Towards an open cloud marketplace: vision and first steps

As one of the most promising, emerging concepts in Information Technology (IT), cloud computing is transforming how IT is consumed and managed; yielding improved cost efficiencies, and delivering flexible, on-demand scalability by reducing computing infrastructures, platforms, and services to commodities acquired and paid-for on-demand through a set of cloud providers. Today, the transition of cloud computing from a subject of research and innovation to a critical infrastructure is proceeding at an incredibly fast pace. A potentially dangerous consequence of this speedy transition to practice is the premature adoption, and ossification, of the models, technologies, and standards underlying this critical infrastructure. This state of affairs is exacerbated by the fact that innovative research on production-scale platforms is becoming the purview of a small number of public cloud providers. Specifically, the academic research communities are effectively excluded from the opportunity to contribute meaningfully to the evolution not to mention innovation and healthy mutation of cloud computing technologies. As the dependence on our society and economy on cloud computing increases, so does the realization that the academic research community cannot be shut out from contributing to the design and evolution of this critical infrastructure. In this article we provide an alternative vision that of an Open Cloud eXchange (OCX) a public cloud marketplace, where many stakeholders, rather than just a single cloud provider, participate in implementing and operating the cloud, thus creating an ecosystem that will bring the innovation of a broader community to bear on a much healthier and more efficient cloud marketplace

Cloudbus Toolkit for Market-Oriented Cloud Computing

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of Cloud applications and deployment on private or public Clouds, in addition to supporting market-oriented resource management; (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party Cloud brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green Clouds; and (vi) pathways for future research.Comment: 21 pages, 6 figures, 2 tables, Conference pape

Mainroad: cloud computing

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economic

Business Integration as a Service

This paper presents Business Integration as a Service (BIaS) which enables connections between services operating in the Cloud. BIaS integrates different services and business activities to achieve a streamline process. We illustrate this integration using two services; Return on Investment (ROI) Measurement as a Service (RMaaS) and Risk Analysis as a Service (RAaaS) in two case studies at the University of Southampton and Vodafone/Apple. The University of Southampton case study demonstrates the cost-savings and the risk analysis achieved, so two services can work as a single service. The Vodafone/Apple case study illustrates statistical analysis and 3D Visualisation of expected revenue and associated risk. These two cases confirm the benefits of BIaS adoption, including cost reduction and improvements in efficiency and risk analysis. Implementation of BIaS in other organisations is also discussed. Important data arising from the integration of RMaaS and RAaaS are useful for management of University of Southampton and potential and current investors for Vodafone/Apple

An innovative IoT service for medical diagnosis

Due to the misdiagnose of diseases that increased recently in a scarily manner, many researchers devoted their efforts and deployed technologies to improve the medical diagnosis process and reducing the resulted risk. Accordingly, this paper proposed architecture of a cyber-medicine service for medical diagnosis, based internet of things (IoT) and cloud infrastructure (IaaS). This service offers a shared environment for medical data, and extracted knowledge and findings between patients and doctors in an interactive, secured, elastic and reliable way. It predicts the medical diagnosis and provides an appropriate treatment for the given symptoms and medical conditions based on multiple classifiers to assure high accuracy. Moreover, it entails different functionalities such as on-demand searching for scientific papers and diseases description for unrecognized combination of symptoms using web crawler to enrich the results. Where such searching results from crawler, are processed, analyzed and added to the resident knowledge base (KB) to achieve adaptability and subsidize the service predictive ability

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

Spatially localized management companies using cloud technology

Poslovne aplikacije i softverske platforme prelaze u cloud okruženje. Ovaj rad ima za cilj analizu nove generacije alata koji se koriste u industrijskoj proizvodnji zajedno sa cloud tehnologijama. Decenije pred nama će obeležiti nov način komunikacije u poslovnim okruženjima telekomunikacija i medicine kao i industrijske proizvodnje i energetske efikasnosti. Standarde poslovne aplikacije i instalacije softvera zahtevaju značajna finansijska sredstva i troškove za hardver. Sa tim u vezi postoji potreba za timovima stručnjaka za instalaciju, testiranje i održavanje sistema. Novi pristup aplikacijama ovoj oblasti donosi nove načine ažuriranja softvera koje je automatsko, sa lakim pristupom aplikacijama bez obzira gde se prostorno nalazite.Content - Business applications and software platforms crossing in the cloud environment. This paper analyses new generation of management tools in industrial production with cloud technologies. The decades ahead will be marked by a new way of communication in business environments from telecommunication field to medicine as well as industrial production and energy efficiency. Standard business applications and software with its installation and maintenance require considerable financial resources and significant spending on hardware. To address that requirement there is the need for special teams of experts to install, test and maintain the system. The new approach to cloud applications brings to this field that what is needed, a software update is automatic with an easy access to applications efficiently from anywhere on the planet and spatially are independent where you are located

