Keyword Specific Cloud Computing

It is now a known fact that Internet of things (Iot) and Cloud computing will be the way ahead. Store and transmit of massive amounts of data is on the cards in the coming years which will profoundly affect other areas of everyday life in the next generation. Cloud and Iot are merged together is seen as an enabler of a large number of application scenarios. As an example at the start of 2016 automakers are building a driverless taxi service. Keeping this in mind a novel idea of keyword based Cloud Computing is brought about in this paper which gives out entire data to the user if the user types the keyword of the required entity

Cloud and HPC Headway for Next-Generation Management of Projects and Technologies

In the last decade, cloud computing has changed dramatically. More providers and administration contributions have entered the market, and cloud infrastructure, once limited to single-provider data centers, is expanding. This article discusses the shifting cloud foundation and the benefits of decentralizing computing from data centers. These patterns necessitate novel cloud computing architectures. These models may affect linking people and devices, data-intensive computing, the service space, and self-learning frameworks. Finally, we compiled a list of issues to consider while assessing modern cloud frameworks. Architectural and urban design projects breach scale and predictability constraints and seek enhanced competency, maintainability, energy performance, and cost-efficiency. Simulation and large-scale information processing drive this cycle. Advances in calculations and computer power help address the complex elements of a coordinated whole-structure framework. Adaptability is a barrier to the configuration, control, and development of whole-system frameworks. This position paper proposes several solutions for semi-or fully automated projects, such as short-plan boundary space exploration, large-scope high-accuracy simulation, and integrated multidisciplinary development. These computer-intensive operations were previously only accessible to the exam network. Once empowered by cloud computing and high-performance computing, these methods can stimulate intelligent plan measures, leading to enhanced results and shorter development times

A Model Driven Framework for Portable Cloud Services

Cloud Computing is an evolving technology as it offers significant benefits like pay only for what you use, scale the resources according to the needs and less in-house staff and resources. These benefits have resulted in tremendous increase in the number of applications and services hosted in the cloud which inturn has resulted in increase in the number of cloud providers in the market. Cloud service providers have a lot of heterogeneity in the resources they use. They have their own servers, different cloud infrastructures, API’s and methods to access the cloud resources. Despite its benefits; lack of standards among service providers has caused a high level of vendor lock-in when a software developer tries to change its cloud provider. In this paper we give an overview on the ongoing and current trends in the area of cloud service portability and we also propose a new cloud portability platform. Our new platform is based on establishing feature models which offers the desired cloud portability. Our solution DSkyL uses feature models and domain model analysis to support development, customization and deployment of application components across multiple clouds. The main goal of our approach is to reduce the effort and time needed for porting applications across different clouds. This paper aims to give an overview on DSkyL

Implications of Integration and Interoperability for Enterprise Cloud-based Applications

Enterprise’s adoption of cloud-based solutions is often hindered by problems associated with the integration of the cloud environment with on-premise systems. Currently, each cloud provider creates its proprietary application programing interfaces (APIs), which will complicate integration efforts for companies as they struggle to understand and manage these unique application interfaces in an interoperable way. This paper aims to address this challenge by providing recommendations to enterprises. The presented work is based on a quantitative study of 114 companies, which discuss current issues and future trends of integration and interoperability requirements for enterprise cloud application adoption and migration. The outcome of the discussion provides a guideline applicable to support decision makers, software architects and developers when considering to design and develop interoperable applications in order to avoid lock-in and integrate seamlessly into other cloud and on-premise systems

Cloud Abstraction Libraries: Implementation and Comparison

Vendor lock-in makes it difficult for an organization to port their services, application or data. Cloud providers are in race to provide the best-in-class storage, networking and compute resources. Many organizations are moving towards micro-services and cloud services architecture. It is very important for an infrastructure platform to offer a high-quality cloud computing environment consistently across multiple cloud platforms. To enable this, a collaborative yet an independent cloud abstraction service is required. The cloud abstraction library should support the basic use cases of delivery pipeline, service management, cloud operations and security service. Cloud interoperability standards helps to improve availability and scalability by providing cross organizational or vendor independent projects. An important aspect of cloud interoperability is development of standardized APIs to send and receive data, irrespective of the underlying cloud implementation. Cloud interoperability helps application and data portability between public clouds and private clouds. This thesis explores the role of open source libraries to use cloud specific features. Our work is to qualitatively and quantitatively evaluate Dasein cloud and jClouds against Amazon EC2 and Google Compute Engine. We believe that cloud standardization can be accelerated by implementations based on open source and open standards

Next Generation Cloud Computing: New Trends and Research Directions

The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201

Cloud application portability: an initial view.

Growing interest towards cloud application platforms has resulted in a large number of platform offerings to be already available on the market and new related products to be continuously launched. However, there are a number of challenges that prevent cloud application platforms from becoming widely adopted. One such challenge is application portability. This paper reports on an ongoing effort to explore the area of cloud application portability. We briefly examine the issue of heterogeneity in cloud platforms and highlight specific platform characteristics that may hinder the portability of cloud applications. We present some high level approaches and existing work that attempts to address this challenge. In order to narrow down the area of our exploration we have been carrying out an experiment in cross-platform application development and deployment with four prominent cloud platforms: OpenShift, Google App Engine, Heroku, and Amazon Elastic Beanstalk. We briefly discuss our initial conclusions from this ongoing experimentation