On a Catalogue of Metrics for Evaluating Commercial Cloud Services

Given the continually increasing amount of commercial Cloud services in the market, evaluation of different services plays a significant role in cost-benefit analysis or decision making for choosing Cloud Computing. In particular, employing suitable metrics is essential in evaluation implementations. However, to the best of our knowledge, there is not any systematic discussion about metrics for evaluating Cloud services. By using the method of Systematic Literature Review (SLR), we have collected the de facto metrics adopted in the existing Cloud services evaluation work. The collected metrics were arranged following different Cloud service features to be evaluated, which essentially constructed an evaluation metrics catalogue, as shown in this paper. This metrics catalogue can be used to facilitate the future practice and research in the area of Cloud services evaluation. Moreover, considering metrics selection is a prerequisite of benchmark selection in evaluation implementations, this work also supplements the existing research in benchmarking the commercial Cloud services.Comment: 10 pages, Proceedings of the 13th ACM/IEEE International Conference on Grid Computing (Grid 2012), pp. 164-173, Beijing, China, September 20-23, 201

How can startups make use of cloud services

The purpose of this project is to discuss the technical obstacles that small and medium-sized enterprises (SMEs) face, as well as how cloud computing can help to solve these issues. Cloud computing has the ability to radically change competitive environments by offering a new forum for generating and delivering business value and market development. Small and medium-sized enterprises (SMEs) also lack sufficient technological capital. They could either buy expensive software customized by large companies or develop their own low-cost applications with limited functionality. The research questions answered in this project are as follows: 1. How can a startup build a cost-effective website and host it on a cloud platform? 2. How can a startup make a website always available? 3. How can a startup resolve the low latency problem using cloud services? 4. How can a startup make use of different cloud services to reduce the use of infrastructure and technology resources. The methodology used for this project is to understand what is cloud computing, cloud implementation models, cloud computing services, and their benefits. The Implementation Solution is offered by evaluating various cloud vendors such as AWS and Microsoft Azure and the various services they provide. This study provides a realistic demonstration of designing and hosting a website in AWS and Microsoft Azure to support this approach. This study offers insights and suggestions to SMEs for implementing various cloud services to achieve economies of scale. The project concluded that cloud computing is simple to use, inexpensive, eliminates the need for physical office space, and eliminates the need to transport storage devices. Because of its scalability and faster content delivery, as well as various business models, the cloud is an excellent choice for startups

Scientific Workflow Applications on Amazon EC2

The proliferation of commercial cloud computing providers has generated significant interest in the scientific computing community. Much recent research has attempted to determine the benefits and drawbacks of cloud computing for scientific applications. Although clouds have many attractive features, such as virtualization, on-demand provisioning, and "pay as you go" usage-based pricing, it is not clear whether they are able to deliver the performance required for scientific applications at a reasonable price. In this paper we examine the performance and cost of clouds from the perspective of scientific workflow applications. We use three characteristic workflows to compare the performance of a commercial cloud with that of a typical HPC system, and we analyze the various costs associated with running those workflows in the cloud. We find that the performance of clouds is not unreasonable given the hardware resources provided, and that performance comparable to HPC systems can be achieved given similar resources. We also find that the cost of running workflows on a commercial cloud can be reduced by storing data in the cloud rather than transferring it from outside

High-Performance Cloud Computing: A View of Scientific Applications

Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a Service Level Agreement (SLA), which ensure the desired Quality of Service (QoS). Aneka, an enterprise Cloud computing solution, harnesses the power of compute resources by relying on private and public Clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the Cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape

Cloud computing models

Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 79-80).Information Technology has always been considered a major pain point of enterprise organizations, from the perspectives of both cost and management. However, the information technology industry has experienced a dramatic shift in the past decade - factors such as hardware commoditization, open-source software, virtualization, workforce globalization, and agile IT processes have supported the development of new technology and business models. Cloud computing now offers organizations more choices regarding how to run infrastructures, save costs, and delegate liabilities to third-party providers. It has become an integral part of technology and business models, and has forced businesses to adapt to new technology strategies. Accordingly, the demand for cloud computing has forced the development of new market offerings, representing various cloud service and delivery models. These models significantly expand the range of available options, and task organizations with dilemmas over which cloud computing model to employ. This thesis poses analysis of available cloud computing models and potential future cloud computing trends. Comparative analysis includes cloud services delivery (SaaS, PaaS, IaaS) and deployment models (private, public, and hybrid). Cloud computing paradigms are discussed in the context of technical, business, and human factors, analyzing how business and technology strategy could be impacted by the following aspects of cloud computing: --Architecture --Security --Costs --Hardware/software trends (commodity vs. brands, open vs. closed-source) --Organizational/human Factors To provide a systematic approach to the research presented in this paper, cloud taxonomy is introduced to classify and compare the available cloud service offerings. In particular, this thesis focuses on the services of a few major cloud providers. Amazon Web Services (AWS) will be used as a base in many examples because this cloud provider represents approximately 70% of the current public cloud services market. Amazon's AWS has become a cloud services trend-setter, and a reference point for other cloud service providers. The analysis of cloud computing models has shown that public cloud deployment model is likely to stay dominant and keep expanding further. Private and Hybrid deployment models are going to stay for years ahead but their market share is going to continuously drop. In the long-term private and Hybrid cloud models most probably will be used only for specific business cases. IaaS service delivery model is likely to keep losing market share to PaaS and SaaS models because companies realize more value and resource-savings from software and platform services rather than infrastructure. In the near future we can expect significant number of market consolidations with few large players retaining market control at the end.by Eugene Gorelik.S.M.in Engineering and Managemen

Cloud Computing for Digital Libraries

Information management systems (digital libraries/repositories, learning management systems, content management systems) provide key technologies for the storage, preservation and dissemination of knowledge in its various forms, such as research documents, theses and dissertations, cultural heritage documents and audio files. These systems can make use of cloud computing to achieve high levels of scalability, while making services accessible to all at reasonable infrastructure costs and on-demand. This research aims to develop techniques for building scalable digital information management systems based on efficient and on-demand use of generic grid-based technologies such as cloud computing. In particular, this study explores the use of existing cloud computing resources offered by some popular cloud computing vendors such as Amazon Web Services. This involves making use of Amazon Simple Storage Service (Amazon S3) to store large and increasing volumes of data, Amazon Elastic Compute Cloud (Amazon EC2) to provide the required computational power and Amazon SimpleDB for querying and data indexing on Amazon S3. A proof-of-concept application comprising typical digital library services was developed and deployed in the cloud environment and evaluated for scalability when the demand for more data and services increases. The results from the evaluation show that it is possible to adopt cloud computing for digital libraries in addressing issues of massive data handling and dealing with large numbers of concurrent requests. Existing digital library systems could be migrated and deployed into the cloud

An analysis of the cloud computing platform

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2009.Includes bibliographical references.A slew of articles have been written about the fact that computing will eventually go in the direction of electricity. Just as most software users these days also own the hardware that runs the software, electricity users in the days of yore used to generate their own power. However, over time with standardization in voltage and frequency of generated power and better distribution mechanisms the generation of electricity was consolidated amongst fewer utility providers. The same is being forecast for computing infrastructure. Its is being touted that more and more users will rent computing infrastructure from a utility or "cloud" provider instead of maintaining their own hardware. This phenomenon or technology is being referred to Cloud Computing or Utility Computing. Cloud computing has been in existence in some form or the other since the beginning of computing. However, the advent of vastly improved software, hardware and communication technologies has given special meaning to the term cloud computing and opened up a world of possibilities. It is possible today to start an ecommerce or related company without investing in datacenters. This has turned out to be very beneficial to startups and smaller companies that want to test the efficacy of their idea before making any investment in expensive hardware. Corporations like Amazon, SalesForce.com, Google, IBM, Sun Microsystems, and many more are offering or planning to offer these infrastructure services in one form or another.(cont.) An ecosystem has already been created and going by the investment and enthusiasm in this space the ecosystem is bound to grow. This thesis tries to define and explain the fundamentals of cloud computing. It looks at the technical aspects of this industry and the kind of applications where cloud can be used. It also looks at the economic value created by the platform, the network externalities, its effect on traditional software companies and their reaction to this technology. The thesis also tries to apply the principle of multi-homing, coring and tipping to the cloud-computing platform and explain the results. The hurdles for both users and providers of this service are also examined in this thesis.by Ratnadeep Bhattacharjee.S.M