A view at desktop clouds

Cloud has emerged as a new computing paradigm that promises to move into computing-as-utility era. Desktop Cloud is a new type of Cloud computing. It merges two computing models: Cloud computing and volunteer computing. The aim of Desktop Cloud is to provide Cloud services out of infrastructure that is not made for this purpose in order to reduce running and maintenance costs. This paper discusses this new type of Cloud by comparing it with current Cloud and Desktop Grid models. It, also, presents several research challenges in Desktop Cloud that require further attention

Clouds of Small Things: Provisioning Infrastructure-as-a-Service from within Community Networks

Community networks offer a shared communication infrastructure where communities of citizens build and own open networks. While the IP connectivity of the networking devices is successfully achieved, the number of services and applications available from within the community network is typically small and the usage of the community network is often limited to providing Internet access to remote areas through wireless links. In this paper we propose to apply the principle of resource sharing of community networks, currently limited to the network bandwidth, to other computing resources, which leads to cloud computing in community networks. Towards this vision, we review some characteristics of community networks and identify potential scenarios for community clouds. We simulate a cloud computing infrastructure service and discuss different aspects of its performance in comparison to a commercial centralized cloud system. We note that in community clouds the computing resources are heterogeneous and less powerful, which affects the time needed to assign resources. Response time of the infrastructure service is high in community clouds even for a small number of resources since resources are distributed, but tends to get closer to that of a centralized cloud when the number of resources requested increases. Our initial results suggest that the performance of the community clouds highly depends on the community network conditions, but has some potential for improvement with network-aware cloud services. The main strength compared to commercial cloud services, however, is that community cloud services hosted on community-owned resources will follow the principles of community network and will be neutral and open

Bonus Computing: An Evolution from and a Supplement to Volunteer Computing

Despite the huge success in various worldwide projects, volunteer computing also suffers from the possible lack of computing resources (one volunteered device can join one project at a time) and from the uncertain job interruptions (the volunteered device can crash or disconnect from the Internet at any time). To relieve the challenges faced by volunteer computing, we have proposed bonus computing that exploits the free quotas of public Cloud resources particularly to deal with problems composed of fine-grained, short-running, and compute-intensive tasks. In addition to explaining the loosely-coupled functional architecture and six architectural patterns of bonus computing in this paper, we also employ the Monte-Carlo approximation of Pi (π) as a use case demonstration both to facilitate understanding and to help validate its functioning mechanism. The results exhibit not only effectiveness but also multiple advantages of bonus computing, which makes it a valuable evolution from and supplement to volunteer computing

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

Personal Volunteer Computing

We propose personal volunteer computing, a novel paradigm to encourage technical solutions that leverage personal devices, such as smartphones and laptops, for personal applications that require significant computations, such as animation rendering and image processing. The paradigm requires no investment in additional hardware, relying instead on devices that are already owned by users and their community, and favours simple tools that can be implemented part-time by a single developer. We show that samples of personal devices of today are competitive with a top-of-the-line laptop from two years ago. We also propose new directions to extend the paradigm

Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth

Geospatial information infrastructures

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Geospatial information infrastructures (GIIs) provide the technological, semantic,organizationalandlegalstructurethatallowforthediscovery,sharing,and use of geospatial information (GI). In this chapter, we introduce the overall concept and surrounding notions such as geographic information systems (GIS) and spatial datainfrastructures(SDI).WeoutlinethehistoryofGIIsintermsoftheorganizational andtechnologicaldevelopmentsaswellasthecurrentstate-of-art,andreflectonsome of the central challenges and possible future trajectories. We focus on the tension betweenincreasedneedsforstandardizationandtheever-acceleratingtechnological changes. We conclude that GIIs evolved as a strong underpinning contribution to implementation of the Digital Earth vision. In the future, these infrastructures are challengedtobecomeflexibleandrobustenoughtoabsorbandembracetechnological transformationsandtheaccompanyingsocietalandorganizationalimplications.With this contribution, we present the reader a comprehensive overview of the field and a solid basis for reflections about future developments

Earth Observation Open Science and Innovation

geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc