The thriving Internet of Things, a paradigm shift from the traditional Internet has brought about great societal improvements such as smart homes, smart cities, smart health, intelligent systems and many more. With these diverse societal improvements come increasing complexities in the areas of system efficiency, privacy, and security. In recent years ample academic and industrial research have delved into resource optimization to the detriment of security, as security features are left to be bolted on at the end of design and developmental processes. This approach leaves the system susceptible to threats and attacks. Consequently, this paper seeks to incorporate security features from the onset, weaving the security feature into the system's design and developmental phase. The proposed model structured in a three-tiered design comprises of concepts of Blockchain, edge computing, clustering techniques and a hybrid algorithm consisting of the static round-robin and the dynamic resource-based algorithms. The composition of the structural layout which considers aspects of the blockchain as a security tight measure for resource optimization in Internet of Things' environment, also incorporates features of edge computing, clustering techniques and the hybrid algorithm as components for resource optimization of the Internet of Things. In addition to the prospective security feature provided by the Hyperledger fabric BC in the proposed model, simulation results illustrate the Hyperledger fabric BC's dexterity in making IoT systems even more efficient, further showing its efficacy over the PSOR2B and the BC-EDSSP.
Support tools that monitor software application processes are required to identify, measure, and assess their performance and resolve any anomalies that impede their full functionality. Similarly, applications that use blockchain technology require analysis and monitoring tools for the resources and functionality provided by their smart contracts. This paper presents a computational tool that monitors hardware resources and evaluates transaction processing requests in blockchain networks. The solution presented here is called MonitorChain, and it has software components that allow the connection with different blockchain networks, the configuration of the workload, the monitoring of consumed hardware resources, and the evaluation of requests processed over blockchain networks. The effectiveness and adaptability of MonitorChain were validated through extensive evaluations across various blockchain environments, including public networks like Ethereum, Avalanche, and Fantom, as well as a private network using Hyperledger Fabric, with a consistent data load of 10,000 transactions. Additionally, through interviews with experienced software developers, we gathered feedback that led to further refinements and identified opportunities for future enhancements. The results demonstrated MonitorChain’s capability to provide critical insights into blockchain applications’ performance, scalability, and efficiency. MonitorChain advances the field compared to existing solutions by offering enhanced support for diverse networks, customizable workloads, and real-time data visualization, contributing significantly to the blockchain monitoring landscape.
This work proposes an end-to-end architecture for secure data federation and privacy-preserving analytics across multi-tenant cloud environments using homomorphic encryption (HE). We address the core challenge of enabling cross-tenant joins, aggregations, and model scoring without exposing plaintext or weakening tenant isolation. The framework integrates schema-level federation with encrypted data lakes, columnar ciphertext packing for vectorized operations, and an adaptive HE planner that selects between CKKS for approximate analytics and BFV/BGV for exact computations. To bound latency while maintaining correctness, we apply batching, ciphertext relinearization, and rotation scheduling, and offload heavy primitives to accelerator-ready microservices. Policy-aware orchestration enforces per-tenant keys via cloud KMS and supports fine-grained access control and revocation. For sensitive workflows, we compose HE with complementary protections secure enclaves for control-plane logic, differential privacy on result releases, and zero-knowledge proofs to attest query policy compliance achieving defense-in-depth without collapsing the HE trust model. The system exposes SQL-like and DataFrame APIs, a query optimizer that estimates noise budgets and bootstrapping costs, and lineage-rich audit trails for regulatory reporting. We outline deployment patterns on containerized clusters, discuss cost/performance trade-offs under realistic workloads, and provide guidance on tenancy hardening (noisy neighbor resistance, side-channel hygiene). The result is a practical pathway for organizations to collaborate on analytics and machine learning across clouds and jurisdictions while preserving confidentiality, minimizing data movement, and meeting compliance obligations
Today’s organizations are seeking to develop new solutions to enhance the security, transparency, and accessibility of their cloud-based infrastructure. Integrating distributed ledger technology with cloud-based infrastructure can bring significant advantages to organizations but involves a complex process that requires meticulous planning, design, and execution. The process commences with choosing the suitable DLT platform, and one must possess a thorough understanding of distributed ledger technology and cloud computing technologies, including their unique features, capabilities, and compromises.
