Related papers: Emulating a computing grid in a local environment …
Cloud computing is the next generation computing. Adopting the cloud computing is like signing up new form of a website. The GUI which controls the cloud computing make is directly control the hardware resource and your application. The…
Computer Technology has Revolutionized Science. This has motivated scientists to develop mathematical model to simulate salient features of Physical universe. These models can approximate reality at many levels of scale such as atomic…
Increasing complexity in the power system and the transformation towards a smart grid lead to the necessity of new tools and methods for the development and testing of new technologies. One testing method is co-simulation, which allows…
The ATLAS experiment at CERN relies on a worldwide distributed computing Grid infrastructure to support its physics program at the Large Hadron Collider. ATLAS has integrated cloud computing resources to complement its Grid infrastructure…
Computational grids that couple geographically distributed resources are becoming the de-facto computing platform for solving large-scale problems in science, engineering, and commerce. Software to enable grid computing has been primarily…
Since the mid 1990s, grid computing systems have emerged as an analogy for making computing power as pervasive an easily accessible as an electric power grid. Since then, grid computing systems have been shown to be able to provide very…
As computing energy demand continues to grow and electrical grid infrastructure struggles to keep pace, an increasing number of data centers are being planned with colocated microgrids that integrate on-site renewable generation and energy…
Cloud computing focuses on delivery of reliable, secure, fault-tolerant, sustainable, and scalable infrastructures for hosting Internet-based application services. These applications have different composition, configuration, and deployment…
Computational grids are believed to be the ultimate framework to meet the growing computational needs of the scientific community. Here, the processing power of geographically distributed resources working under different ownerships, having…
Many cluster similarity indices are used to evaluate clustering algorithms, and choosing the best one for a particular task remains an open problem. We demonstrate that this problem is crucial: there are many disagreements among the…
One way of characterizing the topological and structural properties of vertices and edges in a graph is by using structural similarity measures. Measures like Cosine, Jaccard and Dice compute the similarities restricted to the immediate…
The rapid growth of demanding applications in domains applying multimedia processing and machine learning has marked a new era for edge and cloud computing. These applications involve massive data and compute-intensive tasks, and thus,…
Resource discovery is one of the most important services that significantly affects the efficiency of grid computing systems. The inherent dynamic and large-scale characteristics of grid environments make their resource discovery a…
Cloud-based software systems are increasingly becoming complex and operating in highly dynamic environments. Self-adaptivity and self-awareness have recently emerged to cope with such level of dynamicity and scalability. Meanwhile,…
Cyber-physical power systems, such as grids, integrate computational and communication components with physical systems to introduce novel functions and improve resilience and fault tolerance. These systems employ computational components…
In the context of cluster analysis and graph partitioning, many external evaluation measures have been proposed in the literature to compare two partitions of the same set. This makes the task of selecting the most appropriate measure for a…
This thesis introduces a set of methods for testing models of modified gravity using galaxy clusters. In particular, a technique for constraining models with a chameleon screening is introduced. In addition, the outlined technique is…
The increased integration of information and communications technology at the distribution grid level offers broader opportunities for active operational management concepts. At the same time, requirements for resilience against internal…
We investigate a fundamental aspect of machine vision: the measurement of features, by revisiting clustering, one of the most classic approaches in machine learning and data analysis. Existing visual feature extractors, including ConvNets,…
Grid computing is a collection of computer resources that are gathered together from various areas to give computational resources such as storage, data or application services. This is to permit clients to access this huge measure of…