy constraint, which is nonconvex in nature. Following that, to overcome this, we transformed the original optimization problem using the first approximation method and solved the partial offloading schemes. Results reveal that the proposed scheme outperforms the others by considering computational rate as a performance matrix.

Integration of Cloud in Mobile Forensics

With emerging technology and the connection of electronic devices to the internet, Internet of Things (IoT) has become part of human life. From the development of smartphones to smartwatches and smart-homes, electronic devices now have the capability of performing human activities or aiding humans in performing activities such as turning hall lights on or off with their voice. Although a large number of people use these devices for the greater good, a few individuals or group of people hide behind these devices to perform malicious activities. In order to apprehend and prosecute perpetuators who hide behind smart devices for evil gains, forensic examinations or investigations must be conducted. This review aims to identify digital forensic challenges in IoT. The inclusion criteria for this paper were international journals, articles, conference papers and case studies published from 2019 to 2022. Thematic analysis was used to analyze and synthesis the literature. Three themes emerged from the analysis; automated compromised smart-home tracer; data volatility and reconstruction; IoT forensic investigation framework. This integrative review combines evidence of digital forensic challenges in diverse IoT devices. Keyword IoT forensics, IoT challenges, Digital forensics, Smart-home forensics.

Blockchain-Cloud Integration: A Survey.

Over the last couple of years, Blockchain technology has emerged as a game-changer for various industry domains, ranging from FinTech and the supply chain to healthcare and education, thereby enabling them to meet the competitive market demands and end-user requirements. Blockchain technology gained its popularity after the massive success of Bitcoin, of which it constitutes the backbone technology. While blockchain is still emerging and finding its foothold across domains, Cloud computing is comparatively well defined and established. Organizations such as Amazon, IBM, Google, and Microsoft have extensively invested in Cloud and continue to provide a plethora of related services to a wide range of customers. The pay-per-use policy and easy access to resources are some of the biggest advantages of Cloud, but it continues to face challenges like data security, compliance, interoperability, and data management. In this article, we present the advantages of integrating Cloud and blockchain technology along with applications of Blockchain-as-a-Service. The article presents itself with a detailed survey illustrating recent works combining the amalgamation of both technologies. The survey also talks about blockchain–cloud services being offered by existing Cloud Service providers.

Uses of IOT in Home Appliances

As they increase comfort and quality of life, IOT in Home Appliances have gained popularity in recent years. The bulk of smart home systems are controlled by smartphones and micro-controllers. A smartphone application is used to monitor and control house processes via wireless connection technologies. We explore the idea of a smart home with the integration of IoT services and cloud computing to it by embedding intelligence into sensors and actuators, networking smart things using corresponding technology, facilitating interactions with smart things using cloud computing for easy access in different locations, increasing computation power, storage space, and improving data exchange efficiency. In this chapter, we'll examine how the utilization of three different elements can serve as a strong foundation for an advanced smart home concept and its actualization.

Cloud Based Irrigation System with IoT and Machine Learning

There is a growing demand for electrical energy requirements in India. Nowadays, people tend to maintain home gardens, Terrace farms, and Mini farms. This Maintenance growth has been possible because of a timely and adequate supply of water. The irrigation depends on the groundwater availability, but as per the census of 2017, the groundwater levels have dropped down by 61% from 2007. Therefore, water usage with effective power consumption is of at most importance. Despite their desire to maintain, people take a step back, owing to time constraints, their busy lives, and the unavailability of a person to look after farms. Hence, the Internet of Things (IoT) and Machine Learning (ML) based smart irrigation system with Cloud integration is employed to address the farms. The system forecasts using SVM and reports graphically, the irrigation requirement of the field using several environmental parameters along with weather forecasting that assists the growth of the crops with the effective use of water and power conserving initiatives is presented in this paper.

A Secure Interoperable API Wrapper Tunnel for Integration of GIS-Based ICS-IIoT and Digital Twins in Industry 4.0 Clouds

Industry 4.0 is the most disruptive revolution engulfing all the digital transformation from sensors nodes to cloud applications. A sustainable and secure Industry 4.0 ecosystem is a core challenge for stakeholders and state agencies addressed in this work by layered API tunnel interoperability instead of conventional cybersecurity methods and techniques. In this work, an interoperable application programmer interface (API) wrapper is being proposed to manage heterogeneous cloud architectures using Eucalyptus, Apache CloudStack, and OpenNebula. A comprehensive design and implementation plan from things layer to user interface has been accomplished in this work. Infrastructure as a Service (IaaS) is being automated using Ansible from Web Servers Layers through Common Gateway Interface (CGI) scripting. The Web Servers are being managed using WebSockets by micro–Web Servers Gateway Interface (uWSGI) from cloudstack managers (CSM) API. The Platform as a Service (PaaS) for big data, web servers, and machine learning platforms is accomplished using uWSGI from CSM. The public and private clouds are being managed using individual APIs. The wrapper, proposed in this work enables the big challenge of Industry 4.0 for realizing interoperability, scalability, heterogeneity, and automated cloud integration by functioning at the Software as a Service (SaaS) Layer.

