Fr. 79.00

Study on Batch Balancing for Mainframe Environments - Scaling Systems

English · Paperback / Softback

Shipping usually within 2 to 3 weeks (title will be printed to order)

Description

Read more

Over the years, several innovations have emerged to provide greater processing capacity at a lower cost. Among these new technologies, distributed computing and its applications such as server clustering can be highlighted, which despite allowing a scalar increase in productivity, introduced new difficulties such as the management of several servers and the guarantee that they have balanced performances. Load scaler systems have been targets of studies for decades, and despite being found in the form of specialized equipment or as software components, no architectural evaluations of this type of system have been found, even because the fact that they are software systems is often ignored, being considered only as resources or architectural tactics used to improve performance and increase availability. The use of architectural techniques, in a practical example of a platform little studied in academia, will allow the documentation of the steps that can be reused in similar environments.

About the author










The Author is a Support Analyst with 29 years of experience in large IBM operating systems. Developer of performance improvement solutions and tools in general. Extensive experience in Assembler programming as well as IBM products in general.

Product details

Authors Ituriel do Nascimento Neto
Publisher Our Knowledge Publishing
 
Languages English
Product format Paperback / Softback
Released 28.03.2023
 
EAN 9786205845196
ISBN 9786205845196
No. of pages 116
Subjects Guides
Natural sciences, medicine, IT, technology > IT, data processing

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.