Distributed ledgers are common in the industry. Some of them can use blockchains as their underlying infrastructure. A blockchain requires participants to agree on its contents. This can be achieved via a consensus protocol. How do these protocols differ in performance, and how are the differences affected by the communication network? Moreover, such a protocol would need a timer to ensure progress, but how should the timer be set? This article presents an analytical model to address these and related issues when there are crash faults. Specifically, it focuses on two consensus protocols (Istanbul BFT and HotStuff) and two network topologies (Folded-Clos and Dragonfly). The model provides formulas that express the consensus time in terms of protocol and topology parameters. No other model in the literature provides such a global view of the parameter space. Analysis of the closed-form expressions yield new insights into how the timers should be set, how faults affect the consensus time, when one protocol is faster than the other, and how the two topologies differ in their impact. The formulas and analyses are validated with simulations. The conclusion also offers some tips for the analytical modeling of similar protocols.
Cloud computing is popular in modern businesses because it is scalable, versatile, and cost-effective. Due to the spread and complexity of cloud infrastructures, fault tolerance is crucial. This research focuses on improved cloud failure tolerance using Distributed Ledger Technology (DLT). Decentralised and immutable DLT offers verifiable and transparent transaction history, data consistency, and decentralised recovery, promising to improve cloud infrastructure stability and robustness. This study examines how DLT improves cloud-based detection, recovery, and fault tolerance. Using blockchain and cloud services to create a fault-tolerant system is novel. Comparison of fault tolerance solutions in existing cloud settings with DLT integration is the plan. Data was obtained during failure testing simulations using genuine cloud infrastructure platforms and blockchain networks. Recovery time, defect detection, energy utilisation, and uptime were measured. Graphviz was used to create flowcharts, and Matplotlib was utilised for graphs and plots. Test results show improved fault tolerance due to lower fault impact and faster recovery from DLT. DLT can make cloud systems more fault-tolerant and resilient, setting the pace for distributed computing innovation, the research concludes.
Blockchain-empowered end-edge collaborative computing is a promising technology for enhancing the timeliness and trustworthiness of Industrial Internet of Things (IIoT). However, integrating task offloading with blockchain consensus inevitably escalates resource consumption across communication, computation, and energy domains. Thus, the joint optimization of task offloading, resource allocation and blockchain consensus is very important for IIoT. This paper studies a general end-edge collaborative computing scenario with multiple end devices and multiple edge servers. We first propose a novel dynamic blockchain (DBC) scheme by developing a dynamic leader election mechanism and designing a dynamic consensus waiting time window. Then, by fully considering the constraints of multi-task size and deadline, communication bandwidth, computing frequency, battery capacity, Byzantine fault tolerant and trustworthiness, we formulate the trustworthy processing efficiency (TPE) maximization problem with respect to end-edge task division, communication and computation resource allocation, leader election and consensus waiting window. To address this problem, we transform it into a Markov decision process and design a compound reward by fully considering the penalty for computing timeout and consensus failure. After that, we propose a rotating multi-agent deep reinforcement learning (R-MADRL) algorithm tailored to the proposed DBC scheme, where an entropy-based dual-critic DRL algorithm is proposed for rotating multi-agent training and decentralized execution. Extensive experiments validate the effectiveness and superiority of the proposed DBC with R-MADRL, where three benchmark DRL algorithms and three blockchain consensus schemes are compared. The results demonstrate that R-MADRL achieves stable convergence with more than 60.32% TPE reward than other algorithms while the task timeout ratio of DBC is reduced by more than 66.49% compared with other schemes.
