An investigation into the cloud manufacturing based approach towards global high value manufacturing for smes

Considering the high labour costs and intensive competitions in the global market, improving the effective deployment of innovative design and manufacturing and utilisation of all existing technical information, for the full life cycle of the product, is essential and much needed for manufacturing Small and Medium sized Enterprises (SMEs) in particular. Cloud Manufacturing , as a powerful tool supported with ‘big data’, will likely enable SMEs to move towards using dynamic scalability and ‘free’ available data resources in a virtual manner and to provide solution-based, value-added, digital-driven manufacturing service over the Internet. The research presented in this paper aims to develop a cloud manufacturing based approach towards value-added, knowledge/solution driven manufacturing for SMEs, where there are many constraints in engaging responsive high value manufacturing. The paper will present the framework, architecture and key moderator technologies for implementing cloud manufacturing and the associated application perspectives. The paper concludes with further discussion on the potential and application of the approach

Cloud-based digital twinning for structural health monitoring using deep learning

Digital Twin technology has recently gathered pace in the engineering communities as it allows for the convergence of the real structure and its digital counterpart throughout their entire life-cycle. With the rapid development of supporting technologies, including machine learning, 5G/6G, cloud computing, and Internet of Things, Digital Twin has been moving progressively from concept to practice. In this paper, a Digital Twin framework based on cloud computing and deep learning for structural health monitoring is proposed to efficiently perform real-time monitoring and proactive maintenance. The framework consists of structural components, device measurements, and digital models formed by combining different sub-models including mathematical, finite element, and machine learning ones. The data interaction among physical structure, digital model, and human interventions are enhanced by using cloud computing infrastructure and a user-friendly web application. The feasibility of the proposed framework is demonstrated via case studies of damage detection of model bridge and real bridge structures using deep learning algorithms, with high accuracy of 92%

A cost engine system for estimating whole-life cycle cost of long-term digital preservation activities

This research paper presents a cost engine system that estimates the whole life cycle cost of long-term digital preservation (LTDP) activities using cloud-based technologies. A qualitative research methodology has been employed and the activity based costing (ABC) technique has been used to develop the cost model. The unified modelling language (UML) notation and the object oriented paradigm (OOP) are utilised to design the architecture of the software system. In addition, the service oriented architecture (SOA) style has been used to deploy the function of the cost engine as a web service in order to ensure its accessibility over the web. The cost engine is a module that is part of a larger digital preservation system and has been validated qualitatively through experts’ opinion. Its benefits are realised in the accurate and detailed estimation of cost for companies wishing to employ LTDP activities

My precious information : How to preserve it?

Do you think your information remains safe inside a cloud? Do you have another truly trustworthy place where you can store all your precious information? These questions lead us to the basic problem behind this paper: None of the official instances are interested in materials possessed by average Joes and Janes. You will have to be politically or otherwise important person to get your personal life story into official digital repositories. We at the Digitalia1 (Research Center on Digital Information Management) at South-Eastern Finland University of Applied Sciences, believe that there is a strong need for a digital preservation service that would give ordinary citizens the right to decide what to do with their personal information. It is not right that common folks must rely on cloud drives with dubious terms and conditions or unreliable portable or optical devices to store their precious digital information. This article describes an initiative of a low cost full-scale digital archive solution that will be available to common people

CloudChain: A novel distribution model for digital products based on supply chain principles

Cloud computing is a popular outsourcing solution for organizations to support the information management during the life cycle of digital information goods. However, outsourcing management with a public provider results in a lack of control over digital products, which could produce incidents such as data unavailability during service outages, violations of confidentiality and/or legal issues. This paper presents a novel distribution model of digital products inspired by lean supply chain principles called CloudChain, which has been designed to support the information management during digital product lifecycle. This model enables connected networks of customers, partners and organizations to conduct the stages of digital product lifecycle as value chains. Virtual distribution channels are created over cloud resources for applications of organizations to deliver digital products to applications of partners through a seamless information flow. A configurable packing and logistic service was developed to ensure confidentiality and privacy in the product delivery by using encrypted packs. A chain management architecture enables organizations to keep tighter control over their value chains, distribution channels and digital products. CloudChain software instances were integrated to an information management system of a space agency. In an experimental evaluation CloudChain prototype was evaluated in a private cloud where the feasibility of applying supply chain principles to the delivery of digital products in terms of efficiency, flexibility and security was revealed.This work was partially funded by the sectorial fund of research, technological development and innovation in space activities of the Mexican National Council of Science and Technology (CONACYT) and the Mexican Space Agency (AEM), project No. 262891

Cloud TAC: OpenStack and Technology Learning and Knowledge for teaching IT Infrastructure

In today's university environment, most students are digital natives. Therefore, it is difficult to imagine their academic life without relating it to the various cloud tools for communication and collaborative work. In this context, university professors work in new scenarios of communication and collaborative work in the classroom. This represents a transformation in the teaching-learning process assisted by new ICTs s in the cloud. Working in the cloud offers the opportunity to transmit new knowledge when using pedagogical strategies supported by computer technologies. With the combination of ICTs and modern teaching-learning processes, the concept of Learning and Knowledge Technologies (TAC) is valuable. This work exposes the academic experience of researching and developing Cloud Computing using an OpenStack configuration so that students can empower themselves with the knowledge and use of cloud technologies. Thus, to be able to teach concepts and practices on IT Infrastructure including activities such as: design, configuration, implementation and administration of a private cloud for academic uses.Instituto de Investigación en InformáticaInstituto de Investigación en Informátic

An efficient cloud based architecture for integrating content management systems

The use of digital content is increasing day after day and now it is an essential element of our day today life. The amount of stored information is so huge that it is highly difficult to manage the content especially in a distributed cloud environment. There are many open source software solutions available in cloud to handle huge amount of digital data. However none of these solutions addresses all the requirements needed to manage the content spread out in multiple systems effectively. The user has to relay on multiple content management systems to do the work. This turns into ever more unwieldy, time consuming and leads to loss of data. Using robust and integrated content management systems, these issues could be solved effectively. In this paper we have identified various challenges of using the content management system in the cloud after surveying many Content Management System related article and proposed an integrated solution named Cloud based Architecture integrating Content Management System which is capable of interfacing with various unique features available at different content management system installations in the cloud. This maximizes the functionality and performance of any Content management systems. The Representational State Transfer (REST) protocol is used to integrate the best features of various open source content management systems. REST provides higher level of security compared to existing systems as it does not store the user sessions. The users can interact with the system with the help of an interface which abstracts the complexities of multiple content management systems running in the cloud. © 2017 IEEE

An energy optimization with improved QOS approach for adaptive cloud resources

In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (ACRR) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model ACRR in terms of average run time, power consumption and average power required than any other state-of-art techniques