The need for patient-centered electronic records that can store and retrieve the myriad details of a patient's medical history as documented during treatment has increased dramatically.These records are vital for future care, billing, or treatment.The distributed ledger technology known as Blockchain enables us to store this data and start and enable use at lightning speed while keeping the system transparent and secure.Using a distributed system with ledger capability allows for the safe and interoperable storage of records.With the elimination of mediators in financial and data transactions and in verifying data authenticity and ownership records, blockchain technology promises to alter the current state of digital asset transactions radically.Its extensive files and easy access to patients' medical histories are two of the most critical issues in healthcare, and its immutability, decentralization, and openness make it an ideal solution.Interoperability, the ability of various health organizations and software product makers to connect and exchange data securely and smoothly, is crucial to healthcare systems' practical and successful operation.Lack of interoperability is the root cause of many difficulties in contemporary healthcare, including data silos and disparate workflow tools.To solve this problem, a system that allows safe, recognized medical records to be kept in separate databases should be implemented.Using fog computing, which can decentralize data processing and handle massive amounts of data, we reviewed the literature and performed a system overview of blockchain technology in this study.Our ongoing experimental study highlights areas where current systems are lacking and suggests potential avenues for further research.
Junaid Nasir Qureshi, Muhammad Shoaib Farooq, Adel Khelifi, Zabihullah Atal
Distributed Scrum of Scrums Agile Software Development (DSsASD) plays a crucial role in modern software development, enabling collaboration across vast distances in software development. However, existing tools and frameworks have struggled to effectively address communication, teamwork, and collaboration challenges within DSsASD teams. These challenges include transparency, trust, traceability, auditability, and security concerns, these issues are related to project delays, client dissatisfaction, contract cancellations, miscommunication collaboration, and payment disputes between stakeholders. To tackle these persistent concerns and issues, this article introduces ChainAgilePlus, a novel framework that integrates blockchain technology in the distributed scrum of scrum agile software development. ChainAgilePlus implements smart contracts by utilizing a private Ethereum blockchain to govern acceptance acknowledgment, deployment testing, secure payments, verification of developer payments, and automated payment distribution to team wallets. Smart contracts also enforce penalties for delayed payments and overdue tasks, promoting accountability and adherence to deadlines. Additionally, ChainAgilePlus mitigates blockchain scalability challenges by integrating the Interplanetary File System (IPFS) for off-chain storage. Empirical results from experimental processes demonstrate the effectiveness of ChainAgilePlus in enhancing communication, transparency, coordination, traceability, auditability, security, and trust among clients and developers in DSsASD projects.
Introduction/purpose: This work provides a comprehensive overview of blockchain technology, elucidating its foundational principles and how it ensures transparency, immutability, and decentralization. The integration of Solidity with blockchain is explored through theoretical approach. Methods: This work meticulously dissects blockchain principles, elucidating transparency, immutability, and decentralization, while exploring Solidity integration in a theoretical framework, ensuring a comprehensive understanding of their intricate relationship and contributing to a broader comprehension of modern distributed ledger technology. Results: The resulting product of this paper will be getting useful knowledge about the technology that practically shapes the world. Conclusion: In conclusion, the adoption of Solidity as a programming language in blockchain technology has proven to be pivotal, enhancing smart contract functionality and overall system security. Its specialized features make it an indispensable tool for developers navigating the complexities of decentralized applications.
