73,384 research outputs found
CloudOps: Towards the Operationalization of the Cloud Continuum: Concepts, Challenges and a Reference Framework
The current trend of developing highly distributed, context aware, heterogeneous computing intense and data-sensitive applications is changing the boundaries of cloud computing. Encouraged by the growing IoT paradigm and with flexible edge devices available, an ecosystem of a combination of resources, ranging from high density compute and storage to very lightweight embedded computers running on batteries or solar power, is available for DevOps teams from what is known as the Cloud Continuum. In this dynamic context, manageability is key, as well as controlled operations and resources monitoring for handling anomalies. Unfortunately, the operation and management of such heterogeneous computing environments (including edge, cloud and network services) is complex and operators face challenges such as the continuous optimization and autonomous (re-)deployment of context-aware stateless and stateful applications where, however, they must ensure service continuity while anticipating potential failures in the underlying infrastructure. In this paper, we propose a novel CloudOps workflow (extending the traditional DevOps pipeline), proposing techniques and methods for applicationsâ operators to fully embrace the possibilities of the Cloud Continuum. Our approach will support DevOps teams in the operationalization of the Cloud Continuum. Secondly, we provide an extensive explanation of the scope, possibilities and future of the CloudOps.This research was funded by the European project PIACERE (Horizon 2020 Research and Innovation Programme, under grant agreement No. 101000162)
CloudOps: Towards the Operationalization of the Cloud Continuum: Concepts, Challenges and a Reference Framework
The current trend of developing highly distributed, context aware, heterogeneous computing intense and data-sensitive applications is changing the boundaries of cloud computing. Encouraged by the growing IoT paradigm and with flexible edge devices available, an ecosystem of a combination of resources, ranging from high density compute and storage to very lightweight embedded computers running on batteries or solar power, is available for DevOps teams from what is known as the Cloud Continuum. In this dynamic context, manageability is key, as well as controlled operations and resources monitoring for handling anomalies. Unfortunately, the operation and management of such heterogeneous computing environments (including edge, cloud and network services) is complex and operators face challenges such as the continuous optimization and autonomous (re-)deployment of context-aware stateless and stateful applications where, however, they must ensure service continuity while anticipating potential failures in the underlying infrastructure. In this paper, we propose a novel CloudOps workflow (extending the traditional DevOps pipeline), proposing techniques and methods for applicationsâ operators to fully embrace the possibilities of the Cloud Continuum. Our approach will support DevOps teams in the operationalization of the Cloud Continuum. Secondly, we provide an extensive explanation of the scope, possibilities and future of the CloudOps.This research was funded by the European project PIACERE (Horizon 2020 Research and Innovation Programme, under grant agreement No. 101000162)
Semantic-based policy engineering for autonomic systems
This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise
FEDGEN Testbed: A Federated Genomics Private Cloud Infrastructure for Precision Medicine and Artificial Intelligence Research
The cloud computing space is enjoying a renaissance. Not long ago, cloud
computing was confined to the wall of high-revenue companies, but in recent
times a growing number of businesses, public and private institutions are
turning to the cloud computing platform to reap the benefits of a self-service,
scalable, and flexible infrastructure. Moreover, with the increased
implementation, advantages, and popularity of artificial intelligence, the
demand for computing environments to solve age-old problems such as
malaria and cancer is on the rise. This paper presents the implementation of a
cloud computing infrastructure, the FEDerated GENomics (FEDGEN) Testbed,
to provide an adequate IT environment for cancer and malaria researchers.
The cloud computing environment is built using Openstack middleware.
OpenStack is deployed using Metal-As-A-Service (MAAS) and Juju. Virtual
Machines (Instances) were deployed, and services (JupiterHub) were installed
on the FEDGEN testbed. The built infrastructure would allow the running of
models requiring high computing power and would allow for collaboration
among teams
Comparative Study on Agile software development methodologies
Today-s business environment is very much dynamic, and organisations are
constantly changing their software requirements to adjust with new environment.
