Run Time Models Self Managing Systems (11 results)

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Condition: New. Focuses on the adoption of run-time models for the design and management of autonomic systems. This book includes techniques and solutions for the run-time estimation of autonomic systems performance, the analysis of transient conditions and their application in prototype environments. Editor(s): Ardagna, Danilo; Zhang, Li. Series: Autonomic Systems. Num Pages: 194 pages, biography. BIC Classification: UGK; UKR; UMB. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 10. Weight in Grams: 320. . 2010. Paperback. . . . .

Paperback. Condition: Brand New. 174 pages. 9.00x6.00x0.50 inches. In Stock.

Condition: New. Focuses on the adoption of run-time models for the design and management of autonomic systems. This book includes techniques and solutions for the run-time estimation of autonomic systems performance, the analysis of transient conditions and their application in prototype environments. Editor(s): Ardagna, Danilo; Zhang, Li. Series: Autonomic Systems. Num Pages: 194 pages, biography. BIC Classification: UGK; UKR; UMB. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 10. Weight in Grams: 320. . 2010. Paperback. . . . . Books ship from the US and Ireland.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The complexity of Information Technology (IT) systems has been steadily incre- ing in the past decades. In October 2001, IBM released the 'Autonomic Computing Manifesto' observing that current applications have reached the size of millions of lines of code, while physical infrastructures include thousands of heterogeneous servers requiring skilled IT professionals to install, con gure, tune, and maintain. System complexity has been recognized as the main obstacle to the further advan- ment of IT technology. The basic idea of Autonomic Computing is to develop IT systems that are able to manage themselves, as the human autonomic nervous system governs basic body functions such as heart rate or body temperature, thus freeing the conscious brain- IT administrators-from the burden of dealing with low-level vital functions. Autonomic Computing systems can be implemented by introducing autonomic controllers which continuously monitor, analyze, plan, and execute (the famous MAPE cycle) recon guration actions on the system components. Monitoring acti- ties are deployed to measure the workload and performance metrics of each running component so as to identify system faults. The goal of the analysis activities is to determine the status of components from the monitoring data, and to forecast - ture conditions based on historical observations. Finally, plan and execute activities aim at deciding and actuating the next system con guration, for example, deciding whether to accept or reject new requests, determining the best application to servers assignment, in order to the achieve the self-optimization goals.

Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | The complexity of Information Technology (IT) systems has been steadily incre- ing in the past decades. In October 2001, IBM released the ¿Autonomic Computing Manifestö observing that current applications have reached the size of millions of lines of code, while physical infrastructures include thousands of heterogeneous servers requiring skilled IT professionals to install, con?gure, tune, and maintain. System complexity has been recognized as the main obstacle to the further advan- ment of IT technology. The basic idea of Autonomic Computing is to develop IT systems that are able to manage themselves, as the human autonomic nervous system governs basic body functions such as heart rate or body temperature, thus freeing the conscious brain¿ IT administrators¿from the burden of dealing with low-level vital functions. Autonomic Computing systems can be implemented by introducing autonomic controllers which continuously monitor, analyze, plan, and execute (the famous MAPE cycle) recon?guration actions on the system components. Monitoring acti- ties are deployed to measure the workload and performance metrics of each running component so as to identify system faults. The goal of the analysis activities is to determine the status of components from the monitoring data, and to forecast - ture conditions based on historical observations. Finally, plan and execute activities aim at deciding and actuating the next system con?guration, for example, deciding whether to accept or reject new requests, determining the best application to servers assignment, in order to the achieve the self-optimization goals.

Condition: new. Questo è un articolo print on demand.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The complexity of Information Technology (IT) systems has been steadily incre- ing in the past decades. In October 2001, IBM released the 'Autonomic Computing Manifesto' observing that current applications have reached the size of millions of lines of code, while physical infrastructures include thousands of heterogeneous servers requiring skilled IT professionals to install, con gure, tune, and maintain. System complexity has been recognized as the main obstacle to the further advan- ment of IT technology. The basic idea of Autonomic Computing is to develop IT systems that are able to manage themselves, as the human autonomic nervous system governs basic body functions such as heart rate or body temperature, thus freeing the conscious brain- IT administrators-from the burden of dealing with low-level vital functions. Autonomic Computing systems can be implemented by introducing autonomic controllers which continuously monitor, analyze, plan, and execute (the famous MAPE cycle) recon guration actions on the system components. Monitoring acti- ties are deployed to measure the workload and performance metrics of each running component so as to identify system faults. The goal of the analysis activities is to determine the status of components from the monitoring data, and to forecast - ture conditions based on historical observations. Finally, plan and execute activities aim at deciding and actuating the next system con guration, for example, deciding whether to accept or reject new requests, determining the best application to servers assignment, in order to the achieve the self-optimization goals. 184 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Investigate concepts, models and tools for the run-time management of autonomic computing systems at very fine-grained time scales and in transient conditions Introduces the main challenges and future re- search directions for the adoption of run-time model.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The complexity of Information Technology (IT) systems has been steadily incre- ing in the past decades. In October 2001, IBM released the ¿Autonomic Computing Manifestö observing that current applications have reached the size of millions of lines of code, while physical infrastructures include thousands of heterogeneous servers requiring skilled IT professionals to install, con gure, tune, and maintain. System complexity has been recognized as the main obstacle to the further advan- ment of IT technology. The basic idea of Autonomic Computing is to develop IT systems that are able to manage themselves, as the human autonomic nervous system governs basic body functions such as heart rate or body temperature, thus freeing the conscious brain¿ IT administrators¿from the burden of dealing with low-level vital functions. Autonomic Computing systems can be implemented by introducing autonomic controllers which continuously monitor, analyze, plan, and execute (the famous MAPE cycle) recon guration actions on the system components. Monitoring acti- ties are deployed to measure the workload and performance metrics of each running component so as to identify system faults. The goal of the analysis activities is to determine the status of components from the monitoring data, and to forecast - ture conditions based on historical observations. Finally, plan and execute activities aim at deciding and actuating the next system con guration, for example, deciding whether to accept or reject new requests, determining the best application to servers assignment, in order to the achieve the self-optimization goals.Springer Nature c/o IBS, Benzstrasse 21, 48619 Heek 184 pp. Englisch.