Abstract: Computing services are increasingly located in computing clouds, which allows for on-demand scalability but may also increase operating costs. It is believed that cloud expenses constitute a significant budget item in companies of all sizes. There is a considerable body of work dedicated to reducing the costs of cloud computing, which is mainly focused on optimizing the use of cloud resources. Such optimization, however, tends to result in the deterioration of computing service responsiveness and, as a result, quality of service parameters, especially when applied to real-world, noisy data which include anomalies. This article presents a novel approach which involves a six-stage optimization process incorporating load prediction supported by machine learning, the discovery of computing service characteristics and long-term planning of resource usage alongside anomaly detection and continuous monitoring with a self-adapting ability. The solution proposed works autonomously, builds knowledge about the optimized system and its load patterns, calculates cost-optimal resource provisioning plans and adapts to rapid environmental changes. Our evaluation using Microsoft’s Azure cloud environment demonstrates savings ranging from 31% to 89% depending on the test scenario; cost reductions for other cloud computing providers were estimated as well.

Abstract: Conventional cloud computing, where compute, storage, and networking resources reside in one or a few centralized data centers, has become unable to meet the stringent latency requirements of new applications. Along with that, the rapid development of 5G network introduces the trend of network cloudification and network service provisioning according to cloud service models. Therefore, the emerging distributed cloud model represents an evolution from conventional centralized cloud into geographically dispersed cloud computing services located as per application needs. In this article, we attempt to sketch a big picture of distributed cloud. We first interpret the concept of distributed cloud computing. Then, we describe an architecture of the distributed cloud along with the enabling technologies. We also carry out a case study on service deployment and discovery in a three-layer distributed cloud prototype and provide a preliminary assessment of service discovery time. Finally, we discuss open research challenges toward distributed cloud.

Abstract: Cloud computing is a new paradigm in information and communication technologies (ICTs) that provides the ability to access shared pools of different computing resources that are related to many cloud users within a pay-per-use or on-demand approach. It has transformed the delivery model of ICT from a product to a service. This provides several different advantages for institutions, companies and users based on savings and reduced capital expenditure through lower operating expenses. This paper provides a comprehensive survey of cloud computing. It first develops an understanding of cloud computing in general and discusses its advantages, current development, challenges and future trends. Subsequently, a detailed discussion on the cloud computing architectures, services models, fault tolerance mechanisms, services selection methods, adoption by industry, and scheduling of cloud-based resources is also presented. Nonetheless, cloud computing has many obstacles which expose it to a number of limitations. Some of these challenges include security of data, fault tolerance, and load balancing. A number of techniques in literature are proposed to cope with these challenges which are discussed and analyzed. Experimental data and usage drift validates the popularity of cloud computing and its adoption in recent years. Future trends in cloud computing support the use of intelligent machine learning (ML) techniques and new technologies to cope with some of the challenges and making cloud computing more efficient, secure and commercially viable to be widely accepted. Keywords—Cloud computing; security challenges; machine learning; resource scheduling; information and communication technologies

Abstract: <p>With a variety of software and hardware services available to users, cloud computing has developed in recent years as a very influential and transformational technology. It functions as a fundamental method for sharing resources via the internet, with virtualization being essential to making this sharing of cloud resources possible. The National Institute of Standards and Technology (NIST) has described cloud computing as a concept that permits easy, on-demand network access to a shared pool of reconfigurable computing resources. With little management work or communication with the cloud provider, these resources can be quickly supplied and released. A significant amount of businesses have adopted cloud computing due to the many advantages and opportunities it provides. But the quick shift to the cloud has also given rise to security worries. Cloud computing is one of the modern technology that must to be used with caution. Cloud computing does not come with strong data privacy protections. Therefore, it is very important to ensure the confidentiality of data storage in order to protect data security. The objective of this paper is to discuss about the cloud computing models, the cloud service providers, the security and privacy issues surrounding cloud computing. Furthermore, prevention strategies and best practices for security and privacy issues in cloud computing will also be discussed in this paper. </p>

Abstract: This chapter examines the fundamentals of cloud computing and its applications. Beginning with the National Institute of Standards and Technology (NIST) definition of cloud computing, it covers the five essential characteristics, three service models, and four deployment models the NIST has defined. It introduces compute, storage, database, and network as components that work together to create a modern data center. It presents an overview of virtualization, a disruptive technology that paved the way to the cloud. Business drivers for cloud adoption are presented. This chapter concludes by comparing a legacy to a virtualized three-tier web architecture.

