NDLI: Optimal Deployment of Distributed Passive Measurement Monitors

Content Provider	IEEE Xplore Digital Library
Author	Chengchen Hu Bin Liu Zhen Liu Shifang Gao Dapeng Wu
Copyright Year	2006
Description	Author affiliation: Dept. of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA (Dapeng Wu) \|\| Dept. of Computer Science and Technology, Tsinghua University, Beijing, China (Bin Liu; Zhen Liu) \|\| Dept. of Computer Science and Technology, Tsinghua University, Beijing, China. hucc03@mails.tsinghua.edu.cn (Chengchen Hu) \|\| Dept. of Automatic Control, Northwest Polytechnical University, Xi'an, Shaanxi, China (Shifang Gao)
Abstract	Flow-level traffic measurement is important for network management. The widely used centralized per-flow measurement faces a great challenge due to the demanding requirement on both memory bandwidth and memory size within a single traffic monitor. This paper addresses the issue of deploying a Distributed Passive Measurement System (DPMS) in a large scale network; specifically, we study how to optimally place traffic monitors and sample stochastic traffic flows, so that the probability of a packet being sampled (a.k.a. measurement coverage) is maximized. We formulate this problem as a Stochastic Chance Constrained Optimization (SCCO) problem; and we propose a Hybrid Intelligent (HI) algorithm to solve this problem. The HI algorithm consists of two major components, namely, uncertain function approximation and genetic algorithm. Equipped with the HI algorithm, we are able to address the optimal tradeoff between measurement coverage and deployment cost for networks with random traffic, which has not been studied before. Our simulations and experiments demonstrate the effectiveness of our algorithm, i.e., a small deployment cost or a small number of monitors are sufficient to maintain a high level of measurement coverage.
Starting Page	621
Ending Page	626
File Size	271912
Page Count	6
File Format	PDF
ISBN	1424403553
ISSN	81649547
DOI	10.1109/ICC.2006.254776
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-11
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Telecommunication traffic Size measurement Bandwidth Large-scale systems Stochastic systems Stochastic processes Constraint optimization Approximation algorithms Function approximation Genetic algorithms genetic algorithm passive measurement distributed monitoring stochastic chance constrained optimization
Content Type	Text
Resource Type	Article

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