Abstract: The cloud heralds a new era of computing where application services are provided through the Internet. Cloud computing can enhance the computing capability of mobile systems, but is it the ultimate solution for extending such systems' battery lifetimes?

Abstract: Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world However, existing systems do not support mechanisms and policies for dynamically coordinating load distribution among different Cloud-based data centers in order to determine optimal location for hosting application services to achieve reasonable QoS levels Further, the Cloud computing providers are unable to predict geographic distribution of users consuming their services, hence the load coordination must happen automatically, and distribution of services must change in response to changes in the load To counter this problem, we advocate creation of federated Cloud computing environment (InterCloud) that facilitates just-in-time, opportunistic, and scalable provisioning of application services, consistently achieving QoS targets under variable workload, resource and network conditions The overall goal is to create a computing environment that supports dynamic expansion or contraction of capabilities (VMs, services, storage, and database) for handling sudden variations in service demands. This paper presents vision, challenges, and architectural elements of InterCloud for utility-oriented federation of Cloud computing environments The proposed InterCloud environment supports scaling of applications across multiple vendor clouds We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit The results demonstrate that federated Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

Abstract: While many public cloud providers offer pay-as-you-go computing, their varying approaches to infrastructure, virtualization, and software services lead to a problem of plenty. To help customers pick a cloud that fits their needs, we develop CloudCmp, a systematic comparator of the performance and cost of cloud providers. CloudCmp measures the elastic computing, persistent storage, and networking services offered by a cloud along metrics that directly reflect their impact on the performance of customer applications. CloudCmp strives to ensure fairness, representativeness, and compliance of these measurements while limiting measurement cost. Applying CloudCmp to four cloud providers that together account for most of the cloud customers today, we find that their offered services vary widely in performance and costs, underscoring the need for thoughtful provider selection. From case studies on three representative cloud applications, we show that CloudCmp can guide customers in selecting the best-performing provider for their applications.

Abstract: The Cloud computing emerges as a new computing paradigm which aims to provide reliable, customized and QoS guaranteed dynamic computing environments for end-users. In this paper, we study the Cloud computing paradigm from various aspects, such as definitions, distinct features, and enabling technologies. This paper brings an introductional review on the Cloud computing and provides the state-of-the-art of Cloud computing technologies.

Abstract: Cloud computing services allow users to lease computing resources from large scale data centers operated by service providers. Using cloud services, users can deploy a wide variety of applications dynamically and on-demand. Most cloud service providers use machine virtualization to provide flexible and cost-effective resource sharing. However, few studies have investigated the impact of machine virtualization in the cloud on networking performance. In this paper, we present a measurement study to characterize the impact of virtualization on the networking performance of the Amazon Elastic Cloud Computing (EC2) data center. We measure the processor sharing, packet delay, TCP/UDP throughput and packet loss among Amazon EC2 virtual machines. Our results show that even though the data center network is lightly utilized, virtualization can still cause significant throughput instability and abnormal delay variations. We discuss the implications of our findings on several classes of applications.

Abstract: Advances in Cloud computing opens up many new possibilities for Internet applications developers. Previously, a main concern of Internet applications developers was deployment and hosting of applications, because it required acquisition of a server with a fixed capacity able to handle the expected application peak demand and the installation and maintenance of the whole software infrastructure of the platform supporting the application. Furthermore, server was underutilized because peak traffic happens only at specific times. With the advent of the Cloud, deployment and hosting became cheaper and easier with the use of pay-peruse flexible elastic infrastructure services offered by Cloud providers. Because several Cloud providers are available, each one offering different pricing models and located in different geographic regions, a new concern of application developers is selecting providers and data center locations for applications. However, there is a lack of tools that enable developers to evaluate requirements of large-scale Cloud applications in terms of geographic distribution of both computing servers and user workloads. To fill this gap in tools for evaluation and modeling of Cloud environments and applications, we propose CloudAnalyst. It was developed to simulate large-scale Cloud applications with the purpose of studying the behavior of such applications under various deployment configurations. CloudAnalyst helps developers with insights in how to distribute applications among Cloud infrastructures and value added services such as optimization of applications performance and providers incoming with the use of Service Brokers.