Abstract: In the current scenario, researchers have made a new invention and added to the computing paradigm every next second. Cloud computing is one of the most demanding, practical, accessible and extended technologies based on ‘pay as per use model’ and works on virtualisation via internet. Data sharing and accessing have become easy by properly organising various resources, such as storage, servers, development tools, software, etc, in cloud. Handling these resources has faced many challenges, such as cost management, system performance, migration, load imbalance, reliability and privacy etc. Load imbalance is one of the most important factors which are solved by load balancing techniques. This paper introduced the detailed classification of load balancing methods and techniques that are taken as a solution to overcome such problems and also helps future researchers. Also given is a proposed model for load balancing and some comparative studies of the heuristics methods based on platforms and simulator tools.

Abstract: In the recent era, Cloud computing has emerged as a high demanding technology. Apart from the cloud computing, edge and fog computing also becoming popular. Cloud computing was developed to provide steady and expansible services to end-users as well as industries. The merger of cloud computing with smart devices brings us into a new version of computing. Presently, Edge computing and fog computing techniques are flattering the world after cloud computing, which has all matured with the limitations in cloud. The objective of this study is to examine the current trends and concepts in detail, also, to provide a comparative study for the fog computing, edge computing, and cloud computing. This study includes few features, application, advantages as well as disadvantages, and the contrast between these technologies and how every one of them is effective for different applications.

Abstract: The flexibility and reliability with which cloud computing can deliver a wide variety of computation, memory, communication, and resource management services through the internet have contributed to its rise in popularity in recent years. Increasing interest in cloud computing is due to the growing need for reliable, affordable infrastructure. This essay largely focuses on an overview of problems and unresolved difficulties with cloud databases as storage for cloud computing. This survey’s objective is to give a researcher a broad perspective on the problems, unresolved problems, and emerging trends in cloud storage, with a particular focus on cloud databases. This article compares academic approaches and methodologies to address the difficulties related to data availability, including replication, managing, and securing data in cloud enabled technologies.

Abstract: A holistic approach that makes it possible to control, manage, and optimize both computing resources and networking in a Cloud environment is required because of the crucial role that networking plays in Cloud computing. This results in a convergence of networking and Cloud computing. As a crucial feature for the next generation of networking, network virtualization is being implemented in the Internet and telecommunications sectors. It is anticipated that virtualization will bridge the gap between these two fields as a potential enabler of profound changes in the communications and computing domains. When applied to network virtualization, Service-Oriented Architecture (SOA) creates a Network-as-a-Service (NaaS) paradigm that may significantly facilitate the convergence of networking and Cloud computing. The use of SOA in network virtualization has recently received a lot of attention from both academia and industry. Although numerous pertinent research papers have been published, they are currently dispersed across a variety of subject areas in the literature, such as cloud computing, telecommunications, computer networking, and Web services. Specifically, we first introduce the SOA principle and review recent research progress on applying SOA to support network virtualization in both telecommunications and the Internet. In this article, we present a comprehensive survey of the most recent developments in service-oriented network virtualization for supporting Cloud computing, particularly from the perspective of network and Cloud convergence through NaaS. Next, we discuss the most recent advancements in network service description, discovery, and composition, as well as a framework for network-to-cloud convergence based on service-oriented network virtualization. We also talk about the problems these technologies face because of network-cloud convergence and the research opportunities in these areas. Our goal is to get researchers interested in this new interdisciplinary field.

Abstract: Cloud Computing is a method of providing IT computing resources over Internet, ranging from data storage and processing of software’s to provisioning of an operating platform. With the advent of Amazon Web Services, Google Cloud Platform, Microsoft Azure, the cloud computing services are now affordable and businesses can transform their existing server infrastructures into dynamic environments where they can expand and reduce their server capacity depending on their requirements. The advent of technology is leading to the big data cloud computing which is an on-demand delivery of IT resource over Internet. Different cloud computing platforms like AWS, GCP, IBM Cloud, MS Azure, provide pay as per need services. Cloud computing provides different models as services like Infrastructure as Service, Platform as a Service and Software as a Service to the users. In big data cloud computing, platforms are very commonly used for data analysis. In the paper, services offered by various cloud computing platforms like AWS, GCP, IBM Cloud and MS Azure for building a data analytics platform are discussed.

