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Using Virtualization to Improve Software Rejuvenation

Authors: Luís Moura Silva; Javier Alonso 0001; Paulo Silva; Jordi Torres; Artur Andrzejak 0001;

Using Virtualization to Improve Software Rejuvenation

Abstract

In this paper, we present an approach for software rejuvenation based on automated self-healing techniques that can be easily applied to off-the-shelf Application Servers and Internet sites. Software aging and transient failures are detected through continuous monitoring of system data and performability metrics of the application server. If some anomalous behavior is identified the system triggers an automatic rejuvenation action. This self-healing scheme is meant to be the less disruptive as possible for the running service and to get a zero downtime for most of the cases. In our scheme, we exploit the usage of virtualization to optimize the self-recovery actions. The techniques described in this paper have been tested with a set of open-source Linux tools and the XEN virtualization middleware. We conducted an experimental study with two applications benchmarks (Tomcat/Axis and TPC-W). Our results demonstrate that virtualization can be extremely helpful for software rejuvenation and fail-over in the occurrence of transient application failures and software aging.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    22
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Average
Top 10%
Top 10%
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