cloud computing

Cloud technologies are innovative techniques that offer shared resources for stock cache and server management. Cloud technologies save time and monitoring costs for any organization and turn technology solutions into a framework for large-scale systems from server to service. However, cloud technologies create many forms of security threats and problems. In this paper, we focus on discussing various cloud models and cloud services. Then, we discuss security trends in cloud models.

This paper analyzes the challenges, current limitations, and future prospects of database systems in modern information systems. Quantitative assessments indicate that NoSQL solutions can increase transaction processing speed by up to 40% compared to traditional SQL systems under high load conditions, while cloud-based architectures reduce maintenance costs by approximately 30% and improve system availability.

This article presents a new scalable system for automated modeling of physical processes and experiment management based on microservice architecture and cloud technologies. The proposed platform addresses the growing need for flexible, cost-effective, and highly scalable computational solutions for physical research. The system utilizes Amazon Web Services cloud infrastructure with containerized microservices to provide automated resource allocation, experiment orchestration, and laboratory equipment integration.

Cold-chain logistics needs decisions that are fast in operation and defensible at audit. This article presents a compact, evidence-centric workflow for service-level agreements (SLAs). SLA clauses are encoded as smart- contract rules on a permissioned blockchain with Byzantine fault-tolerant consensus (Hyperledger Fabric).

The rapid expansion of cyber-physical systems (CPS) has intensified the need for scalable and adaptive mechanisms to collect heterogeneous environmental data from numerous unstable external sources. Traditional serverless orchestration frameworks, while elastic and cost- efficient, lack runtime adaptability and feedback-awareness, leading to inefficiencies under dynamic API conditions. This paper presents a novel adaptive orchestration model for serverless data collection pipelines, driven by metadata configuration and continuous feedback control.

Due to the need to store large amounts of data, automate processes, support business continuity, and organize remote work, there is a need for a deep understanding of the concepts and capabilities of cloud computing. The use of this technology is becoming a key factor in the competitiveness of enterprises in the digital age.

This paper proposes a novel architecture of a multi-agent system and its formal specification for analyzing and adaptively correcting students' learning trajectories using software agents in digital learning environments. The proposed approach integrates artificial intelligence tools, tem- poral logic, and a multi-agent system architecture to ensure personalized adaptation of educational content.

The article explores the architecture of efficient and high-performance distributed on- line transaction processing systems, leveraging cloud-based tools, cloud-native architectural approaches, and database replication methods. It focuses on reducing network latency, opti- mizing resource usage−and consequently, costs−enhancing data replication, and improving fault tolerance. This article provides a practical demonstration of how modern cloud solutions and technologies enable the rapid and efficient development of enterprise-level distributed online transaction processing systems.