Nederlands
Contact
Sitemap
Search
OrganisationEEMCS EPrints Service
 |
|
|
||||||||||||||||||||||||||||||||||
|
|
|
|
|
||||||||||||||||||||||||||||||||
|
|
|
||||||||||||||||||||||||||||||||||
|
|
|
|
|
||||||||||||||||||||||||||||||||
|
|
Fioreze, T. and Granville, L. and Sadre, R. and Pras, A.
(2009)
A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections.
In: Proceedings of the 3rd International Conference on Autonomous Infrastructure, Management and Security (AIMS 2009), June 30 - July 2, 2009, Enschede, The Netherlands.
pp. 15-27.
Lecture Notes in Computer Science 5637.
Springer Verlag.
ISSN 0302-9743
ISBN 978-3-642-02626-3
Full text available as:
Official URL: http://dx.doi.org/10.1007/978-3-642-02627-0_2  AbstractNetwork monitoring plays an important role in network management. Through the analysis of network parameters (e.g., flow throughput), managers can observe network behavior and make decisions based on them. The choice of network parameters although should be relevant for each specific objective. In this paper, we focus on the analysis of network parameters that are relevant for our self-management of lambda-connections proposal. This proposal consists of an automatic decision process to offload large IP flows onto lambda-connections. This paper aims at statistically analyzing a list of potential network parameters as relevant estimators for flow volume. The main contribution of this work is the introduction of a statistical methodology to validate that some few network parameters can be considered as good predictors for flow volume. These predictors are therefore of great interest to be used in our automatic decision process.
Export this item as: To correct this item please ask your editor Repository Staff Only: edit this item |
|
|
||||||||||||||||||||||||||||||||
|
|
|
||||||||||||||||||||||||||||||||||
|
|
|
|
|
||||||||||||||||||||||||||||||||
|
|
|
||||||||||||||||||||||||||||||||||