Abstract: A technology architecture known as "cloud computing" offers end users on-demand, scalable, & measurable resources. Today's businesses rely heavily on computational innovation for a variety of reasons, including cost savings, architecture, developmental platforms, data preparation, data insights, etc. The end users have accessed the cloud service providers' (CSP) services from any location at any time using a webpage. The protection of the cloud platform is of the utmost importance, and many studies using a variety of technologies have been conducted to develop more effective defences against cloud threats. In upcoming years, machine learning technology has shown to be more effective in security the cloud environment. In contrast to other technologies, machine learning algorithms are educated on a variety of real-world information to develop complex that can streamline the task of identifying cloud assaults. This article examines some of the most recent studies that have used machine learning as a defence versus cloud threats.

Abstract: Cloud computing is a technology that impacted the performance of modern markets and businesses. Because of this, cloud computing has become more significant to humans with its virtualization and distributed computing. However, according to the gathered literature for this paper, cloud computing imposes security concerns. This paper examines the definition of cloud computing by analyzing its historical perspective, architecture, and framework. We attempt to understand cloud security threats by classifying their type and affected cloud layers. From that, we correlate our assessments to the virtualization of Philippine education.

Abstract: After years of development, cloud computing has developed into public cloud, private cloud, community cloud, hybrid cloud and other cloud forms. However, the government, financial and other industries have more concerns about security, operation and maintenance, cost and other issues in the process of cloud. In this regard, the industry, academia and other parties have launched the frontier exploration, give different solutions. To meet users’ new needs, we proposed a new model that combines the advantages of public and private clouds. It is called proprietary cloud. Proprietary cloud provides users with more efficient management by incorporating years of experience of public cloud providers. On the one hand, it meets the rigid needs of users’ independent control and exclusive resources, on the other hand, it reduces the maintenance cost and downtime probability of users, and achieves the desired effect of users. It mainly includes self-built model and exclusive model deployment modes. The main difference is whether to accept public cloud management. This paper introduces and analyzes proprietary cloud in detail from the aspects of deployment architecture, mode differences and common deployment patterns. It concludes that proprietary cloud is an indispensable cloud computing deployment pattern in the future.

Abstract: Abstract Context Over the last decade, the widespread adoption of cloud computing has spawned a new branch of the computing industry, known as green cloud computing. Cloud computing is improving, and data centers are increasing at regular frequencies to meet the demands of users. Cloud providers, on the other hand, pose major environmental risks because massive data centers use a large amount of energy and leave a carbon footprint. One possible solution to this issue is the use of green cloud computing. However, clients face significant difficulties in adopting green cloud computing. Objective This study aims to understand the problems faced by client organizations while considering green cloud computing. In addition, this study aims to empirically identify the solution to the challenges faced by green cloud computing practitioners. Method A questionnaire survey approach was used to get insight into green cloud computing practitioners concerning the challenges they faced and their solutions. Results Data were obtained from sixty-nine professionals in green cloud computing. The results revealed that "lack of quality of service", "lack of dynamic response", and "lack of services to satisfy client's requirements" are critical for green cloud computing. In addition, sixty-three practices for addressing the challenges in green cloud computing are also identified. Conclusion The identified challenges and practices of green cloud computing will benefit the client organizations to update and revise their process to consider green cloud computing. In addition, it will also assist vendor organizations in developing, planning, and managing systems concerning client satisfaction.

Abstract: The concept of distributed cloud computing is a part of cloud computing systems in which the computing resources and software applications are located at different cloud service providers or servers but they act under one cloud computing software for operating and managing the resources across multiple cloud platforms.

Abstract: Abstract Cloud computing offers a widespread variety of services for the users. In multi-cloud environment, the service centric features are introduced to assist the cloud users from the multiple endpoints. In order to enhance the service availability, cloud brokerage is introduced into the multi-cloud environment that outperforms the effective utilization of required services. The primary objective of a cloud broker is to ensure about the services and its outcomes while offering them to a customer. The role of a traditional broker has the restrictions such as measuring the service trust, validity, and the future enhancement of the considered cloud services from the multi-cloud environment. Hence, the need for the intelligence feature is highly solicited in the cloud broker while working in a multi-cloud environment. The proposed intelligent cloud broker performs the validation and verification of service trust details by analysing the service trust factors such as service response time, sustainability, suitability, accuracy, transparency, interoperability, availability, reliability, stability, cost, throughput, efficiency, scalability of the cloud services. The customer’s feedback is taken into consideration for measuring the service trust factors before the service recommendation. In this proposed model, the Service Ranking (SR) values are calculated for the available cloud services. Additionally, the proposed model considers the newly arrived services during cloud services validation process by mapping its services with the available cloud services from the Service Collection Repository (SCR). Hence, this proposed model outperforms well in the process of recommending services to the cloud users.

