13. Distributed Computing – GRID Computing

2005 ◽  
pp. 193-206
Author(s):  
Andreas Mauthe ◽  
Oliver Heckmann
Keyword(s):  
Distributed Computing ◽  
Grid Computing ◽  
Computing Grid

Architecture and Key Technologies of Cloud Computing

2013 ◽  
Vol 756-759 ◽  
pp. 1953-1956
Author(s):  
Li Yuan Xiao ◽  
Zheng Wang ◽  
Rui Wang ◽  
Hai Ning Wang
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Distributed Computing ◽  
Grid Computing ◽  
The Internet ◽  
Key Technologies ◽  
The Future ◽  
Computing Grid

The Internet has changed the computing world in a drastic way from the advent of the Internet in 1990. The concepts of distributed computing, parallel computing, grid computing and cloud computing have been proposed successively. Although cloud computing is generally recognized as a technology which will has a significant impact on IT in the future. But cloud computing is still in its infancy. In this paper we will discuss the architecture and the key technologies of the cloud computing.

Resource Scheduling for Big Data on Cloud

2016 ◽  
pp. 185-205 ◽  
Author(s):  
K. Indira Suthakar ◽  
M. K. Kavitha Devi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Distributed Computing ◽  
Grid Computing ◽  
Task Scheduling ◽  
Service Providers ◽  
Maximum Profit ◽  
Cloud Computing Service ◽  
Computing Grid ◽  
Scheduling Strategies

Cloud computing is based on the concepts of distributed computing, grid computing, utility computing and virtualization. It is a virtual pool of resources which are provided to users via Internet. It gives users virtually unlimited pay-per-use computing resources without the burden of managing the underlying infrastructure. Cloud computing service providers' one of the goals is to use the resources efficiently and gain maximum profit. This leads to task scheduling as a core and challenging issue in cloud computing. This paper gives different scheduling strategies and algorithms in cloud computing.

Pervasive Computing

2010 ◽  
pp. 234-252
Author(s):  
Varuna Godara
Keyword(s):  
Grid Computing ◽  
Science Fiction ◽  
Pervasive Computing ◽  
Ambient Intelligence ◽  
New Products ◽  
Value Systems ◽  
Smart Environments ◽  
Fiction Writers ◽  
Computing Grid ◽  
Networking Technologies

Pervasive computing is trying to make the dreams of the science fiction writers come true—where you think of some type of convenience and you have it. It appears that pervasive computing is allowing tiny computers, sensors, networking technologies, and human imagination to blend and mould into new products and services. This chapter introduces pervasive computing, grid computing, and ambient intelligence with explanation of how these technologies are merging to create sensor embedded smart environments. Along with description and scope of e-business and m-business, different views of p-business are illustrated. Finally, different smart environments including smart consumer-to-consumer, smart value systems, smart p-education, p-governance, and so forth, are explained.

Grid Computing and its Application to Geoinformatics

2010 ◽  
pp. 213-221
Author(s):  
Aijun Chen ◽  
Liping Di ◽  
Yuqi Bai ◽  
Yaxing Wei
Keyword(s):  
Grid Computing ◽  
Earth Science ◽  
Grid Architecture ◽  
Research Areas ◽  
Computing Grid ◽  
Open Geospatial Consortium ◽  
Definition Of ◽  
Hourglass Model ◽  
Geospatial Services ◽  
Protocol Architecture

The definition of the Grid computing and its application to geoinformatics are introduced. Not only the comparison of power Grid and computing Grid is illustrated, also Web technology and Grid technology are compared. The Hourglass Model of Grid architecture is depicted. The layered Grid architecture, relating to Internet protocol architecture, consists of the fabric (computer, storage, switches, etc.) layer, connectivity layer, resource layer, collective layer, and application layer. Grid computing has been applied to many disciplines and research areas, such as physics, Earth science, astronomy, bioinformatics, etc. By applying the Grid computing to Open Geospatial Consortium, Inc.’s Web services and geospatial standards from International Organization for Standardization, US Federal Geographic Data Committee and US NASA, a geospatial Grid is proposed here, which consisting of Grid-managed geospatial data and Grid-enabled geospatial services.

Cluster and Grid Computing: A Graduate Distributed-Computing Course

2007 ◽  
Vol 8 (12) ◽  
pp. 2-2 ◽  
Author(s):  
Rajkumar Buyya ◽  
Srikumar Venugopal
Keyword(s):  
Distributed Computing ◽  
Grid Computing

Distributed computing research issues in grid computing

2002 ◽  
Vol 33 (3) ◽  
pp. 50-70 ◽  
Author(s):  
Henri Casanova
Keyword(s):  
Distributed Computing ◽  
Grid Computing ◽  
Research Issues

scholarly journals Anomaly detection using Unsupervised Machine Learning for Grid computing site operation

2020 ◽  
Vol 245 ◽  
pp. 07016
Author(s):  
Tomoe Kishimoto ◽  
Junichi Tnaka ◽  
Tetsuro Mashimo ◽  
Ryu Sawada ◽  
Koji Terashi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Anomaly Detection ◽  
Grid Computing ◽  
Machine Learning Techniques ◽  
Storage Element ◽  
Site Administrators ◽  
Grid Middleware ◽  
Learning Techniques ◽  
The Status ◽  
Computing Grid

A Grid computing site is composed of various services including Grid middleware, such as Computing Element and Storage Element. Text logs produced by the services provide useful information for understanding the status of the services. However, it is a time-consuming task for site administrators to monitor and analyze the service logs every day. Therefore, a support framework has been developed to ease the site administrator’s work. The framework detects anomaly logs using Machine Learning techniques and alerts site administrators. The framework has been examined using real service logs at the Tokyo Tier2 site, which is one of the Worldwide LHC Computing Grid sites. In this paper, a method of the anomaly detection in the framework and its performances at the Tokyo Tier2 site are reported.

Sign in / Sign up

Export Citation Format

Share Document