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Hybrid Passive and Active Surveillance Approach with Interchangeable Filters and a Time Window Mechanism for Performance Monitoring

Prathap M1 , Antony Selvadoss Thanamani2

Section:Review Paper, Product Type: Journal Paper
Volume-4 , Issue-4 , Page no. 30-33, Apr-2016

Online published on Apr 27, 2016

Copyright © Prathap M , Antony Selvadoss Thanamani . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Prathap M , Antony Selvadoss Thanamani, “Hybrid Passive and Active Surveillance Approach with Interchangeable Filters and a Time Window Mechanism for Performance Monitoring,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.30-33, 2016.

MLA Style Citation: Prathap M , Antony Selvadoss Thanamani "Hybrid Passive and Active Surveillance Approach with Interchangeable Filters and a Time Window Mechanism for Performance Monitoring." International Journal of Computer Sciences and Engineering 4.4 (2016): 30-33.

APA Style Citation: Prathap M , Antony Selvadoss Thanamani, (2016). Hybrid Passive and Active Surveillance Approach with Interchangeable Filters and a Time Window Mechanism for Performance Monitoring. International Journal of Computer Sciences and Engineering, 4(4), 30-33.

BibTex Style Citation:
@article{M_2016,
author = {Prathap M , Antony Selvadoss Thanamani},
title = {Hybrid Passive and Active Surveillance Approach with Interchangeable Filters and a Time Window Mechanism for Performance Monitoring},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2016},
volume = {4},
Issue = {4},
month = {4},
year = {2016},
issn = {2347-2693},
pages = {30-33},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=851},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=851
TI - Hybrid Passive and Active Surveillance Approach with Interchangeable Filters and a Time Window Mechanism for Performance Monitoring
T2 - International Journal of Computer Sciences and Engineering
AU - Prathap M , Antony Selvadoss Thanamani
PY - 2016
DA - 2016/04/27
PB - IJCSE, Indore, INDIA
SP - 30-33
IS - 4
VL - 4
SN - 2347-2693
ER -

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Abstract

According to Bonald and Feuillet (2011), the management of network resources has taken on a new urgency with the highly interactive nature of modern computing and the increasing interdependence of networked applications. As a result, the monitoring of network behavior has become an integral part of management. It is critical that applications are armed with tools that can facilitate the estimation of performance and allow the selection of suitable encoding schemes, buffering sizes, and adaptation features. This paper examines the importance to assess the requirements for monitoring the network performance within a wireless environment for the processing and presentation of the statistical outcome of surveillance information. In comparison to the probing technique, which is based on the distance separating data packets, the two monitoring schemes lead to considerable traffic within the network. The proposed method will use a straightforward statistical analysis to determine variations in the network characteristics used a hybrid passive and active surveillance approach with interchangeable filters and a time window mechanism.

Key-Words / Index Term

Buffer Size, Surveillance Information, Interchangeable Filters, Time Window Mechanism

References


[1] Bonald, T., & Feuillet, M. “Network performance analysis”. London, UK: ISTE 2011.
[2] George, D. K., et al “Exact-order asymptotic analysis for closed queuing networks” Journal of Applied Probability, 49(2), 2012, 503-520.
[3] Holt, A. “Network performance analysis: Using the J programming language” London, UK: Springer 2008
[4] Markl, C., & Huhn, O. (Eds.). “Evaluation of prioritization in performance models of DTP Systems” IEEE Conference on Commerce and Enterprise Computing CEC’09: Vienna, Austria: IEEE. 2009
[5] Marshall, P. “Quantitative analysis of cognitive radio and network performance” Norwood, MA: Artech House. 2010
[6] Nelson, P., & Rebelo, P. “Network performance”. New York, NY: Taylor & Francis. 2009.
[7] Perkins, D. D et al Proceedings of IEEE International Conference on Communications COC’12: Factors affecting the performance of ad hoc networks. Lafayette, LA: IEEE, 2012.
[8] Pallavi S and M. Lakshmi, “Estimation Of Burst Length in OBS Networks” Indian Journal of Computer Science and Engineering (IJCSE). Vol.5, Issue-2, 2014, pp.78-84. e-ISSN:0976-5166 p-ISSN:2231-3850.