Abstract: An emerging method of digital computing known as "cloud computing" has recently gained immense popularity. While there are many benefits to using the cloud over the internet, there are also serious challenges that must be addressed in order to boost the efficiency of this method. Challenges to cloud computing via the internet include load balancing, work scheduling, fault tolerance, and several security concerns. The effectiveness of the cloud may be enhanced by fixing a number of problems, one of the most pressing being load balancing. To prevent any one node from being too overburdened or underused, a system employs a technique known as load balancing. In order to increase utilization and minimize overall task execution time, load balancing algorithms are developed to distribute work fairly across available resources. In this article, a review and comparison of different load-balancing algorithms is provided. This paper provides a basis of the application of different load-balancing techniques, which utilize the approach of soft computing within the cloud computing environment.

Abstract: For the last few decades cloud computing is a blooming word in the field of computer science. Cloud computing is a fast growing technology; it provides various services to the user through internet on demand. Now a days, people in busy move, they use Cloud to store and retrieve data at anywhere, any time without use of any physical storage devices like pen drive, compact disc etc . Enormous features of cloud, most of the small and large scale organizations outsource their data in cloud data storage. With the widespread application of cloud, huge amount of users are incorporated in public cloud, it may lead to vulnerable attacks. So security and privacy is an important factor in cloud environment. This security problem can be solved by various ways. Cryptography is one of the techniques to secure user data in cloud. Researchers can use various cryptographic algorithms to implement the security in cloud storage. This paper focuses the summative analysis of researches, in cloud security from 2018-2022. This survey paper provides solution to researchers who have their work in cloud.

Abstract: Nowadays, cloud computing is a growing field in research and the marketplace, including virtualization, internet service, computer software, and web services. A cloud comprises multiple elements like a consumer's data center and servers. It provides high availability, efficiency, scalability, mobility, fault tolerance, decreased overhead of users, reduced expenses of ownership, on-demand services, etc. A Variety Of users need various Quality of Service (QoS) demands. Therefore, the cloud supplier needs to arrange the tasks to get maximum advantages regarding their services, and the consumer's quality of service demands are satisfied. Currently, the need for cloud is increasing day by day, people moved towards cloud simultaneously, so its scale is up that's why the service providers are required to deal with enormous requests. The biggest challenge is the availability of services and maintaining the performance equivalent or more effective whenever workload occurs. Multiple requests are processed simultaneously; that's why the workload increased. The load balancer uses to resolve that issue. Our research shows how to balance the load in a cloud environment using fuzzy logic. The processor speed, storage capacity, and assigned load of Virtual Machine (VM) utilize to balance the load in cloud computing through fuzzy logic to achieve better processing time and storage utilization.

Abstract: Cloud computing provides on-demand delivery of computer resources ranging from, compute, data storage, networking, software, and other IT services over the internet in exchange for pay as you go billing model. The study discusses various types of cloud computing available, cloud computing advantages, cloud computing implementation models, cost-effective IT solution, IT service agility, challenges, and features of cloud computing in this growing digital world. Keywords: cloud, data storage, compute, digital, on-demand billing model.

Abstract: One of the cornerstones of the future generation of computing is cloud computing, a form of internet-based computing. It allows for the instantaneous allocation of Internet-accessible resources whenever they are needed. Services such as software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) are made available to people and businesses through cloud computing. By giving customers a low-cost, scalable, and financially-independent place to store their data, cloud storage services have seen rapid revenue growth in recent years. An interoperable cloud computing system is built on open architectures and interfaces that support both private and public cloud services. Many businesses today are making the switch to the cloud because of the numerous advantages it offers in terms of data storage, retrieval, management, and availability. While cloud computing is receiving a lot of attention, it is imperative that security problems be addressed first. This study proposes a crypto-stegno mechanism in the cloud as a solution to cloud security problems. This study proposes a practical method for ensuring data privacy and security in cloud storage. In order to obtain their own public and private key, users must first register their information in the cloud and come up with a unique username and password. Cryptography, a means of concealing information and sending information in an unreadable format, is employed in the next level of security. Secure data transmission and storage on the web, electronic commerce, digital media privacy, and ATM transfer are all dependent on cryptography to some degree. Repudiation, integrity, authenticity, and confidentiality are all possible using today's cryptographic methods. Signcryption is a lightweight cryptographic system that combines encryption and signatures in a logical way to achieve higher security with less computing time.