Opportunity and Implementation of Cloud Computing in Indian Health Sector

In this paper I am dealing with the effectiveness of cloud computing technologies in health care information systems. Health care, like other service operation, requires consistent and systematic innovation in order to remain cost effective, efficient and timely to provide high-quality services. The health care industry is generally considered a slow in adoption of technology. In the last few years, expectations about patient privacy information, medical services, data retention and health care provider availability have risen dramatically. For solving such kind of issues I suggest the electronic health care systems using cloud computing techniques. Cloud technology reduces the time delay and more time can be spared for patient care. In this paper I discuss the cloud computing evolution, how can the health care industries use the cloud computing and improves the service to patient in India, challenges of cloud in health care and benefits of cloud techniques in health care industries

Literature Based Study On Cloud Computing For Health And Sustainability In View Of Covid19

The modern age of technology is trending with digitalization and reshaping the business around the world. Advancement of new technologies and innovations are transforming businesses in numerous ways and creating a whole new business computational ecosystem. Most often professionals are across the globe are talking about terms like digitization, Industry 4.0, Big Data, Block chain Technologies, cloud computing, 3D Printing, Machine Learning, Automation, Artificial Intelligence (AI), Internet of Things (IoT), Data mining etc. Amidst, all the major advanced technologies mentioned above, Cloud Computing, is one of the fast emerging into a large scale computing system with seamless access to virtually limitless resources. Just to apprise how the computing systems works before cloud computing ;technically to elucidate, Server-That was the past, back in the days say 20 years ago every company used to have its own server. In computing, a server is a computer program or a device that provides functionality for other programs or devices. A server is basically a very large computer (just like a mainframe) with its own set of hardware which includes a sophisticated processor capable of handling huge workloads from the office clients. On top of these servers the Operating System (OS) was installed and the applications were placed on these OS. The server will contain all the database of that particular organization and all the concerned in that organization will have access to that data stored in that server through WAN (Wide Area Network) or LAN (Local Area Network). The data stored in these servers can be anything ranging from stock record, records of all transactions or even application or email service. Typical servers are Database servers, CatLog server, File Servers, Print Servers, Sound Server, Media Server, Mail Server, Proxy servers, Web servers, Game Servers, Application servers etc. Hence, to maintain such server facility and proper functionality, it’s becoming daunting task for small and big companies too. As such huge investment, technical expertise, IT infrastructure, vendors, manpower, security , licensing, overall maintenance cost shall gradually become untenable. Then come “Revolutionizing Computing systems called ‘Cloud computing” which is supposed to be totally changed scenario of computational systems. Since it is cheap, no need to hire professional IT to maintain server, no wastage of money on acquiring server OS licensing, user friendly. Hence, it could be sustained in small and big companies/enterprises easily. Coronavirus, now declared as pandemic, is causing widespread shutdown and chaos. The rapid spread and global impact of COVID-19 can make people feel helpless and scared as the novel coronavirus escalates and forces them to change many aspects of their respective lives. It is clear that the world needs a quick & safe solution right now to combat further spread of coronavirus . What then is the best solution to this health crisis? This is where technologies such as cloud computing, AI & machine learning come into play. It will be very interesting to see how cloud computing will address and contribute towards these issues in the healthcare system & industry. The purpose of this paper is to explore the current state, status and trends of cloud computing in health system in view of covid-19

Service Quality Assessment for Cloud-based Distributed Data Services

The issue of less-than-100% reliability and trust-worthiness of third-party controlled cloud components (e.g., IaaS and SaaS components from different vendors) may lead to laxity in the QoS guarantees offered by a service-support system S to various applications. An example of S is a replicated data service to handle customer queries with fault-tolerance and performance goals. QoS laxity (i.e., SLA violations) may be inadvertent: say, due to the inability of system designers to model the impact of sub-system behaviors onto a deliverable QoS. Sometimes, QoS laxity may even be intentional: say, to reap revenue-oriented benefits by cheating on resource allocations and/or excessive statistical-sharing of system resources (e.g., VM cycles, number of servers). Our goal is to assess how well the internal mechanisms of S are geared to offer a required level of service to the applications. We use computational models of S to determine the optimal feasible resource schedules and verify how close is the actual system behavior to a model-computed \u27gold-standard\u27. Our QoS assessment methods allow comparing different service vendors (possibly with different business policies) in terms of canonical properties: such as elasticity, linearity, isolation, and fairness (analogical to a comparative rating of restaurants). Case studies of cloud-based distributed applications are described to illustrate our QoS assessment methods. Specific systems studied in the thesis are: i) replicated data services where the servers may be hosted on multiple data-centers for fault-tolerance and performance reasons; and ii) content delivery networks to geographically distributed clients where the content data caches may reside on different data-centers. The methods studied in the thesis are useful in various contexts of QoS management and self-configurations in large-scale cloud-based distributed systems that are inherently complex due to size, diversity, and environment dynamicity