Abstract: Cloud computing has seen tremendous growth, particularly for commercial web applications. The on-demand, pay-as-you-go model creates a flexible and cost-effective means to access compute resources. For these reasons, the scientific computing community has shown increasing interest in exploring cloud computing. However, the underlying implementation and performance of clouds are very different from those at traditional supercomputing centers. It is therefore critical to evaluate the performance of HPC applications in today’s cloud environments to understand the tradeoffs inherent in migrating to the cloud. This work represents the most comprehensive evaluation to date comparing conventional HPC platforms to Amazon EC2, using real applications representative of the workload at a typical supercomputing center. Overall results indicate that EC2 is six times slower than a typical mid-range Linux cluster, and twenty times slower than a modern HPC system. The interconnect on the EC2 cloud platform severely limits performance and causes significant variability.

Abstract: Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

Abstract: The anticipated uptake of Cloud computing, built on well-established research in Web Services, networks, utility computing, distributed computing and virtualisation, will bring many advantages in cost, flexibility and availability for service users. These benefits are expected to further drive the demand for Cloud services, increasing both the Cloud's customer base and the scale of Cloud installations. This has implications for many technical issues in Service Oriented Architectures and Internet of Services (IoS)-type applications; including fault tolerance, high availability and scalability. Central to these issues is the establishment of effective load balancing techniques. It is clear the scale and complexity of these systems makes centralized assignment of jobs to specific servers infeasible; requiring an effective distributed solution. This paper investigates three possible distributed solutions proposed for load balancing; approaches inspired by Honeybee Foraging Behaviour, Biased Random Sampling and Active Clustering.

Abstract: In the last few years, cloud computing has grown from being a promising business concept to one of the fastest growing segments of the IT industry. Now, recession-hit companies are increasingly realizing that simply by tapping into the cloud they can gain fast access to best-of-breed business applications or drastically boost their infrastructure resources, all at negligible cost. But as more and more information on individuals and companies is placed in the cloud, concerns are beginning to grow about just how safe an environment it is. This paper discusses security issues, requirements and challenges that cloud service providers (CSP) face during cloud engineering. Recommended security standards and management models to address these are suggested for technical and business community.

Abstract: Well-known security experts decipher the most challenging aspect of cloud computing-security Cloud computing allows for both large and small organizations to have the opportunity to use Internet-based services so that they can reduce start-up costs, lower capital expenditures, use services on a pay-as-you-use basis, access applications only as needed, and quickly reduce or increase capacities. However, these benefits are accompanied by a myriad of security issues, and this valuable book tackles the most common security challenges that cloud computing faces. The authors offer you years of unparalleled expertise and knowledge as they discuss the extremely challenging topics of data ownership, privacy protections, data mobility, quality of service and service levels, bandwidth costs, data protection, and support. As the most current and complete guide to helping you find your way through a maze of security minefields, this book is mandatory reading if you are involved in any aspect of cloud computing. Coverage Includes: Cloud Computing Fundamentals Cloud Computing Architecture Cloud Computing Software Security Fundamentals Cloud Computing Risks Issues Cloud Computing Security Challenges Cloud Computing Security Architecture Cloud Computing Life Cycle Issues Useful Next Steps and Approaches

Abstract: To become an industry platform, vendors must open their infrastructure technology to other product companies.

Abstract: Cloud computing emerges as one of the hottest topic in field of information technology. Cloud computing is based on several other computing research areas such as HPC, virtualization, utility computing and grid computing. In order to make clear the essential of cloud computing, we propose the characteristics of this area which make cloud computing being cloud computing and distinguish it from other research areas. The cloud computing has its own conceptional, technical, economic and user experience characteristics. The service oriented, loose coupling, strong fault tolerant, business model and ease use are main characteristics of cloud computing. Clear insights into cloud computing will help the development and adoption of this evolving technology both for academe and industry.

