Andere Kunden interessierten sich auch für
![Discovery of association rules in datasets via evolutionary algorithms]( "Discovery of association rules in datasets via evolutionary algorithms")
Discovery of association rules in datasets via evolutionary algorithms36,99 €![Large Scale Support Vector Machines Algorithms for Visual Recognition]( "Large Scale Support Vector Machines Algorithms for Visual Recognition")
Large Scale Support Vector Machines Algorithms for Visual Recognition51,99 €![Large-Scale Information Dissemination utilizing Distributed Networks]( "Large-Scale Information Dissemination utilizing Distributed Networks")
Large-Scale Information Dissemination utilizing Distributed Networks51,99 €![Query-Driven Indexing in Large-Scale Distributed Systems]( "Query-Driven Indexing in Large-Scale Distributed Systems")
Query-Driven Indexing in Large-Scale Distributed Systems38,99 €![The Discovery of Interacting Episodes and Temporal Rule Determination]( "The Discovery of Interacting Episodes and Temporal Rule Determination")
The Discovery of Interacting Episodes and Temporal Rule Determination51,99 €![Data Integration in Large Scale]( "Data Integration in Large Scale")
Data Integration in Large Scale32,99 €![Rough Set and Statistical Approach to Knowledge Discovery]( "Rough Set and Statistical Approach to Knowledge Discovery")
Rough Set and Statistical Approach to Knowledge Discovery51,99 €
There is a growing interest in discovery of internet
topology at the
interface level. A new
generation of highly distributed measurement systems
is currently
being deployed.
Unfortunately, prior to this thesis, the research
community has not
examined the problem
of how to perform such measurements efficiently and
in a network-
friendly manner. In this
book, we make several contributions toward that end.
First, we
show that standard
topology discovery methods are quite inefficient,
repeatedly probing
the same interfaces.
This is a concern, because when scaled up, such
methods will
generate so much traffic that
they will begin to resemble DDoS attacks. As it is
not unusual for a
route tracing monitor
to operate in isolation, we next propose and evaluate
strategies for
reducing redundancy
within a single monitor. We third propose and
evaluate Doubletree, a
cooperative algorithm
that reduces redundancy simultaneously on routers and
end
systems. Finally, we also
provide a generalization of Bloom filters, called
retouched Bloom
filters, that permits false
negatives in addition to false positives and allows a
trade-off
between the two.
topology at the
interface level. A new
generation of highly distributed measurement systems
is currently
being deployed.
Unfortunately, prior to this thesis, the research
community has not
examined the problem
of how to perform such measurements efficiently and
in a network-
friendly manner. In this
book, we make several contributions toward that end.
First, we
show that standard
topology discovery methods are quite inefficient,
repeatedly probing
the same interfaces.
This is a concern, because when scaled up, such
methods will
generate so much traffic that
they will begin to resemble DDoS attacks. As it is
not unusual for a
route tracing monitor
to operate in isolation, we next propose and evaluate
strategies for
reducing redundancy
within a single monitor. We third propose and
evaluate Doubletree, a
cooperative algorithm
that reduces redundancy simultaneously on routers and
end
systems. Finally, we also
provide a generalization of Bloom filters, called
retouched Bloom
filters, that permits false
negatives in addition to false positives and allows a
trade-off
between the two.