Abstract: Cloud computing is an important source of computing worldwide because it can serve customers as needed and without additional costs. Moreover, it serves the customer at the lowest cost and fastest time by providing computing sources in various forms. Aside from providing millions of users the means to use offered services through their own computers, terminals, and mobile devices, studying cloud computing on real cloud systems is difficult at times. Thus, researchers used a specialized program called cloud simulator to study cloud computing, which in turn studies cloud computing from different perspectives, such as energy consumption, cloud services, and resource management. In this paper, we used Green Cloud simulator to model and simulate cloud data centers (DCs). Through this simulator, we presented an experimental comparative study among common task scheduling algorithms in cloud computing (i.e., green, power-saver, random, and round-robin schedulers). These algorithms are discussed and analyzed briefly. The metrics used to evaluate the task scheduling algorithms include (1) server loads, (2) DC loads, and (3) number of servers used.

Abstract: Cloud computing has emerged as a transformative technology with profound implications for thedigital society. This paper aims to evaluate the development and significance of cloud computingand its impact on various aspects of society, including businesses, individuals, and governmentorganizations.The development of cloud computing can be attributed to advancements in internet infrastructure,virtualization technologies, and the increasing demand for scalable and cost-effective computingsolutions. Cloud computing offers a model for delivering computing resources, such as storage,processing power, and software applications, over the internet on a pay-as-you-go basis. Itenables users to access these resources from anywhere at any time, eliminating the need for on-premises infrastructure and reducing the barriers to entry for businesses and individuals.The significance of cloud computing lies in its transformative potential across multiple domains.In the business sector, cloud computing enables organizations to streamline their IT operations,achieve greater scalability, and reduce capital expenditures by shifting from traditional on-premises data centers to cloud-based infrastructure. This empowers businesses to focus on theircore competencies while leveraging the expertise and economies of scale offered by cloud serviceproviders.

Abstract: Cloud computing has been the groundbreaking technology of the last decade. The ease-of-use of the managed environment in combination with nearly infinite amount of resources and a pay-per-use price model enables fast and cost-efficient project realization for a broad range of users. Cloud computing also changes the way software is designed, deployed and used. This thesis focuses on database systems deployed in the cloud environment. We identify three major interaction points of the database engine with the environment that show changed requirements compared to traditional on-premise data warehouse solutions. First, software is deployed on elastic resources. Consequently, systems should support elasticity in order to match workload requirements and be cost-effective. We present an elastic scaling mechanism for distributed database engines, combined with a partition manager that provides load balancing while minimizing partition reassignments in the case of elastic scaling. Furthermore we introduce a buffer pre-heating strategy that allows to mitigate a cold start after scaling and leads to an immediate performance benefit using scaling. Second, cloud based systems are accessible and available from nearly everywhere. Consequently, data is frequently ingested from numerous endpoints, which differs from bulk loads or ETL pipelines in a traditional data warehouse solution. Many users do not define database constraints in order to avoid transaction aborts due to conflicts or to speed up data ingestion. To mitigate this issue we introduce the concept of PatchIndexes, which allow the definition of approximate constraints. PatchIndexes maintain exceptions to constraints, make them usable in query optimization and execution and offer efficient update support. The concept can be applied to arbitrary constraints and we provide examples of approximate uniqueness and approximate sorting constraints. Moreover, we show how PatchIndexes can be exploited to define advanced constraints like an approximate multi-key partitioning, which offers robust query performance over workloads with different partition key requirements. Third, data-centric workloads changed over the last decade. Besides traditional SQL workloads for business intelligence, data science workloads are of significant importance nowadays. For these cases the database system might only act as data delivery, while the computational effort takes place in data science or machine learning (ML) environments. As this workflow has several drawbacks, we follow the goal of pushing advanced analytics towards the database engine and introduce the Grizzly framework as a DataFrame-to-SQL transpiler. Based on this we identify user-defined functions (UDFs) and machine learning inference as important tasks that would benefit from a deeper engine integration and investigate approaches to push these operations towards the database engine.

Abstract: <p><strong><span>Abstract:</span></strong></p> <p><span>Web services and cloud computing have completely changed how people and organizations use and access technology in recent years. Web services offer a standardized method of integrating different software systems, while cloud computing offers scalable computer resources via the internet. Instead of building and maintaining computing infrastructures in-house, cloud computing allows businesses to use compute resources as a utility, similar to energy. For both enterprises and end consumers, cloud computing offers a number of alluring advantages. Web services are software programs that facilitate machine-to-machine communication via a network. They offer a platform-neutral method of system-to-system communication through protocols. This paper </span><span>explores</span><span> the advantages, difficulties, and potential developments of cloud computing and web services working together. Businesses have been able to innovate, cut expenses, and increase efficiency thanks to the integration of these technologies, which has made them crucial in the age of digital transformation.</span></p>

Abstract: In recent years, cloud computing has gained popularity and it is now used to support various areas of human life. Cloud computing technology and services, despite the advantages they bring to the market, have created number of issues regarding the security and trust of the individuals using them. Incidents occurring in cloud computing environments are hard to be solved since digital forensic methods used to conduct digital investigations are not suitable for cloud computing investigations. This is due to the fact that they do not consider the specific characteristics of the Cloud. Cloud forensics has been introduced to help forensic investigators find potential evidence against cloud criminal activities and maintain the security and integrity of the information stored in the cloud. Cloud forensics introduces processes for resolving incidents occurring in cloud computing environments. However, designing cloud services capable to assist a cloud investigation process when an incident occurs is of vital importance and recent research efforts concentrate on these directions. In addition, digital forensics methods cannot support a cloud investigation since cloud environments introduce many differences compared to traditional IT environments. Although cloud forensics assists in the direction of investigating and solving cloud-based cyber-crimes, in many cases the design and implementation of cloud services falls back. Software engineers should focus their attention on the design and implementation of cloud services that can be investigated in a sound forensic manner. This thesis makes an original contribution to knowledge in the field of cloud forensics by implementing a framework that assists software engineers to design cloud forensic-enabled services. In order to do so, a thorough literature review has been conducted focusing on the methodological aspects of cloud forensics. It critically reviews cloud forensics’ existing challenges and solutions and it explores, based on a detailed review of the area, all the work that has been carried out both in digital and cloud forensic methodologies mainly for supporting the investigation of security incidents in cloud environments. Furthermore, the detailed comparison reveals similarities and drawbacks of the existing methodologies providing some novel future research directions. This thesis moves current research one step further by identifying the major concepts, actors and their relationships that participating in a cloud forensic investigation through the introduction of a meta-model. The framework, which is implemented in order to support the elicitation of forensic requirements and software engineers consists of an identified number of a set of cloud forensic constraints, a modelling language expressed through a conceptual meta-model and a process based on the concepts identified and presented in the meta-model. The meta-model presented in this thesis not only includes the concepts that make a system forensic-enabled but also the concepts for cloud forensic investigation, raising the importance of the relation between a forensic-enabled system and an investigation process and how the latter is assisted when an incident occurs. In this way an integrated meta-model is produced to assist designers in a way that, they will be able to design forensic-enabled cloud services. The applicability of the framework is demonstrated through a case study. The main advantage of the proposed model is the correlation of cloud services’ characteristics with the cloud investigation while providing software engineers the ability to design and implement cloud forensic-enabled services via the use of process patterns.