Abstract: As an emerging technology and business paradigm, Cloud Computing has taken commercial computing by storm. Cloud computing platforms provide easy access to a company’s high-performance computing and storage infrastructure through web services. With cloud computing, the aim is to hide the complexity of IT infrastructure management from its users. At the same time, cloud computing platforms provide massive scalability, 99.999% reliability, high performance, and specifiable configurability. These capabilities are provided at relatively low costs compared to dedicated infrastructures. This article gives a quick introduction to cloud storage. It covers the key technologies in Cloud Computing and Cloud Storage, several different types of clouds services, and describes the advantages and challenges of Cloud Storage after the introduction of the Cloud Storage reference model.

Abstract: Cloud computing promises a number of advantages for the deployment of data-intensive applications. One important promise is reduced cost with a pay-as-you-go business model. Another promise is (virtually) unlimited throughput by adding servers if the workload increases. This paper lists alternative architectures to effect cloud computing for database applications and reports on the results of a comprehensive evaluation of existing commercial cloud services that have adopted these architectures. The focus of this work is on transaction processing (i.e., read and update workloads), rather than analytics or OLAP workloads, which have recently gained a great deal of attention. The results are surprising in several ways. Most importantly, it seems that all major vendors have adopted a different architecture for their cloud services. As a result, the cost and performance of the services vary significantly depending on the workload.

Abstract: To date, conversations about cloud computing have been dominated by vendors who focus more on technology and less on business value. While it is still not fully agreed as to what components constitute cloud computing technology, some examples of its potential uses are emerging. We identify seven cloud capabilities that executives can use to formulate cloud-based strategies. Firms can change the mix of these capabilities to develop cloud strategies for unique competitive benefits. We predict that cloud strategies will lead to more intense ecosystem-based competition; it is therefore imperative that companies prepare for such a future now.

Abstract: The cloud is a next generation platform that provides dynamic resource pools, virtualization, and high availability. Today, we have the ability to utilize scalable, distributed computing environments within the confines of the Internet, a practice known as cloud computing. Cloud computing is the Concept Implemented to decipher the Daily Computing Problems, likes of Hardware Software and Resource Availability unhurried by Computer users. The cloud Computing provides an undemanding and Non ineffectual Solution for Daily Computing. The prevalent Problem Associated with Cloud Computing is the Cloud security and the appropriate Implementation of Cloud over the Network. In this Research Paper, we have tried to assess Cloud Storage Methodology and Data Security in cloud by the Implementation of digital signature with RSA algorithm

Abstract: Efficient task scheduling mechanism can meet users' requirements, and improve the resource utilization, thereby enhancing the overall performance of the cloud computing environment. But the task scheduling in grid computing is often about the static task requirements, and the resources utilization rate is also low. According to the new features of cloud computing, such as flexibility, virtualization and etc, this paper discusses a two levels task scheduling mechanism based on load balancing in cloud computing. This task scheduling mechanism can not only meet user's requirements, but also get high resource utilization, which was proved by the simulation results in the CloudSim toolkit.

Abstract: Cloud computing is a new form of technology, which infrastructure, developing platform, software, and storage can be delivered as a service in a pay as you use cost model. However, for critical business application and more sensitive information, cloud providers must be selected based on high level of trustworthiness. In this paper, we present a trust model to evaluate cloud services in order to help cloud users select the most reliable resources. We integrate our previous work “conceptual SLA framework for cloud computing” with the proposed trust management model to present a new solution of defining the reliable criteria for the selection process of cloud providers

Abstract: Cloud computing is emerging as an alternative computing platform to bridge the gap between scientists' growing computational demands and their computing capabilities. A scientist who wants to run HPC applications can obtain massive computing resources 'in the cloud' quickly (in minutes), as opposed to days or weeks it normally takes under traditional business processes. Due to the popularity of Amazon EC2, most HPC-in-the-cloud research has been conducted using EC2 as a target platform. Previous work has not investigated how results might depend upon the cloud platform used. In this paper, we extend previous research to three public cloud computing platforms. In addition to running classical benchmarks, we also port a 'full-size' NASA climate prediction application into the cloud, and compare our results with that from dedicated HPC systems. Our results show that 1) virtualization technology, which is widely used by cloud computing, adds little performance overhead; 2) most current public clouds are not designed for running scientific applications primarily due to their poor networking capabilities. However, a cloud with moderately better network (vs. EC2) will deliver a significant performance improvement. Our observations will help to quantify the improvement of using fast networks for running HPC-in-the-cloud, and indicate a promising trend of HPC capability in future private science clouds. We also discuss techniques that will help scientists to best utilize public cloud platforms despite current deficiencies.

