Grid Computing — GRID 2001

Author(s):  
Varuna Godara

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.


Author(s):  
Aijun Chen ◽  
Liping Di ◽  
Yuqi Bai ◽  
Yaxing Wei

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.


2020 ◽  
Vol 245 ◽  
pp. 07016
Author(s):  
Tomoe Kishimoto ◽  
Junichi Tnaka ◽  
Tetsuro Mashimo ◽  
Ryu Sawada ◽  
Koji Terashi ◽  
...  

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.


Author(s):  
Kenneth J. Turner ◽  
Paul Lambert ◽  
K. L. Tan ◽  
Vernon Gayle ◽  
Richard O. Sinnott ◽  
...  

Grid computing is named by analogy with the electrical power grid. Power stations are linked into a universal supply that delivers electricity on demand to consumers. Similarly, computational resources can be linked into a grid that delivers computing or data on demand to the user’s desktop. The origins of grid computing lie in networked computing, distributed computing, and parallel computing. Grid computing coordinates distributed resources that are not subject to central control, using standard protocols and interfaces to meet the required levels of service (Foster, 2002).


Author(s):  
Lizhe Wang

This chapter discusses research issues related to agent-based Grid computing. Grid computing now becomes an innovative computing paradigm and helps build non-traditional computing infrastructures and applications. Multiple-agent systems and algorithms, on the other hand, mainly focus on solving corporative problems among multiple participants, mainly from theoretical aspects. It is thus a natural choice to combine these two key technologies together and benefit both research communities. This chapter first reviews background for multi-agent system, agent-based computing, and Grid computing. Research challenges and issues are characterized and identified together with possible solutions. After the investigation of current research efforts of agent-based Grid computing, future research trends are presented and studied.


Author(s):  
Neil Geddes

We present a brief history of the beginnings, development and achievements of the worldwide Large Hadron Collider Computing Grid (wLCG). The wLCG is a huge international endeavour, which is itself embedded within, and directly influences, a much broader computing and information technology landscape. It is often impossible to identify true cause and effect, and they may appear very different from the different perspectives (e.g. information technology industry or academic researcher). This account is no different. It represents a personal view of the developments over the last two decades and is therefore inevitably biased towards those things in which the author has been personally involved.


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