This publication presents a novel cryptographic commit scheme named DFTWS which is used to enable deterministic, fair, and transparent winner selection in an open source Proof-of-Useful-Work blockchain for High Energy Physics (HEP) called gophy. In gophy, instead of spamming hashing operations to mine blocks, miners are running computationally expensive Monte Carlo simulations to support a real-world HEP experiment with necessary data required to conduct the experiment. To preserve the usefulness property, block problems are defined over time by a Root Authority which is coordinated by a representative of a real-world HEP experiment. In order to be able to provide a transparent mechanism that allows for fair block winner selection from a list of eligible miners that solved a block problem, DFTWS is employed to achieve consensus between nodes. A strength of this approach is that every node is able to verify the fairness of the winner selection process. This publication provides an in-depth description and theoretical fairness analysis of DFTWS, a practical evaluation of its performance under real-world conditions and considerations of potential bottlenecks that can potentially occur as the node network scales. It also discusses a deployment strategy for using DFTWS on top of existing blockchain infrastructure like the Ethereum network. Additionally, theoretical performance aspects of DFTWS are compared with various state-of-the-art cryptographic commitment schemes and Zero-Knowledge Proof systems.
H.C. Zhang, Shike Li, Shike Li, Hang Bao · 6 authors
The rapid development of blockchain technology has driven the widespread application of decentralized applications (DApps) across various fields. However, DApps cannot directly access external data and rely on oracles to interact with off-chain data. As a bridge between blockchain and external data sources, oracles pose potential risks of malicious behavior, which may inject incorrect or harmful data, leading to trust and security issues. Additionally, with the surge in data requests, the disparity in oracle trustworthiness and costs has increased, making the dynamic selection of the most suitable oracle for each request a critical challenge. To address these issues, this paper proposes a Trust-Aware and Cost-Optimized Blockchain Oracle Selection Model with Deep Reinforcement Learning (TCO-DRL). The model incorporates a comprehensive trust management mechanism to evaluate oracle reputation from multiple dimensions and employs an improved sliding time window to monitor reputation changes in real time, enhancing resistance to malicious attacks. Moreover, TCO-DRL uses deep reinforcement learning algorithms to dynamically adapt to fluctuations in oracle reputation, ensuring the selection of high-reputation oracles while optimizing node selection, thereby reducing costs without compromising data quality. We implemented and validated TCO- DRL on Ethereum. Experimental results show that, compared to existing methods, TCO-DRL reduces the allocation rate to malicious oracles by more than 39.10% and saves over 12.00% in costs. Furthermore, simulated experiments on various malicious attacks further validate the robustness and effectiveness of TCO-DRL
The rapid growth of IoT has increased the demand for large-scale data processing. However, traditional centralized methods struggle with real-time requirements and data security . This paper introduces VCD-TSNet, a novel real-time IoT data processing framework that combines blockchain and edge computing . By integrating deep learning models like VGG, ConvLSTM , and DNN , VCD-TSNet effectively performs spatial feature extraction, temporal modeling , and decision-making, while using blockchain to ensure data integrity and privacy. Experimental results demonstrate that VCD-TSNet outperforms baseline models in classification accuracy , prediction precision, and real-time performance. For instance, on the BoT-IoT dataset, the classification accuracy reaches 97.5%, throughput increases to 920 TPS, and response time stays below 85 ms. This study validates the model’s effectiveness and highlights its potential in large-scale IoT environments, offering efficient, secure solutions for real-time data processing. It also provides insights for future improvements in frameworks that combine edge computing with blockchain.
This article presents a comprehensive framework for integrating blockchain technology with Oracle SOA Suite to facilitate secure and efficient real-time financial transactions. The proposed architecture leverages distributed ledger technology's inherent security features alongside Oracle's robust service orchestration capabilities to address prevalent challenges in traditional payment systems. Through systematic implementation and rigorous testing, the article demonstrates significant improvements in transaction processing speed, security, and regulatory compliance. The integration framework incorporates smart contracts for automated transaction validation, enhanced payment messaging protocols, and optimized data processing pipelines. The article indicates that this hybrid architecture effectively reduces transaction settlement times while maintaining data integrity and meeting industry regulatory requirements. The article contributes to the growing body of knowledge in enterprise integration architecture and provides valuable insights for financial institutions seeking to modernize their transaction processing systems.