Due to the promising scalability property, sharding technology has gained widespread attention. It improves the transaction throughput of blockchain systems but also introduces cross-shard transactions. Current two-phase commit (2PC) protocols process different cross-shard transactions sequentially, resulting in significant system overhead and low throughput. Besides, current sharding blockchains rely on Byzantine fault tolerance (BFT) as a black box, lacking specific designs to efficiently handle cross-shard proposals. Moreover, cross-shard communication complexity is high, and transaction processing parallelism is low. In this paper, we first propose P-2PC, a general framework to process cross-shard transactions of different phases in a pipelined way, suitable for most sharding blockchains. Further, we design Cherubim with improved quadruple 2PC, 4P-2PC. By combining P-2PC with an intra-shard pipelined BFT, 4P-2PC achieves both intra-shard and cross-shard pipelined processing. Combined with a newly designed batch processing method, each shard processes 4 transaction batches simultaneously through 1 round of calculation and communication, compared to 4 rounds in previous work. In particular, Cherubim seamlessly integrates a multi-signature algorithm supporting further aggregation, reducing communication complexity. Furthermore, we evaluate our work through theoretical analysis and implementation, proving that Cherubim has a communication complexity linear to the node number. We also propose horizontal and vertical consensus parallelism degrees to evaluate the parallelism ability. Compared to the state-of-the-art solutions, the evaluation demonstrates that Cherubim achieves a transaction throughput improvement of at least 2.28×.
Blockchain is an emerging technology with Big data, Artificial Intelligence, and Machine Learning. It disrupted industries such as health, education, manufacturing, and banking. However, the increasing popularity of Blockchain ex- poses the scalability issues of major public blockchain platforms (e.g., Bitcoin and Ethereum) and dramatically affects its development. The scalability problem manifests in terms of Low throughput, high transaction latency, and massive energy consumption. Several reviews and studies cover these factors and their potential solutions, yet these studies need to highlight more information through actual application to natural systems or projects. This study investigates all relevant papers on current research solutions for public blockchain scalability issues. The scope of this paper is to explore the implementation of different state-of-the-art scalability solutions to natural systems and projects while simultaneously highlighting the results. This study discusses the methods and techniques used and the challenges encountered that have yet to future researchers must explore.
Distributed Outsourced Storage systems, exemplified by the InterPlanetary File System (IPFS), offer compelling alternatives to traditional centralized cloud storage by emphasizing resilience and openness. Advancing this paradigm, Decentralized Storage (DS) markets leverage distributed ledgers to facilitate the monetization of outsourced storage. However, these markets often prioritize security over cost-efficiency, leading to high costs in existing DS markets. In our work, we introduce a middleware service, DWare, utilizing trusted hardware to balance security and cost efficiency. DWare offers two key advantages: 1) It enhances storage auditing efficiency by delegating computational tasks and standardizing the batched audit process. This approach offers a more feasible solution for validating outsourced storage with recurring pay-offs. 2) It implements secure and verifiable data deduplication, thereby increasing storage efficiency and reducing operational costs. This step, commonplace in cloud storage services, remains largely unexplored in current DS designs. While DWare could empirically reduce costs to levels near raw storage fees, it entails certain security concessions due to middleware involvement. To address this, we propose a hybrid trust security model, granting data owners the flexibility to adjust the security-cost balance as needed.