Abstract: Disclosed is a management service that enables a user to establish, monitor, and control cloud computing sessions offered via third-party service providers. In some instances, the management service establishes a market space that allows a user to establish a customized cloud computing session based on computing resources offered by third-party service providers. In some instances, the management service instantiates monitoring mechanisms within the virtual servers of the cloud computing sessions to be able to monitor, assess, and provide reports and alerts pertaining to performance metrics of the various virtual servers. In some instances, the management service also allows a user to remotely transfer services from a first cloud computing session to a second cloud computing session.

Abstract: Cloud computing, a rapidly developing information technology, has aroused the concern of the whole world. Cloud computing is Internet-based computing, whereby shared resources, software and information, are provided to computers and devices on-demand, like the electricity grid [1]. Cloud computing is the product of the fusion of traditional computing technology and network technology like grid computing, distributed computing parallel computing and so on. It aims to construct a perfect system with powerful computing capability through a large number of relatively low-cost computing entity, and using the advanced business models like SaaS (Software as a Service), PaaS (Platform as a Service), IaaS (Infrastructure as a Service) to distribute the powerful computing capacity to end users' hands. This article introduces the background and service model of cloud computing. This article also introduces the existing issues in cloud computing such as security, privacy, reliability and so on. Proposition of solution for these issues has been provided also.

Abstract: Assessing the strengths, weaknesses, and general applicability of the computing-as-utility business model.

Abstract: In the introductory chapter we define the concept of cloud computing and cloud services, and we introduce layers and types of cloud computing. We discuss the differences between cloud computing and cloud services. New technologies that enabled cloud computing are presented next. We also discuss cloud computing features, standards, and security issues. We introduce the key cloud computing platforms, their vendors, and their offerings. We discuss cloud computing challenges and the future of cloud computing.

Abstract: Cloud computing provides people the way to share distributed resources and services that belong to different organizations or sites. Since cloud computing share distributed resources via the network in the open environment, thus it makes security problems important for us to develop the cloud computing application. In this paper, we pay attention to the security requirements in cloud computing environment. We proposed a method to build a trusted computing environment for cloud computing system by integrating the trusted computing platform into cloud computing system. We propose a model system in which cloud computing system is combined with trusted computing platform with trusted platform module. In this model, some important security services, including authentication, confidentiality and integrity, are provided in cloud computing system.

Abstract: The success of the Cloud Computing paradigm may be jeopardized by concerns about the risk of misuse of this model aimed at conducting illegal activities. In this paper we address the issue of detecting Denial of Service attacks performed by means of resources acquired on-demand on a Cloud Computing platform. To this purpose, we propose to investigate the consequences of the use of a distributed strategy to detect and block attacks, or other malicious activities, originated by misbehaving customers of a Cloud Computing provider. In order to check the viability of our approach, we also evaluate the impact on performance of our proposed solution. This paper presents the installation and deployment experience of a distributed defence strategy and illustrates the preliminary results of the performance evaluation.

Abstract: Embodiments relate to systems and methods for a cross-vendor mapping service in cloud networks. A mapping service can be provided external to one or more sets of clouds which can access vendor databases in those clouds, and generate reports on software compatibility for software resources available in those diverse cloud networks. A user in an original cloud may wish to construct an image of a set of appliances or other services or entities in a second, external cloud or clouds. The external target cloud(s) may have different application sets, and/or applications available from different vendors, than those software resources hosted in the original cloud. A mapping service external to the participating clouds can enumerate the applications or other resources available in an external cloud, and generate a mapping or translation of those components to construct desired appliance images in that destination. Subscription terms can also be translated between clouds.