This article presents a novel framework for implementing decentralized identity management in microservices architecture using blockchain technology. The proposed solution addresses the inherent challenges of traditional centralized identity management systems by leveraging distributed ledger technology and smart contracts to create a secure, transparent, and user-centric authentication mechanism. The framework incorporates comprehensive privacy controls and consent management features while ensuring compliance with regulatory requirements across various industries. Through extensive evaluation across multiple use cases in healthcare, financial services, and government sectors, the results demonstrate enhanced security, improved scalability, and better user privacy control compared to conventional approaches. The article suggests that blockchain-based identity management can significantly reduce the risk of security breaches while providing a more robust and flexible authentication mechanism for modern distributed systems. This article contributes to the growing body of knowledge in distributed systems security and provides practical insights for organizations looking to implement decentralized identity management solutions.
Nabil A. Ismail, Shaimaa Abu Khadra, Gamal Attiya, Salah Eldin S. E. Abdulrahman
Abstract Blockchain technology offers a robust framework for integration with the Internet of Things (IoT), enhancing interoperability, security, privacy, and scalability in modern technological ecosystems. However, traditional cryptographic protocols used in blockchain systems are increasingly vulnerable to quantum attacks due to advancements in quantum computing. In response, the National Institute of Standards and Technology (NIST) has prioritized research in post-quantum cryptography, presenting challenges and opportunities for developing blockchain-based applications tailored to IoT devices. Among the post-quantum cryptographic schemes evaluated in NIST's third standardization round, the Supersingular Isogeny Key Encapsulation (SIKE) protocol stands out for its relatively small public and private key sizes. Despite this advantage, SIKE faces challenges related to high latency, necessitating efficient implementations to make it viable for real-world applications. This research focuses on optimizing the cryptographic foundations of blockchain networks to securely and efficiently integrate resource-constrained IoT ecosystems. By enhancing the SIKE protocol, which exhibits strong resistance to brute-force and whitewashing attacks, the study achieves significant performance improvements. Our FPGA-based implementation on the VIRTEX-6 XC6VLX760 demonstrates reduced latency, achieving a key generation time of 24 ms, encapsulation time of 72 ms, and decapsulation time of 73 ms for SIKEp434. These results highlight the feasibility of deploying SIKE-optimized blockchain networks in IoT environments with stringent resource constraints.
The increasing adoption of multi-cloud database systems has transformed enterprise data management, enabling enhanced scalability, reliability, and cost efficiency.However, managing databases across multiple cloud providers introduces significant challenges, including data fragmentation, latency, security vulnerabilities, and inconsistencies in synchronization.Traditional approaches to database management struggle to provide seamless interoperability, fault tolerance, and resilience against failures, necessitating innovative architectural solutions.This paper explores the design and implementation of resilient multicloud database systems, integrating Distributed Ledger Technology (DLT) for enhanced data integrity, fault tolerance mechanisms to ensure high availability, and cross-platform synchronization techniques for maintaining consistency across heterogeneous cloud environments.DLT, particularly blockchain, offers a decentralized approach to data validation, reducing the risk of tampering and unauthorized modifications while enabling transparent and auditable transactions.Fault tolerance strategies, including redundancy, self-healing systems, and predictive analytics, play a crucial role in mitigating system failures and ensuring business continuity.Additionally, cross-platform synchronization mechanisms, such as conflict-free replicated data types (CRDTs) and real-time consistency protocols, are explored to address latency and data consistency challenges across cloud infrastructures.By integrating these technologies, organizations can enhance the resilience, security, and operational efficiency of multi-cloud database architectures.This paper provides a comprehensive framework for implementing adaptive database management solutions, leveraging AI-driven automation, blockchain-based security, and advanced fault recovery models.The findings highlight best practices for enterprises aiming to achieve scalable, reliable, and fault-tolerant multi-cloud database environments.Future research directions include the role of edge computing in multi-cloud synchronization, quantum-safe cryptographic techniques for DLT security, and AI-driven predictive failure management in cloud-native databases.
