Title:	A HIERARCHICAL ARCHITECTURE FOR ON-LINE CONTROL OF PRIVATE CLOUD-BASED SYSTEMS
Author(s):	Mauro Andreolini, Sara Casolari, Stefania Tosi
ISBN:	978-972-8939-25-0
Editors:	Bebo White, Pedro Isaías and Diana Andone
Year:	2010
Edition:	Single
Keywords:	Cloud computing, architecture, design, statistical models, anomaly detection, hierarchical
Type:	Full Paper
First Page:	201
Last Page:	210
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	Several enterprise data centers are adopting the private cloud computing paradigm as a scalable, cost-effective, robust way to provide services to their end users. The management and control of the underlying hw/sw infrastructure pose several interesting problems. In this paper we are interested to evidence that the monitoring process needs to scale to thousands of heterogeneous resources at different levels (system, network, storage, application) and at different time scales; it has to cope with missing data and detect anomalies in the performance samples; it has to transform all data into meaningful information and pass it to the decision process (possibly through different, ad-hoc algorithms for different resources). In most cases of interest for this paper, the control management system must operate under real-time constraints. We propose a hierarchical architecture that is able to support the efficient orchestration of an on-line management mechanism for a private cloud-based infrastructure. This architecture integrates a framework that collects samples from monitors, validates and aggregates them. We motivate the choice of a hierarchical scheme and show some data manipulation, orchestration and control strategies at different time scales. We then focus on a specific context referring to mid-term management objectives. We have applied the proposed hierarchical architecture successfully to data centers made of a large number of nodes that require short to mid-term control and in our experience we can conclude that it is a viable approach for the control of private cloud-based systems.
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