Industry 4.0 in Action: Digitalisation of a Continuous Process Manufacturing for Formulated Products

The pharmaceutical industry is going through a significant change to adopt smart manufacturing for more integrated supply chains and improved sustainability. Today's competitive market demands have put pressure on healthcare systems to take a comprehensive assessment of the drug life cycle, its environmental effect, industrial use of energy and resources, supply chain, and impact on end-users. The exploitation of emerging Industry 4.0 technologies will allow a sustainable process design and personalised health care system through the realisation of digital twins, which could transform the pharmaceutical sector to be more flexible, robust, adaptive, and smart. A significant level of research and development has been applied to pharmaceutical manufacturing especially in existing, outdated design and scale-up paradigms in isolated unit operations. However, addressing the key challenges in pharmaceutical manufacturing requires whole systems approaches to incorporate Industry 4.0 concepts.This paper aims to share the latest development of an advanced digital twin of a continuous wet granulation and tableting process at The University of Sheffield. These include the delivery of a digital platform consisting of an Advanced Process Control system (APC), mechanistic model platform and industrial IoT platform for data analytics and visualisation. The combined solution aligns with the concepts of Industry 4.0 by providing a digital twin, cloud integration, sophisticated statistical, as well as hybrid and mechanistic models. The models are in turn, used for soft-sensors, Model Predictive Control and Optimisation algorithms to predict and control product Quality Attributes. The potential application of digital twins in the pharmaceutical industry will also be explored.

Robust 4-D Hyperchaotic DNA Framework for Medical Image Encryption

With the integration of cloud computing approaches in the healthcare systems, medical images are now processed and stored remotely on third-party servers. For such digital medical image data, privacy, protection, and security must be maintained by using image encryption methods. The aim of this paper is to design and apply a robust medical encryption framework to enhance the protection of medical image transformation and the patient information confidentiality. The proposed Framework encrypt the digital medical images using DNA computation and hyperchaotic RKF-45 random sequence approach. For which, the DNA computation is enhanced by applying hyperchaoticRKF-45 random key to the different Framework phases. The simulation results on different medical images were measured with various security analyses to prove the proposed framework randomness and coherent. Simulation results showed the ability of the hyperchaotic DNA encryption framework to withstand multiple electronic attacks with high performance compared to its counterparts of encryption algorithms. Finally, simulation and comparative studies have shown that, the proposed cryptography framework reported UACI and NPCR values 33.327 and 99.603 respectively, which are near to the theoretical optimal value.

Multi-layer encryption algorithm for data integrity in cloud computing

The Internet revolution has changed all aspects of our life, accessing and surfing the Internet is becoming as necessity in our life to obtain any kind of information needed, that produces a huge quantity of data available any time, any where. The greater the facilities, less our data privacy. For that maintaining data confidentiality and integrity in the Internet and cloud world is a primary requirement to continue working and using these facilities. In this paper, we propose a security mechanism that makes accessing the data from unauthorized persons more complex. Our mechanism easy to implement and understand but is complex to decrypt because it works in three levels in each level is used a new encryption key generated randomly and in each level is used a different encryption algorithm. Our results show that the encryption/decryption process time is increased linearly with the text size for the authorized persons and is increased exponentially for unauthorized persons.

Evaluation of a policy enforcement solution in telemedicine with offline use cases

Abstract The emerging popularity of telemedicine solutions brought an alarming problem due to the lack of proper access control solutions. With the inclusion of multi-tiered, heterogeneous infrastructures containing Internet of things and edge computing elements, the severity and complexity of the problem became even more alarming, calling for an established access control framework and methodology. The goal of the research is to define a possible solution with a focus on native cloud integration, possible deployment at multiple points along the path of the healthcare data, and adaptation of the fast healthcare interoperability resources standard. In this paper, the importance of this issue in offline use cases is presented and the effectiveness of the proposed solution is evaluated.

Developing a Smart Irrigation System Incorporating Cloud Integration and IOT Technology.

Developing a Smart Irrigation System Incorporating Cloud Integration and IOT Technology.

A HYBRID POINT CLOUD REALITY CAPTURE FROM TERRESTRIAL LASER SCANNING AND UAV-PHOTOGRAMMETRY

Abstract. Point clouds are a digital representation of physical objects or buildings that exist in real world. There are many sources that a point cloud can come from such as a terrestrial laser scanner (TLS) or an unmanned aerial vehicle (UAV). This paper presents a simple method of integrating point clouds from two (2) data sources; TLS and UAV using simple alignment of rigid body transformation method known as Point Pair Picking (PPP). The point cloud data are the representation of details of a one-story building located in Johor Bahru, Malaysia. The process of aligning two (2) separate clouds into one (1) dataset requires initial processing such as noise removal before the alignment process was started. A laser (LAS) formatted data were formed so that it compatible with the PPP process. As the result, a high dense hybrid cloud-model was produced covering complete details of the building. This shows that integration of point clouds could improve 3D documentation assessment such as Building Information Modelling (BIM) by contributing richer semantic information.