Challenges of cloud technology in manufacturing environment

The rapid growth Information systems and advanced network technologies have significant impact on enterprises around the world. Enterprises are trying to gain competitive advantage in open global markets by using the latest technologies, along with advanced networks, to create collaboration, reduce costs, and maximize productivity. The combination of latest technologies and advanced manufacturing networks technologies lead to growth of new manufacturing model named Cloud Manufacturing which can shift the manufacturing industry from product-oriented manufacturing to services-oriented manufacturing. This paper explores the literature about the current Manufacturing problems, understands the concept of Cloud Computing Technology, introduces Cloud Manufacturing and its role in the enterprise, and investigates the obstacles and challenges of adopting Cloud Manufacturing in enterprises

How can SMEs benefit from big data? Challenges and a path forward

Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the ‘state-of-the-art’ of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd.Peer ReviewedPostprint (author's final draft

A Secure and Fair Resource Sharing Model for Community Clouds

Cloud computing has gained a lot of importance and has been one of the most discussed segment of today\u27s IT industry. As enterprises explore the idea of using clouds, concerns have emerged related to cloud security and standardization. This thesis explores whether the Community Cloud Deployment Model can provide solutions to some of the concerns associated with cloud computing. A secure framework based on trust negotiations for resource sharing within the community is developed as a means to provide standardization and security while building trust during resource sharing within the community. Additionally, a model for fair sharing of resources is developed which makes the resource availability and usage transparent to the community so that members can make informed decisions about their own resource requirements based on the resource usage and availability within the community. Furthermore, the fair-share model discusses methods that can be employed to address situations when the demand for a resource is higher than the resource availability in the resource pool. Various methods that include reduction in the requested amount of resource, early release of the resources and taxing members have been studied, Based on comparisons of these methods along with the advantages and disadvantages of each model outlined, a hybrid method that only taxes members for unused resources is developed. All these methods have been studied through simulations

Toward a framework for data quality in cloud-based health information system

This Cloud computing is a promising platform for health information systems in order to reduce costs and improve accessibility. Cloud computing represents a shift away from computing being purchased as a product to be a service delivered over the Internet to customers. Cloud computing paradigm is becoming one of the popular IT infrastructures for facilitating Electronic Health Record (EHR) integration and sharing. EHR is defined as a repository of patient data in digital form. This record is stored and exchanged securely and accessible by different levels of authorized users. Its key purpose is to support the continuity of care, and allow the exchange and integration of medical information for a patient. However, this would not be achieved without ensuring the quality of data populated in the healthcare clouds as the data quality can have a great impact on the overall effectiveness of any system. The assurance of the quality of data used in healthcare systems is a pressing need to help the continuity and quality of care. Identification of data quality dimensions in healthcare clouds is a challenging issue as data quality of cloud-based health information systems arise some issues such as the appropriateness of use, and provenance. Some research proposed frameworks of the data quality dimensions without taking into consideration the nature of cloud-based healthcare systems. In this paper, we proposed an initial framework that fits the data quality attributes. This framework reflects the main elements of the cloud-based healthcare systems and the functionality of EHR

Cloud computing and prospective business and economic impacts in developing country: A case study of Thailand

The cloud computing model is a modern concept of computation that provides a number of benefits for its adopters. This online computing model has been widely used in the western world and accepted to have some business and economic impacts. This paper provides some basic knowledge about cloud computing along with its economic benefits. The author proposes that there is an endogenous relationship between the cloud computing and each of the business and economic variables, namely output, employment, and labour productivity. In order to forecast the impacts of the cloud computing adoption, the Vector Autoregressive (VAR) model is constructed. Thailand is selected as ground for investigation. Apart from the bi-directional causality, the results also show prospective positive impacts of the cloud computing adoption on the growth of output, employment, and labour productivity. Despite the macroeconomic benefits, some policy implications include the encouragement of the cloud computing adoption in universities and banks in order to realise the benefit of scalability and efficient usage of computing resources. --Cloud computing,Macroeconomic indicators,Forecast,Thailand

Cloud Security : A Review of Recent Threats and Solution Models

The most significant barrier to the wide adoption of cloud services has been attributed to perceived cloud insecurity (Smitha, Anna and Dan, 2012). In an attempt to review this subject, this paper will explore some of the major security threats to the cloud and the security models employed in tackling them. Access control violations, message integrity violations, data leakages, inability to guarantee complete data deletion, code injection, malwares and lack of expertise in cloud technology rank the major threats. The European Union invested €3m in City University London to research into the certification of Cloud security services. This and more recent developments are significant in addressing increasing public concerns regarding the confidentiality, integrity and privacy of data held in cloud environments. Some of the current cloud security models adopted in addressing cloud security threats were – Encryption of all data at storage and during transmission. The Cisco IronPort S-Series web security appliance was among security solutions to solve cloud access control issues. 2-factor Authentication with RSA SecurID and close monitoring appeared to be the most popular solutions to authentication and access control issues in the cloud. Database Active Monitoring, File Active Monitoring, URL Filters and Data Loss Prevention were solutions for detecting and preventing unauthorised data migration into and within clouds. There is yet no guarantee for a complete deletion of data by cloud providers on client requests however; FADE may be a solution (Yang et al., 2012)

Towards Business Integration as a Service 2.0

Cloud Computing Business Framework (CCBF) is a framework for designing and implementation of Could Computing solutions. This proposal focuses on how CCBF can help to address linkage in Cloud Computing implementations. This leads to the development of Business Integration as a Service 1.0 (BIaS 1.0) allowing different services, roles and functionalities to work together in a linkage-oriented framework where the outcome of one service can be input to another, without the need to translate between domains or languages. BIaS 2.0 aims to allow full automation, enhanced security, advanced risk modelling and improved collaboration between processes in BIaaS 1.0. The benefits from adopting BIaS 1.0 and developing BIaS 2.0 are illustrated using a case study from the University of Southampton and several collaborators including IBM US. BIaS 2.0 can work with mainstream technologies such as scientific workflows, and the proposal and demonstration of BIaaS 2.0 will certainly benefit industry and academia