Oleksandr Ulichev, Oleksandr Dorenskyi, Victor Kulahin
The rapid advancement of technology and increasing market competition compel businesses to adapt swiftly by implementing new features and services to meet user demands. Traditional monolithic software architectures often hinder this agility due to challenges in scalability and maintenance. This article aims to analyze microservice architecture to solve these challenges, exploring its historical development, current trends, practical implementation aspects, and comparison with alternative architectural styles such as modulith architecture. The study examines the limitations of monolithic architectures in handling growing complexity and scaling requirements. It explores the emergence of microservice architecture, highlighting core characteristics like independent services, decentralized data management, and autonomous deployment. The evolution influenced by agile methodologies and DevOps practices is discussed. A comparative analysis with other architectural styles—including monolithic, service-oriented, modular monolithic, and serverless architectures—identifies contexts where microservices are most beneficial. The research reviews essential tools and technologies for implementing microservices, such as Docker for containerization, Kubernetes for orchestration, and service meshes like Istio and Linkerd. Practical cases from industry leaders like Netflix and Amazon illustrate successful adoption and the challenges faced during implementation. Findings indicate that while microservice architecture offers significant scalability, flexibility, and rapid deployment advantages, it also introduces complexities related to distributed system management and security. The study emphasizes the importance of adopting best practices and standards, such as those promoted by the Cloud Native Computing Foundation and utilizing modern tools to mitigate these challenges. For organizations where full microservices adoption may be impractical, modulith architecture is a viable alternative that combines modularity with deployment simplicity. The article concludes that the choice of architecture should be carefully aligned with the project's specific needs, resources, and long-term strategic goals.
Asma A. Alhussayen, Kamal Jambi, Maher Khemakhem, Fathy Eassa
Blockchain interoperability has become an essential requirement for the advancement of blockchain technology in numerous fields. Enterprise organizations are increasingly utilizing permissioned blockchains to manage and store their organizations’ data and transactions in a private immutable ledger. Interoperability enables permissioned blockchain platforms to communicate and exchange information which is paramount for fully exploiting permissioned blockchains as facilitators for B2B applications. Additionally, the cross-network invocation of smart contracts under agreed conditions enhances business operations. Blockchain oracles can enable permissioned blockchain interoperability and cross-network transactions in a seamless and private manner. However, they have not been studied in the literature as interoperability techniques between permission blockchains. This study proposes a blockchain oracle interoperability technique designed specifically for permissioned blockchain platforms. We presented the architecture of the blockchain oracle interoperability technique and a prototypical implementation to demonstrate the practicality of the proposed technique. In addition, we obtained cross-network transaction latency measurements and analyzed the results.
Process (or workflow) execution on blockchain suffers from limited scalability; specifically, costs in the form of transactions fees are a major limitation for employing traditional public blockchain platforms in practice. Research, so far, has mainly focused on exploring first (Bitcoin) and second-generation (e.g., Ethereum) blockchains for business process enactment. However, since then, novel blockchain systems have been introduced - aimed at tackling many of the problems of previous-generation blockchains. We study such a system, Algorand, from a process execution perspective. Algorand promises low transaction fees and fast finality. However, Algorand's cost structure differs greatly from previous generation blockchains, rendering earlier cost models for blockchain-based process execution non-applicable. We discuss and contrast Algorand's novel cost structure with Ethereum's well-known cost model. To study the impact for process execution, we present a compiler for BPMN Choreographies, with an intermediary layer, which can support multi-platform output, and provide a translation to TEAL contracts, the smart contract language of Algorand. We compare the cost of executing processes on Algorand to previous work as well as traditional cloud computing. In short: they allow vast cost benefits. However, we note a multitude of future research challenges that remain in investigating and comparing such results.
Capital markets post-trade processes (trade capture, clearing, settlement and reconciliation) are currently limited by excessive data fragmentation, reconciliation lag and high operational expenses. A central architecture creates "data silos" which restricts scalability, transparency and flexibility of integration between disparate financial institutions. This paper introduces a unified, technically advanced framework integrating Hyperledger Fabric (HLF); a permissioned Distributed Ledger Technology (DLT) with cloud native micro services as a means of creating a scalable, fault-tolerant and transparent ecosystem. By implementing Kubernetes based orchestration and Istio service mesh, we have shown how a legacy monolithic system can be replaced with a dynamic, distributed system capable of supporting high frequency transactions. Simulation results on large scale cloud based test beds show that our predictive resource orchestration framework achieves a 5 times greater throughput than a typical standalone DLT deployment and a 26-fold reduction in 95th percentile (p95) latency. The framework offers a scalable way of provisioning AI driven FinTech workloads with significantly increased reliability and decreased Total Cost of Ownership (TCO).