The design and development of a mobile workflow learning application

The aim of this research is the implementation of a Software Reference Architecture for WfLMS (Workflow Learning Management Systems) with Mobile, Cloud and Collaborative functionalities in order to develop a WFLMS as a native application for the iOS platform. Workflow Learning is the adaptation of WfMS (Workflow Management Systems) from the business domain in the learning domain. Cesarini et al. (2004) support the e-learning process with a WfMS and makes a perfect adaptation of the learning process as a Workflow, explains in a simple way that a Workflow which is made by participants, actions, documents and a set of procedural rules, can be adapted in a learning environment, the actors involved in the learning process are the participants, the learning activities are the actions, the artifacts students can produce are the documents and the relationship among the learning topics are the procedural rules. The Reference Architecture has been adapted in order to provide the best WfLMS solution, taking advantage of the cloud, mobile and collaborative functionalities for the learning environment. The Notification Tools module in the Reference Architecture contains the notification tools for keeping the user updated about the state of the Workflow Learning instances, tasks and activities where the user is collaborating. Push notifications and Twitter were used as the principal notification tools. The Collaboration and Storage Applications in the Cloud module is the repository of the cloud collaborative applications and the storage management applications in the cloud. Google Drive, Dropbox and Evernote are the mobile cloud applications for supporting the collaboration in the WfLMS. The Mobile Services Tool module contains the API’s for accessing the mobile services available in the cloud, in that way the mobile workflow learning application can extend its functionalities. The functionalities that social media services offer are key for the collaboration in the WfLMS. Cloud Content Management System Tool module contains the API’s for connecting with the storage services in the cloud (Dropbox, Drive and Evernote), in order to provide the functionality of a content management system (CMS) in the WfLMS The implementation of the software architecture was the development of a native application for the iOS platform. The application was published in the Apple Store with the name of WOLF (Work Linear Flow). In the WOLF application, the users can create projects and associate Workflows to them, a Twitter hashtag is created for each project so in that way the users can post tweets about the learning activities that are related to the Workflows, the project and communicate with other users for collaboration. The users can open Twitter inside WOLF in order to see the list of tweets related to the hashtags of the projects.Postprint (published version

Intelligent Management and Efficient Operation of Big Data

This chapter details how Big Data can be used and implemented in networking and computing infrastructures. Specifically, it addresses three main aspects: the timely extraction of relevant knowledge from heterogeneous, and very often unstructured large data sources, the enhancement on the performance of processing and networking (cloud) infrastructures that are the most important foundational pillars of Big Data applications or services, and novel ways to efficiently manage network infrastructures with high-level composed policies for supporting the transmission of large amounts of data with distinct requisites (video vs. non-video). A case study involving an intelligent management solution to route data traffic with diverse requirements in a wide area Internet Exchange Point is presented, discussed in the context of Big Data, and evaluated.Comment: In book Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence, IGI Global, 201

weSPOT: a cloud-based approach for personal and social inquiry

Scientific inquiry is at the core of the curricula of schools and universities across Europe. weSPOT is a new European initiative proposing a cloud-based approach for personal and social inquiry. weSPOT aims at enabling students to create their mashups out of cloud-based tools in order to perform scientific investigations. Students will also be able to share their inquiry accomplishments in social networks and receive feedback from the learning environment and their peers

The edge cloud: A holistic view of communication, computation and caching

The evolution of communication networks shows a clear shift of focus from just improving the communications aspects to enabling new important services, from Industry 4.0 to automated driving, virtual/augmented reality, Internet of Things (IoT), and so on. This trend is evident in the roadmap planned for the deployment of the fifth generation (5G) communication networks. This ambitious goal requires a paradigm shift towards a vision that looks at communication, computation and caching (3C) resources as three components of a single holistic system. The further step is to bring these 3C resources closer to the mobile user, at the edge of the network, to enable very low latency and high reliability services. The scope of this chapter is to show that signal processing techniques can play a key role in this new vision. In particular, we motivate the joint optimization of 3C resources. Then we show how graph-based representations can play a key role in building effective learning methods and devising innovative resource allocation techniques.Comment: to appear in the book "Cooperative and Graph Signal Pocessing: Principles and Applications", P. Djuric and C. Richard Eds., Academic Press, Elsevier, 201

Medical data processing and analysis for remote health and activities monitoring

Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

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