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Record Nr. |
UNINA9910293143903321 |
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Autore |
John P. Morrison |
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Titolo |
Heterogeneity, High Performance Computing, Self-Organization and the Cloud / / edited by Theo Lynn, John P. Morrison, David Kenny |
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Pubbl/distr/stampa |
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2018 |
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Cham : , : Springer International Publishing : , : Imprint : Palgrave Macmillan, , 2018 |
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ISBN |
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Edizione |
[1st ed. 2018.] |
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Descrizione fisica |
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1 online resource (XXI, 165 p. 46 illus.) |
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Collana |
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Palgrave Studies in Digital Business & Enabling Technologies, , 2662-1290 |
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Classificazione |
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BUS070000BUS070030BUS083000BUS087000COM032000 |
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Disciplina |
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Soggetti |
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Quantitative research |
Business logistics |
Industries |
Electronic data processing - Management |
Computer systems |
Data Analysis and Big Data |
Logistics |
IT Operations |
Computer System Implementation |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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1 Addressing the Complexity of HPC in the Cloud: Emergence, Self-Organisation, Self-Management and the Separation of Concerns -- 2 Cloud Architectures and Management Approaches -- 3 Self-organising, Self-Managing Frameworks and Strategies -- 4 Application Blueprints and Service Description -- Simulating Heterogeneous Clouds at Scale -- Concluding Remarks. |
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Sommario/riassunto |
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This open access book addresses the most recent developments in cloud computing such as HPC in the Cloud, heterogeneous cloud, self-organising and self-management, and discusses the business implications of cloud computing adoption. Establishing the need for a new architecture for cloud computing, it discusses a novel cloud |
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management and delivery architecture based on the principles of self-organisation and self-management. This focus shifts the deployment and optimisation effort from the consumer to the software stack running on the cloud infrastructure. It also outlines validation challenges and introduces a novel generalised extensible simulation framework to illustrate the effectiveness, performance and scalability of self-organising and self-managing delivery models on hyperscale cloud infrastructures. It concludes with a number of potential use cases for self-organising, self-managing clouds and the impact on those businesses. |
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