Related papers: Distributed Resources for the Earth System Grid Ad…
Robotic systems are more connected, networked, and distributed than ever. New architectures that comply with the \textit{de facto} robotics middleware standard, ROS\,2, have recently emerged to fill the gap in terms of hybrid systems…
Edge-cloud collaborative computing (ECCC) has emerged as a pivotal paradigm for addressing the computational demands of modern intelligent applications, integrating cloud resources with edge devices to enable efficient, low-latency…
Decentralized management and coordination of energy systems are emerging trends facilitated by the uptake of the Internet of Things and Blockchain offering new opportunities for more secure, resilient, and efficient energy distribution.…
The initial location of data in DRAMs is determined and controlled by the 'address-mapping' and even modern memory controllers use a fixed and run-time-agnostic address mapping. On the other hand, the memory access pattern seen at the…
The advances in data, computing and networking over the last two decades led to a shift in many application domains that includes machine learning on big data as a part of the scientific process, requiring new capabilities for integrated…
The next generation of scientific experiments and studies, popularly called as e-Science, is carried out by large collaborations of researchers distributed around the world engaged in analysis of huge collections of data generated by…
In this paper, the benefits of distributed energy resources (DERs) are considered in an energy management scheme for a smart community consisting of a large number of residential units (RUs) and a shared facility controller (SFC). A…
Optimal resource utilization for executing tasks within the cloud is one of the biggest challenges. In executing the task over a cloud, the resource provisioner is responsible for providing the resources to create virtual machines. To…
Data in the energy domain grows at unprecedented rates and is usually generated by heterogeneous energy systems. Despite the great potential that big data-driven technologies can bring to the energy sector, general adoption is still…
Network virtualization has caught the attention of many researchers in recent years. It facilitates the process of creating several virtual networks over a single physical network. Despite this advantage, however, network virtualization…
Grid computing (GC) systems are large-scale virtual machines, built upon a massive pool of resources (processing time, storage, software) that often span multiple distributed domains. Concurrent users interact with the grid by adding new…
In many countries, the currently observable transformation of the power supply system from a centrally controlled system towards a complex "system of systems", comprising lots of autonomously interacting components, leads to a significant…
Nowadays, many scientific areas share the same broad requirements of being able to deal with massive and distributed datasets while, when possible, being integrated with services and applications. In order to solve the growing gap between…
We present status and results of AstroGrid-D, a joint effort of astrophysicists and computer scientists to employ grid technology for scientific applications. AstroGrid-D provides access to a network of distributed machines with a set of…
Grid computing is the next logical step to distributed computing. Main objective of grid computing is an innovative approach to share resources such as CPU usage; memory sharing and software sharing. Data Grids provide transparent access to…
In recent years, various kinds of distributed resource sharing setups have been proposed by taking social relationships into consideration. These dissimilar resource sharing setups are tagged as Social Cloud. These setups have appeared in…
Space-air-ground integrated network (SAGIN) is a new type of wireless network mode. The effective management of SAGIN resources is a prerequisite for high-reliability communication. However, the storage capacity of space-air network segment…
In the immediate future holographic technology will be available to store a very large amount of data in HVD (Holographic Versatile Disk) devices. This technology make extensive use of the WORM (Write-Once-Read-Many) paradigm: this means…
We describe the architecture and initial implementation of the next-generation of Grid Data Management Middleware in the EU DataGrid (EDG) project. The new architecture stems out of our experience and the users requirements gathered during…
Distributed machine learning is becoming increasingly popular for geo-distributed data analytics, facilitating the collaborative analysis of data scattered across data centers in different regions. This paradigm eliminates the need for…