Abstract: This paper evaluates key issues in cloud computing and introduces a novel model, known as sky computing, to address these challenges. Cloud computing, a transformative technology, has played a critical role in reshaping modern operations—especially following the COVID-19 pandemic, when many human activities shifted to technology-driven platforms. It offers multiple service models, including Software as a Service, Hardware as a Service, Desktop as a Service, Backup as a Service, and Network as a Service, each tailored to user requirements. However, the rapid expansion of cloud-based technologies and interconnected systems has intensified infrastructure and scalability challenges. Sky computing, or the “cloud of clouds,” emerges as an advanced layer above traditional cloud models, enabling dynamically provisioned, distributed domains built over multiple serial clouds. Its core capability lies in offering variable computing capacity and storage resources with dynamic, real-time support, providing a robust and unified platform by integrating diverse cloud resources. This paper reviews related technologies, summarizes prior research on sky computing, and discusses its structural design. Furthermore, it examines the limitations of current cloud computing frameworks and highlights how sky computing could overcome these barriers, positioning it as a pivotal architecture for the future of distributed computing.

Abstract: Cloud computing is a new technique of Information Communication Technology because of its potential benefits such as reduced cost, accessible anywhere anytime as well as its elasticity and flexibility. In this Paper defines cloud Computing, Definition, Essential Characteristics, model of Cloud Computing, Components of Cloud, Advantages & Drawbacks of Cloud Computing and also describe cloud computing in libraries. Ø Keywords: Cloud Computing, SaaS, PaaS, IaaS, Components of the Cloud, Models of Cloud Computing, Benefits of Cloud Computing in Library Servicesand Disadvantages, Libraries And Cloud.

Abstract: Cloud-based CAD is a critical direction for the future development of CAD system. This paper proposes a cloud-based CAD processing system utilizing cloud rendering technology and its construction methodology, detailing the overall design scheme of the system architecture, the composition of various components, and their interconnections. Based on the proposed system architecture and implementation approach, a cloud-based 3D design platform has been successfully developed, achieving comprehensive online 2D/3D modeling and collaborative design capabilities. Compared with traditional desktop CAD solutions, this cloud platform demonstrates significant advantages in accessibility, real-time collaboration, and hardware resource utilization. Experimental results confirm the effectiveness of both the proposed system architecture and its implementation methodology.

Abstract: The convergence of Artificial Intelligence (AI) and Machine Learning (ML) technologies with Cloud and Software Testing Automation has fundamentally transformed how organizations operate their IT infrastructures. Processes of automation of complicated procedures make it possible to allocate resources more productively, ensure higher security levels, and construct more rapid cycles of software development and testing. The task of this paper is to demonstrate how these technologies are being used today in the cloud and testing space with pertinent examples from companies such as Netflix and Microsoft. The paper showcases the impact of AI/ML on the cloud ecosystem as well as the issues, solutions and vision in terms of the future developments associated with these technologies. Also, the paper examines the challenges associated with cost, data protection, and the requirement for greater specialists, and addresses the future possibilities including distributed AI architectures along with more powerful cloud management platforms.

Abstract: Abstract—The evolution of distributed computing has been fundamentally shaped by the rise of cloud computing, enabling scalable, flexible, and cost-effective solutions to modern com- putational challenges. Cloud Horizons: Exploring the Future of Distributed Computing examines the next frontier of cloud technology, focusing on emerging trends, innovations, and the evolving landscape of cloud-based infrastructure. This paper explores advancements in cloud architectures, including multi-cloud, hybrid clouds, and edge computing, and their implications for businesses and researchers. It discusses the growing role of artificial intelligence, machine learning, and data analytics in optimizing cloud systems, as well as the impact of quantum computing on future cloud paradigms. Additionally, the paper delves into security, privacy concerns, and the regulatory environment that will shape the future of cloud-based solutions. By synthesizing current developments and anticipating future shifts, this work aims to provide a comprehensive perspective on how distributed computing in the cloud will continue to transform industries, foster innovation, and redefine the way we think about data, computing power, and connectivity in the years to come. Index Terms—Fog Computing, Multi-Cloud Architectures, Cloud Scalability, Cloud Security, Cloud-Native Applications, Virtualization