Aiming to address the shortcomings of traditional blockchain technologies, characterized by high storage redundancy and low transaction query efficiency, we propose a lightweight sender-based blockchain architecture (LSB). In this architecture, the linkage between blocks is associated with the user initiating the transaction, and the hash of the newly generated block is recorded in the user’s wallet, thereby facilitating transaction retrieval. Each user node must store only the blocks that pertain to it, significantly reducing storage costs. To ensure the normal operation of the system, the Delegated Proof of Stake based on Reputation and PBFT (RP-DPoS) consensus algorithm is employed, establishing a reputation model to select honest and reliable nodes for consensus participation while utilizing the Practical Byzantine Fault Tolerance (PBFT) algorithm to verify blocks. The experimental results demonstrate that LSB reduces storage overhead while enhancing the efficiency of querying and verifying transactions. Moreover, in terms of security, it decreases the likelihood of malicious nodes being designated as agent nodes, thereby increasing the chances of honest nodes being selected for consensus participation.
This paper proposes a method of emulation of \verb|OP_RAND| opcode on Bitcoin through a trustless interactive game between transaction counterparties. The game result is probabilistic and doesn't allow any party to cheat, increasing their chance of winning on any protocol step. The protocol can be organized in a way unrecognizable to any external party and doesn't require some specific scripts or Bitcoin protocol updates. We will show how the protocol works on the simple \textbf{Thimbles Game} and provide some initial thoughts about approaches and applications that can use the mentioned approach.
Blockchain-enabled Policy Decision Point (PDP) has been a promising solution to the centralization concern in practical deployment of Attribute-Based Access Control (ABAC). However, existing blockchain systems cannot support PDP adequately since PDP functionalities introduce extra latency to blockchain’s execution process and limits system throughput. This paper proposes an efficient PDP Blockchain (PDPB) by exploiting a minimum-redundancy execution paradigm. Concretely, we design a novel Echo-Based Execution Conclude (EBEC) mechanism to enable minimum redundancy request evaluation while ensure blockchain safety and liveness. Two optimization techniques, Echo Compacting (EC) and Load Balancing (LB), are proposed to reduce the communication and computation overhead of PDPB and further enhance its performance. We implement a prototype of PDPB and evaluate it on Amazon Web Services (AWS) servers. The results show that PDPB achieves more than 35.6% performance improvement over existing methods.
Bitcoin constructs temporal order internally rather than synchronizing to any external clock. Empirical evidence shows that its time evolution is non-continuous, probabilistic, and self-regulated. Block discovery follows a stochastic process in which uncertainty accumulates during the search phase and collapses abruptly when a valid proof-of-work solution appears. Difficulty adjustment maintains the system near the entropy-maximizing regime and allows the network to infer the underlying global hash rate. Building on these observations, we present a unified framework in which Bitcoin time emerges from four interacting mechanisms: proof of work as a distributed entropy source, difficulty adjustment as temporal feedback, entropy collapse as discrete temporal updates, and recursive sealing through hash pointers. Together these mechanisms form a self-regulating temporal architecture that transforms distributed randomness into a coherent and irreversible global timeline, offering a generalizable foundation for autonomous timekeeping in permissionless systems.
The InterPlanetary File System (IPFS) offers decentralized storage and data sharing, which are critical for the functionality of Blockchain of Things (BCoT) systems. Despite its advantages, IPFS faces challenges such as scalability, latency, and resource management issues that hinder its effective integration into existing blockchain infrastructures. This study explores the implementation of Docker containerization to enhance IPFS performance within BCoT environments. An experimental testbed was established, comprising an IPFS node and an IPFS Cluster peer deployed as Docker containers, to evaluate the latency of file operations across various sizes and analyze containerization’s impact on data storage and retrieval efficiency. The proposed Dockerized IPFS implementation demonstrates substantial performance improvements over traditional systems, achieving latency reductions of up to 75% for small files (1–256 KB) and a three-fold decrease for larger files (64 MB). Specifically, write operations were reduced from 1000 ms to 300 ms, while read operations improved by 40%, decreasing from 2500 ms to 1500 ms. Additionally, the containerized approach yielded lower latency than previous standalone IPFS deployments. The study emphasizes the significance of dynamic resource allocation in optimizing resource utilization, thereby enhancing the overall performance of IPFS Clusters within BCoT frameworks. By leveraging Dockerized IPFS, BCoT systems can achieve more efficient off-chain storage solutions, facilitating improved data management and interoperability in decentralized applications.