They also demand for fast delivery of software products as well as for
accepting changing requirements. In this aspect, traditional plan-driven
developments fail to meet up these requirements. Though traditional software
development methodologies, such as life cycle-based structured and object
oriented approaches, continue to dominate the systems development few decades
and much research has done in traditional methodologies, Agile software
development brings its own set of novel challenges that must be addressed to
satisfy the customer through early and continuous delivery of the valuable
software. It is a set of software development methods based on iterative and
incremental development process, where requirements and development evolve
through collaboration between self-organizing, cross-functional teams that
allows rapid delivery of high quality software to meet customer needs and also
accommodate changes in the requirements. In this paper, we significantly
identify and describe the major factors, that Agile development approach
improves software development process to meet the rapid changing business
environments. We also provide a brief comparison of agile development
methodologies with traditional systems development methodologies, and discuss
current state of adopting agile methodologies. We speculate that from the need
to satisfy the customer through early and continuous delivery of the valuable
software, Agile software development is emerged as an alternative to
traditional plan-based software development methods. The purpose of this paper,
is to provide an in-depth understanding, the major benefits of agile
development approach to software development industry, as well as provide a
comparison study report of ASDM over TSDM.Comment: 25 pages, 25 images, 86 references used, with authors biographie
Human-agent collectives
We live in a world where a host of computer systems, distributed throughout our physical and information environments, are increasingly implicated in our everyday actions. Computer technologies impact all aspects of our lives and our relationship with the digital has fundamentally altered as computers have moved out of the workplace and away from the desktop. Networked computers, tablets, phones and personal devices are now commonplace, as are an increasingly diverse set of digital devices built into the world around us. Data and information is generated at unprecedented speeds and volumes from an increasingly diverse range of sources. It is then combined in unforeseen ways, limited only by human imagination. Peopleâs activities and collaborations are becoming ever more dependent upon and intertwined with this ubiquitous information substrate. As these trends continue apace, it is becoming apparent that many endeavours involve the symbiotic interleaving of humans and computers. Moreover, the emergence of these close-knit partnerships is inducing profound change. Rather than issuing instructions to passive machines that wait until they are asked before doing anything, we will work in tandem with highly inter-connected computational components that act autonomously and intelligently (aka agents). As a consequence, greater attention needs to be given to the balance of control between people and machines. In many situations, humans will be in charge and agents will predominantly act in a supporting role. In other cases, however, the agents will be in control and humans will play the supporting role. We term this emerging class of systems human-agent collectives (HACs) to reflect the close partnership and the flexible social interactions between the humans and the computers. As well as exhibiting increased autonomy, such systems will be inherently open and social. This means the participants will need to continually and flexibly establish and manage a range of social relationships. Thus, depending on the task at hand, different constellations of people, resources, and information will need to come together, operate in a coordinated fashion, and then disband. The openness and presence of many distinct stakeholders means participation will be motivated by a broad range of incentives rather than diktat. This article outlines the key research challenges involved in developing a comprehensive understanding of HACs. To illuminate this agenda, a nascent application in the domain of disaster response is presented
Flexible virtual environments: Gamifying immersive learning
© Springer International Publishing AG 2017. The availability of Virtual Reality (VR) and Virtual Environment (VE) equipment - with the launch of domestic technologies such as the Oculus Rift, Microsoft Hololens and Sony Playstation VR) - offer new ways to enable interactive immersive experiences [16]. The opportunities these create in learning and training applications are immense: but create new challenges . Meanwhile, current virtual learning environments are typically web or app based technologies, sometimes perceived as having little value added from a user perspective beyond improved User Interfaces to access some content [6]. The challenge is how the human computer interaction features of such VE platforms may be used in education in a way that adds value, especially for computer mediated instruction. This paper will outline some of the issues, and opportunities, as well as some of the open questions about how such technologies can be used effectively in a higher education context, along with a proposed framework for embedding a learning engine within a virtual reality or environment system. Three-dimensional technologies: from work-walls, through CAVES to the latest headsets offer new ways to immerse users in computer generated environments. Immersive learning [1] is increasingly common in training applications, and is beginning to make inroads into formal education. The recent rise in such off-the-shelf technologies means that Augmented Learning becomes a realistic mainstream tool [13]. Much of this use is built in game environments using game engines, where these serious games provide learning effects as an intended consequence of playing
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