Abstract: Cloud computing seems to be a scalable and realistic distributed computing platform that delivers resources as a service. One of the major difficulties impeding cloud computing development is data security in the cloud. The security vulnerabilities in cloud computing and other cloud services slow down cloud computing growth and difficulties with data protection and privacy. In this new context, cloud service customers must be cautious about data breaches. This article studies a solution to current diverse security challenges that have arisen as a result of the service demonstrating that the offered methods are provably safe and very efficient. The solution comprises a distributed multi-level security scheme for processing the information involved in cloud computing. The proposed scheme evaluates the most significant encryption techniques generally used in various industries like AES (Advanced Encryption Standard), Blowfish, 3DES (Data Encryption Standard), CAST128, and RC4 (Rivest Cipher 4). The proposed model with these encryption techniques ensure minimal energy consumption in cloud computing with maximum speed. Moreover, to increase the security of the data, various cryptographical algorithms are applied, analyzed, and compared in an OpenStack environment.

Abstract: With the rapid development of cloud computing technology, the problem of high energy consumption in data centers is becoming more and more obvious. Researchers pay more attention to how to guarantee the quality of service and improve the efficiency of resource application in their research. According to the analysis of the application of open source infrastructure service platform OpenStack proposed by experimental research in recent years, it is clear that the key technology points of cloud computing can provide an effective basis for the development of modern technology. Therefore, on the basis of understanding the research status of OpenStack cloud platform and cloud computing key technologies, this paper mainly discusses the agile elastic scaling technology with load prediction or feedback as the core. The final experimental results show that the proposed algorithm can use less disk space, improve the efficiency of resource application and service quality.

Abstract: Cloud computing leverages wide range of services (storage, servers, databases, analytics, intelligence, networking, and software) via internet to speed up innovation, provide flexible resources, and forecast economic scalability. Examples include, Netflix (for streaming video) and Gmail (for backup needs). Cloud simulation utilizes computer services in simulation and is nothing more than infrastructure and software that researchers employ as a service. Data centres, virtual machines (VM), and other items can all be managed through CloudSim's administration interfaces. Cloud simulators are used to simulate many kinds of cloud applications. A product can be evaluated by using simulations and make unrestricted fixes to issues prior to the actual launch. Therefore, cloud simulator is an economical tool used to analyse the working of cloud components to operate under various conditions and workloads. Over the years, several cloud simulators have been created; this article provides an evaluation study of most of the existing techniques. This study discusses about the typical architecture in computer simulators. This study has covered cloud simulation operation of the Internet Simulator.

Abstract: Cloud computing provides resources to its consumers as a service. The cloud computing paradigm offers dynamic services by providing virtualized resources via the internet for enabling applications, and these services are provided by large-scale data centers known as clouds. Cloud computing is entirely reliant on the internet to provide its services to consumers. Cloud computing offers several advantages, including the fact that users only pay for what they use weekly, monthly, or yearly, that anybody with an internet connection may use the cloud, and that there is no need to purchase resources, hardware, or software on their own. This paper proposes an efficient task scheduling algorithm based on the Jaya algorithm for the cloud computing environment. We evaluate the performance of our method by applying it to three instances. The recommended technique produced the optimal solution in makespan, speedup, efficiency, and throughput, according to the findings.

Abstract: The development of cloud computing has significantly altered how services are built, deployed, and made accessible to users outside of the organization. In actuality, the pay-as-you-go model of dispersed IT supported by the cloud computing paradigm calls for the outsourcing of software services and applications. In this situation, the capacity to ensure effective cloud performance management and to facilitate automated scalability become fundamental prerequisites. Users of the cloud are becoming more and more interested in a transparent and coherent image of the cloud, where performance is guaranteed in a variety of situations and under a variety of loads. In this essay, We examine the advantages of an integrated scalability approach at various cloud stack layers, concentrating on the database and compute infrastructure layers. In order to achieve this, we offer various performance measurements and a set of rules based on them to assess the cloud stack’s condition and scale it as needed to maintain stable performance. Then, using a proof-of-concept architecture, we empirically investigate three scaling scenarios for cloud performance: database only, computing infrastructure solely, and the scenario where computing infrastructure and database compete for resources.