Muhammad Medhat Kamal, Saad M. Darwish, Adel A. El-Zoghabi
The rapid growth of blockchain-based applications (BoS) has transformed multiple sectors but also brought significant challenges in software testing, particularly for decentralized applications (DApps) and smart contracts. Current development tools primarily support unit testing and do not address the full range of testing needs for blockchain software. Given the complexity of DApps and the immutability of smart contracts, more advanced methods are required to ensure security, performance, and functional accuracy. This study reviews the current state of blockchain software testing, identifying major gaps and limitations in conventional testing frameworks. To address these challenges, we propose an innovative software testing framework that integrates machine learning to offer real-time, customized testing recommendations for blockchain applications. By utilizing key blockchain features, including distributed ledgers, cryptographic hashing, and decentralized consensus, our model enhances testing accuracy by identifying potential vulnerabilities, performance limitations, and functional discrepancies, reducing the risk of undetected defects in the immutable blockchain environment. Experimental assessments show substantial improvements in testing coverage when compared to established tools such as Truffle and Remix, particularly in the validation of smart contracts and identification of security vulnerabilities. Our framework accelerates the testing process and improves the reliability of blockchain applications by providing developers with comprehensive tools to address the unique challenges of decentralized systems. As blockchain continues to advance in sectors like finance, healthcare, and supply chain management, this study highlights the urgent need for sophisticated testing methods and establishes a foundation for future advancements. By combining machine learning with blockchain testing, we introduce a scalable and adaptable approach that can progress alongside developments in blockchain technology. The conclusion explores broader implications and suggests further improvements, including integration into active deployment pipelines and real-time testing in operational settings. This framework marks a significant advancement in ensuring the dependability, security, and scalability of decentralized blockchain applications, supporting the sustainable growth of these systems in the digital ecosystem.
Hybrid cloud solutions are increasingly being adopted across industries to address diverse business needs, offering a blend of public and private cloud capabilities. In healthcare, hybrid clouds enable secure data sharing and compliance with regulatory standards. In finance, they provide flexibility for scaling operations while maintaining sensitive data in private environments. Retailers use hybrid clouds for improved customer experiences, leveraging the scalability of public clouds during peak times. This abstract explores various use cases across sectors, highlighting how hybrid cloud models enhance agility, optimize costs, and ensure security, driving digital transformation and innovation across industries. Keywords Hybrid Cloud, Cloud Use Cases, Healthcare, Finance, Retail, Cloud Scalability, Data Security, Digital Transformation, Cost Optimization, Agility, Cloud Flexibility, Regulatory Compliance, Customer Experience, Cloud Integration, Cloud Solutions, Industry Applications, Innovation, Cloud Adoption. 6.1. Introduction Cloud computing has become the norm for dynamic business infrastructures, replacing in-house architectures. Various services offered online allow companies to be more financially flexible and enable automatic updates and access to the latest technology. Many cloud providers collaborate to create a large number of fully equipped data centers, delivering data and applications through the internet. Furthermore, its adoption by industry has been increasing at a consistent pace. With improving technology in current infrastructure as well as the know-how on cloud computing, a lot of well-established corporations have been experimenting and migrating parts of their businesses. Nonetheless, some of the more sensitive data or processes are still kept internal (Syed, 2021). To support such strategic moves, the concept of hybrid cloud computing was proposed. It is a fusion of joint public and private cloud environments that remain unique entities yet are bound together by standardized or in-house technology, enabling data and application portability. Simply put, the public cloud is used for resources that are based on shared models, while the private cloud is referred to as resources and services that are managed internally. Together, they create a collaborative setup, enhancing internal flexibility and scalability, increasing the overall network performance for the company. As the business landscape undergoes rapid changes, the use of cloud technology is embraced as a method to adapt various business models. With this setup, companies are able to control critical processes internally, while sharing conventional solutions with the external providers, thus forecasting the use and manipulation of larger datasets with increased scalability. Such transitions are especially crucial in the Healthcare industry, where new regulations are mandating an extensive amount of data acquisition. Fig 6.1: Hybrid cloud use cases 6.1.1. Background of Hybrid Cloud Computing Hybrid cloud