Autonomic Management of Clustered Applications

Bouchenak, Sara; Palma, Noël De; Hagimont, Daniel; Taton, Christophe

doi:10.1109/clustr.2006.311842

Cited by 50 publications

(34 citation statements)

References 12 publications

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“…For example, Sicard et al [59] show that the combination of wiring, hierarchy management, property, identity, and lifecycle are required meta-level capabilities in a component model to fully support self-repair capacities in a component-based distributed system. The same reconfiguration capabilities have been exploited to automate overload management in componentbased cluster systems [9]. …”

Section: Personality Level: Implementing the Sca Standardmentioning

confidence: 99%

“…The FRACTAL model has been used as a basis for the development of several kinds of configurable middleware platforms, and has been successfully used for building automated, architecture-based, distributed systems management capabilities, including deployment and (re)configuration management capabilities [1,14,18,25], self-repair capabilities [8,59], overload management capabilities [9], and self-protection capabilities [16]. The FRACTAL model is currently defined by a formal specification [40] based on the Alloy language [32].…”

Section: Kernel Level: Defining a Reflective Component Modelmentioning

confidence: 99%

“…For example, Listing 1 depicts the descriptor corresponding to the assembly of Figure 1. The composite MyApp (lines 1-20) encloses two components: View (lines [3][4][5][6][7][8][9][10][11][12] and Model (lines [13][14][15][16][17][18]. In addition, MyApp exposes the service interface run (line 2), which is promoted from View.…”

Section: Introductionmentioning

confidence: 99%

“…View and Model are implemented in Java by the classes SwingGuiImpl (line 4) and ModelImpl (line 14), respectively. View provides the service interface run (lines 5-7) and requires the service interface model (lines [8][9][10], which is provided by the component Model (lines [15][16][17]. The explicit wiring between these two service interfaces is specified in line 19.…”

Section: Introductionmentioning

confidence: 99%

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A component‐based middleware platform for reconfigurable service‐oriented architectures

et al. 2011

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SUMMARY ThetextitService Component Architecture (SCA) is a technology‐independent standard for developing distributed Service‐oriented Architectures (SOA). The SCA standard promotes the use of components and architecture descriptors, and mostly covers the lifecycle steps of implementation and deployment. Unfortunately, SCA does not address the governance of SCA applications and provides no support for the maintenance of deployed components. This article covers this issue and introduces the FRASCATI platform, a run‐time support for SCA with dynamic reconfiguration capabilities and run‐time management features. This article presents the internal component‐based architecture of the FRASCATI platform, and highlights its key features. The component‐based design of the FRASCATI platform introduces many degrees of flexibility and configurability in the platform itself and it can host the SOA applications. This article reports on micro‐benchmarks highlighting that run‐time manageability in the FRASCATI platform does not decrease its performance when compared with the de facto reference SCA implementation: Apache TUSCANY. Finally, a smart home scenario illustrates the extension capabilities and the various reconfigurations of the FRASCATI platform. Copyright © 2011 John Wiley & Sons, Ltd.

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Section: Personality Level: Implementing the Sca Standardmentioning

confidence: 99%

Section: Kernel Level: Defining a Reflective Component Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A component‐based middleware platform for reconfigurable service‐oriented architectures

et al. 2011

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“…Most self-management proposals that have been prototyped and can be applied in a real setting, reduce to a simple feedback control loops to adapt system parameters or structure [3], thus failing to properly address continuous change. The adaptation policy is defined explicitly by administrators for the system as a whole and the ability to foresee and cope with the impact of design and development decisions is thus limited.…”

Section: Introductionmentioning

confidence: 99%

Measuring Software Systems Scalability for Proactive Data Center Management

Carvalho

Pereira

2010

On the Move to Meaningful Internet Systems, OTM 2010

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Abstract. The current trend of increasingly larger Web-based applications makes scalability the key challenge when developing, deploying, and maintaining data centers. At the same time, the migration to the cloud computing paradigm means that each data center hosts an increasingly complex mix of applications, from multiple owners and in constant evolution. Unfortunately, managing such data centers in a cost-effective manner requires that the scalability properties of the hosted workloads to be accurately known, namely, to proactively provision adequate resources and to plan the most economical placement of applications. Obviously, stopping each of them and running a custom benchmark to asses its scalability properties is not an option. In this paper we address this challenge with a tool to measure the software scalability regarding CPU availability, to predict system behavior in face of varying resources and an increasing workload. This tool does not depend on a particular application and relies only on Linux's SystemTap probing infrastructure. We validate the approach first using simulation and then in an actual system. The resulting better prediction of scalability properties should allow improved (self-)management practices.

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A survey on performance management for internet applications

Guitart

Torres

AyguadÃ©

2009

Concurrency and Computation

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Internet applications have become indispensable for many business and personal processes, turning the performance of these applications into a key issue. For this reason, recent research has comprehensively explored mechanisms for managing the performance of these applications, with special focus on dealing with overload situations and providing QoS guarantees to clients. This paper makes a survey on the different proposals in the literature for managing Internet applications' performance. We present a complete taxonomy that characterizes and classifies these proposals into several categories including request scheduling, admission control, service differentiation, dynamic resource management, service degradation, control theoretic approaches, works using queuing models, observation-based approaches that use runtime measurements, and overall approaches combining several mechanisms. For each work, we provide a brief description in order to provide the reader with a global understanding of the research progress in this area.

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Autonomic Management of Clustered Applications

Cited by 50 publications

References 12 publications

A component‐based middleware platform for reconfigurable service‐oriented architectures

A component‐based middleware platform for reconfigurable service‐oriented architectures

Measuring Software Systems Scalability for Proactive Data Center Management

A survey on performance management for internet applications

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