A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections

Tiago Fioreze; L. Granville; R. Sadre; Aiko Pras

doi:10.1007/978-3-642-02627-0_2

A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections

Tiago Fioreze
, L. Granville
, R. Sadre
, Aiko Pras

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Citations (Scopus)

131 Downloads (Pure)

Abstract

Network 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.

Original language	English
Title of host publication	Scalability of Networks and Services
Subtitle of host publication	Third International Conference on Autonomous Infrastructure, Management and Security, AIMS 2009 Enschede, The Netherlands, June 30 - July 2, 2009: Proceedings
Editors	Ramin Sadre, Aiko Pras
Place of Publication	Berlin
Publisher	Springer
Pages	15-27
Number of pages	13
ISBN (Electronic)	978-3-642-02627-0
ISBN (Print)	978-3-642-02626-3
DOIs	https://doi.org/10.1007/978-3-642-02627-0_2
Publication status	Published - 19 Jun 2009
Event	3rd International Conference on Autonomous Infrastructure, Management and Security, AIMS 2009 - Enschede, Netherlands Duration: 30 Jun 2009 → 2 Jul 2009 Conference number: 3

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
Volume	5637
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Autonomous Infrastructure, Management and Security, AIMS 2009
Abbreviated title	AIMS 2009
Country/Territory	Netherlands
City	Enschede
Period	30/06/09 → 2/07/09

Keywords

2024 OA procedure

Access to Document

10.1007/978-3-642-02627-0_2

ArticleFinal published version, 318 KBLicence: Taverne

Cite this

Fioreze, T., Granville, L., Sadre, R., & Pras, A. (2009). A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections. In R. Sadre, & A. Pras (Eds.), Scalability of Networks and Services: Third International Conference on Autonomous Infrastructure, Management and Security, AIMS 2009 Enschede, The Netherlands, June 30 - July 2, 2009: Proceedings (pp. 15-27). Article 10.1007/978-3-642-02627-0_2 (Lecture Notes in Computer Science; Vol. 5637). Springer. https://doi.org/10.1007/978-3-642-02627-0_2

Fioreze, Tiago ; Granville, L. ; Sadre, R. et al. / A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections. Scalability of Networks and Services: Third International Conference on Autonomous Infrastructure, Management and Security, AIMS 2009 Enschede, The Netherlands, June 30 - July 2, 2009: Proceedings. editor / Ramin Sadre ; Aiko Pras. Berlin : Springer, 2009. pp. 15-27 (Lecture Notes in Computer Science).

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abstract = "Network 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.",

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Fioreze, T, Granville, L, Sadre, R & Pras, A 2009, A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections. in R Sadre & A Pras (eds), Scalability of Networks and Services: Third International Conference on Autonomous Infrastructure, Management and Security, AIMS 2009 Enschede, The Netherlands, June 30 - July 2, 2009: Proceedings., 10.1007/978-3-642-02627-0_2, Lecture Notes in Computer Science, vol. 5637, Springer, Berlin, pp. 15-27, 3rd International Conference on Autonomous Infrastructure, Management and Security, AIMS 2009, Enschede, Netherlands, 30/06/09. https://doi.org/10.1007/978-3-642-02627-0_2

A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections. / Fioreze, Tiago; Granville, L.; Sadre, R. et al.
Scalability of Networks and Services: Third International Conference on Autonomous Infrastructure, Management and Security, AIMS 2009 Enschede, The Netherlands, June 30 - July 2, 2009: Proceedings. ed. / Ramin Sadre; Aiko Pras. Berlin: Springer, 2009. p. 15-27 10.1007/978-3-642-02627-0_2 (Lecture Notes in Computer Science; Vol. 5637).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

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AU - Fioreze, Tiago

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AU - Sadre, R.

AU - Pras, Aiko

N1 - Conference code: 3

PY - 2009/6/19

Y1 - 2009/6/19

N2 - Network 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.

AB - Network 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.

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BT - Scalability of Networks and Services

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Fioreze T, Granville L, Sadre R, Pras A. A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections. In Sadre R, Pras A, editors, Scalability of Networks and Services: Third International Conference on Autonomous Infrastructure, Management and Security, AIMS 2009 Enschede, The Netherlands, June 30 - July 2, 2009: Proceedings. Berlin: Springer. 2009. p. 15-27. 10.1007/978-3-642-02627-0_2. (Lecture Notes in Computer Science). doi: 10.1007/978-3-642-02627-0_2

A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections

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