computing offers enterprises a flexible environment that combines the safety and reliability of private cloud with the scalability of public cloud. There are many definitions but, in general, hybrid cloud computing can be defined as a combination of at least one private and one public cloud that maintains at least one connection between them. Hybrid clouds can be designed in such a way such that the connection can be established via public networks, or more directly, via provider-to-provider connection. There have been considerable technological improvements that can facilitate the creation and management of hybrid clouds (Syed et al., 2021). The growing popularity and maturity of virtual machines or, more modern, containers, has led many production systems to operate on this paradigm. It has enabled better resource management, more flexible environment creation, and faster replica deployment. As more and more companies operate in the cloud, there is always a need for continuous and rapid development of solutions, either increasing the competitiveness of their own products or cutting production costs. Moreover, as the modern market is very volatile and the needs can change rapidly, achieving flexibility and scalability of the environment is often crucial for businesses to rapidly react to sudden changes. Businesses need an environment that can be dynamically extended to adapt to fluctuating workloads. 6.1.2. Significance of Studying Hybrid Cloud Use Cases Across Industries Outlined that cloud computing represents a novel paradigm in the way IT service provision relations exist, and various organisations are seeking ways to implement this technology. The question of how to store and process data is central to contemporary information processing. Cloud computing offers various services that provide protection and the ability to build applications on a large scale, store and process data. Handling computational jobs quickly and packaging those tasks for later use is a challenging task for many engineers (Danda, 2023). Rapid Storage Search For efficiency reasons, large table files used in a variety of computer tasks. At the center of the public cloud is IaaS. Generally, the public cloud is dominated by service from data center providers. From the perspective of research in cloud computing, much of what the industry is seeking focuses on the practices and patterns involved with end users of cloud services. Thus, the institution-based resource choices of mandates and laws will predict how, what, and from where a company will choose services, though this aspect is marginalized in available cloud research literature. 6.2. Hybrid Cloud Use Cases in Healthcare Industry As the information technology sector continues to grow and evolve, cloud computing is progressively thriving due to its elasticity, scalability, high availability, and opportunity for cost reduction. Hybrid Cloud Computing is considered a disruptive innovation which has changed the mindset of enterprises and how they utilize cloud computing models. Consequently, a growing body of organizations employ a mix of public and private clouds creating a hybrid cloud model. It has been adopted by various business domains including finance, government, e-commerce, telecommunications, and education to cope with Big Data. In the context of the information and technology industry, it improves business processes through automation, simplifies resource management, increases utilization of data storage, and makes data accessible from anywhere. Furthermore, cloud technology plays a significant role in the operational processes of applications and in preserving historical records essential to conducting audits. Similarly, public cloud likewise allows enterprises to execute applications efficiently through off-site resources stored in data centers. It is able to significantly expand the existing capabilities of a traditional data infrastructure, developing new competencies and services, and supplying a modular architecture permitting the integration of technologies. It is obvious that cloud technologies are perceived by the healthcare industry as a promising platform to store, access, and process Big Data, preserving health records, images and other sensitive information in a mode that permits quick access by authorized personnel or through personal devices (Syed, 2019). Many hospitals, medical universities, and shared diagnostic centers have executed cloud-based services. The enforcement of cloud computing by these healthcare institutions has resulted in the substantial employment in medical record storage and management, deployment of medical imaging processing services, telemedicine services and enhanced operational processes that facilitate diagnostics. As of today, the sharing of electronic health records (EHR) has been modernized with various cloud-enabled applications which can be entirely integrated across a common network and server infrastructure. Major hospitals and health institutions offer a variety of telemedicine services that can be tied, through cloud service providers, to personal healthcare devices. Equation 1: Healthcare: Data Storage and Compliance 6.2.1. Electronic Health Records (EHR) Management Electronic Health Records (EHR) Management The storage and management of EHR play a very important role on the research efficiency and medical quality for the whole network hospitals system. The cloud computing provides an efficient and easy way where the EHR can be easily accessed by authenticated medical personnel among these hospitals, or the different district diagnostic or treatment can be easily worked by the local district health professional to finish the snapshot of a different qualified treatment. In recent years, the secure EHR cloud storage and management system was developed for the Northwest Chinese hospital, which is the largest regional hospital with 3626 beds. To receive all the necessary treatment, patients of severe injuries usually transfer among the local district hospitals, regional hospitals and the local health service center to ensure consistent treatments, and vice versa, for the patient needs continuous postoperative cure (Syed et al., 2020). The cloud storage provides an eager way where the pertinent patient situational materials can be easily accessed by the authenticated treatment hospitals. It is why this “cloud-interlinked” hospital sequence EHR storage and management system was developed. Based on the specific patient identity, the regional or local diagnosing treatment hospital can upload or download the EHR of the treated treatment or the received previous treatments, with the restriction given the treatment time window. Rapid diagnoses and cuts to a clear-sighted target treatment can be immediately viewed or refined based on the necessary B-style examination reports made by the local hospitals. The EHR storage and management system in the cloud was developed by the “Northwest Patient EHR hospital-tied cloud storage system,” which is supported by the Azure cloud service. 6.2.2. Telemedicine Services The role of hybrid cloud computing in telemedicine services has been the recent subject of much attention and conversation among healthcare professionals, government officials, and academics. As a remote management service, telemedicine seeks to utilise emerging technologies for the exchange or communication of required task information in order to provide medical services from within a healthcare facility to a patient based elsewhere. Hybrid cloud technology has rapidly transformed such services, providing unprecedented potential to both the existing services to operate in real-time monitoring and analysis of multitudes of data, and, to those without access to medical care facilities, in receiving services from remote healthcare professionals. Fig : Global Hybrid Cloud Trends Report 6.3. Hybrid Cloud Use Cases in Finance Industry Financial Services Industry companies are known for being highly complex, with large financial institutions often trading in multiple asset classes around the world every day. With the ever-changing market conditions, these companies are in a constant battle to stay ahead. Fraud is an ongoing but ever-evolving issue for financial institutions large and small, with losses from fraud increasing year-after-year (Tulasi et al., 2022). As companies get more data seemingly newer trends of fraud emerge, requiring more knowledge workers to identify potentially fraudulent trends as they emerge. Additionally, in the financial services industry we have some of the most strict regulatory requirements – such as real-time surveillance – that a Financial Services provider must adhere to. Isolating rogue traders, identifying rogue trading and market makers, enforcing position limits and best execution are just a few examples of challenges that financial industries face under Dodd-Frank regulation. Fig 6.2: Hybrid Cloud Use Cases 6.3.1. Risk Management and Compliance Hybrid cloud computing plays a significant role in managing risk effectively in the finance sector and ensuring regulatory compliance. As the pandemic has demonstrated, the finance sector is highly vulnerable to exogenous shocks because institutions are prone to failures and get easily interconnected. in the finance industry, must be made based on real-time information to et al., 2022). 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Mohammad A. Altahat, Tariq Daradkeh, Anjali Agarwal
Abstract Efficiently managing virtual resources in the cloud is crucial for successful recourse utilization. Scheduling is a vital technique used to manage Virtual Machines (VMs), enabling placement and migration between hosts located in the same or different data centers. Effective scheduling not only ensures better server consolidation but also enhances hardware utilization and reduces power consumption in data centers. However, scheduling VMs across a Wide Area Network (WAN) poses considerable challenges due to connectivity issues, slower communication speeds, and concerns around data integrity and confidentiality. To enable informed scheduling decisions, it is critical to facilitate the exchange of real-time and accurate status information between cloud data centers, ensuring optimal resource allocation and minimizing latency. To address this, we propose a novel distributed cloud management solution that utilizes blockchain technology to facilitate efficient sharing of VM characteristics across multiple data centers. BigchainDB platform has been used as a blockchain-based ledger database to effectively share information required for VM scheduling and migration across different data centers. The proposed framework has been validated and compared with a Virtual Private Network (VPN)-based centralized management solution. The proposed model utilizing blockchain-based solution achieves 41.79% to 49.85% reduction in number of communication messages and 2% to 12% decrease in total communication delay comparing to the centralized model.
Lingxiao Yang, Xuewen Dong, Zhiguo Wan, Di Lu · 6 authors
As the foundation of the Web3 trust system, blockchain technology faces increasing demands for scalability. Sharding emerges as a promising solution, but it struggles to handle highly concurrent cross-shard transactions (\textsf{CSTx}s), primarily due to simultaneous ledger operations on the same account. Hyperledger Fabric, a permissioned blockchain, employs multi-version concurrency control for parallel processing. Existing solutions use channels and intermediaries to achieve cross-sharding in Hyperledger Fabric. However, the conflict problem caused by highly concurrent \textsf{CSTx}s has not been adequately resolved. To fill this gap, we propose HiCoCS, a high concurrency cross-shard scheme for permissioned blockchains. HiCoCS creates a unique virtual sub-broker for each \textsf{CSTx} by introducing a composite key structure, enabling conflict-free concurrent transaction processing while reducing resource overhead. The challenge lies in managing large numbers of composite keys and mitigating intermediary privacy risks. HiCoCS utilizes virtual sub-brokers to receive and process \textsf{CSTx}s concurrently while maintaining a transaction pool. Batch processing is employed to merge multiple \textsf{CSTx}s in the pool, improving efficiency. We explore composite key reuse to reduce the number of virtual sub-brokers and lower system overhead. Privacy preservation is enhanced using homomorphic encryption. Evaluations show that HiCoCS improves cross-shard transaction throughput by 3.5-20.2 times compared to the baselines.
In the rapidly evolving landscape of cloud computing, the burgeoning growth and centralization of data exacerbate security vulnerabilities, necessitating robust and scalable cryptographic solutions. This paper introduces the QP-ChainSZKP framework, a novel architecture that amalgamates Quantum-Secure Cryptographic Algorithms with Zero-Knowledge Proof Management to shield cloud environments against both classical and emerging quantum threats. The proposed QP-ChainSZKP framework effectively integrates advanced cryptographic techniques, enhancing the security protocols and compliance measures required for robust cloud operations. This ensures not only adherence to high-security standards but also provides strong protection against data breaches and unauthorized access, crucial for maintaining data integrity and confidentiality in cloud environments. We employ a dual approach in our methodology by simulating and rigorously testing the framework to evaluate its security, scalability, and performance metrics. The experimental results demonstrate a significant enhancement in transaction throughput and reduction in latency, corroborating the framework’s capability to manage high throughput cloud applications effectively. Specifically, the framework achieves a throughput improvement of 20% and a latency reduction of 30% under peak load scenarios, establishing its efficacy in handling dynamic cloud environments. Notably, the QP-ChainSZKP framework addresses future quantum computational threats by modifying existing cryptographic practices used in public clouds, setting a pioneering standard for using advanced cryptographic technologies in cloud security. Our study contributes a scalable, quantum-resistant solution tailored for extensive cloud applications, marking a substantial advancement in cloud computing security frameworks that can meet the imminent global security requirements.
B Tejaswini, R Induja, M Navyashree, Amreen Kowsar
This paper explores the convergence of block chain technology with distributed NoSQL databases to address the growing demand for secure and scalable decentralized systems. Block chain ensures tamper- resistant and auditable data records, while NoSQL databases offer high- speed data operation for large- scale operations. By integrating these technologies, the proposed system leverages block chain’s agreement- driven synchronization and NoSQL’s effective storage capabilities to produce a flexible frame. The architecture addresses common challenges analogous as data redundancy, quiescence, and performance backups through innovative optimizations. Practical use cases in disciplines analogous as healthcare, finance, and IoT emphasize the eventuality of this approach. also, the paper outlines a crossbred model featuring cryptographic safeguards and off- chain data operation strategies, paving the way for future advancements in decentralized data systems.