Traffic characterization for traffic engineering purposes: analysis of Funet data

Juva, I.; Susitaival, Riikka; Peuhkuri, Markus; Aalto, Samuli

doi:10.1109/ngi.2005.1431694

Cited by 13 publications

(25 citation statements)

References 11 publications

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“…These observations were based on data collected from a Tier-1 backbone with measurement period ∆ = 1 s. Soule et al [6] found similar results from flow data collected from a commercial Tier-1 backbone with measurement period ∆ = 300 s. They report that the power-law constant c for individual OD flows varies in a range spanning from 1 to 4. In our previous work [8] we found that this is true also for the Lucent local area network, used in [7]. For some OD pairs the fit was reasonably good, but for others it was next to non-existent.…”

Section: Temporal Relationmentioning

confidence: 56%

“…Our study [8] of the same local area network data set yielded parameter value of c = 1.96. Medina et al [1] reported that the meanvariance relationship seems to hold, with the parameter value being c = 1.97 in their study.…”

Section: Spatial Relationmentioning

confidence: 99%

“…Concerning the relation over time in one OD pair or link, results in literature are more in line with each other. It is found in [1,6,8] that the parameter values as well as the validity of the relation vary dramatically from OD pair to OD pair.…”

Section: Introductionmentioning

confidence: 99%

“…In [8] we investigate the validity of the moving IID Gaussian model against Finnish university network (Funet) link count measurements, varying the measurement period from 1 second to 5 minutes. We find that the Gaussian assumption is justified for the aggregated link traffic.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Characteristics of origin-destination pair traffic in Funet

Susitaival¹,

Juva²,

Peuhkuri³

et al. 2006

Telecommun Syst

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show abstract

Section: Temporal Relationmentioning

confidence: 56%

Section: Spatial Relationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Characteristics of origin-destination pair traffic in Funet

Susitaival¹,

Juva²,

Peuhkuri³

et al. 2006

Telecommun Syst

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show abstract

“…Such an assumption has been considered in [7,14,15,11,16], and validated via QQ-plots and related correlation tests comparing the empirical distribution with a fitted Gaussian distribution. The data at hand are obtained from the traffic observed on one link, which is partitioned into OD traffic based on source and destination IP addresses (time aggregation from 1 s to 300 s), except in [7] where the data are the traffic observed on the links and OD pairs of a onerouter network with 5 min time aggregation, as provided by SNMP.…”

Section: Introductionmentioning

confidence: 99%

Blind maximum likelihood estimation of traffic matrices under long-range dependent traffic

Conti¹,

Giovanni

Naldi

2010

Computer Networks

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a b s t r a c tA new method, based on the maximum likelihood principle, through the numerical Expectation-Maximization algorithm, is proposed to estimate traffic matrices when traffic exhibits long-range dependence. The methods proposed so far in the literature do not account for long-range dependence. The method proposed in the present paper also provides an estimate of the Hurst parameter. Simulation results show that: (i) the estimate of the traffic matrix is more efficient than those obtained via existing techniques; (ii) the estimation error of the traffic matrix is lower for larger values of the true traffic intensity; (iii) the estimate of the Hurst parameter is slightly negatively biased.

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Effects of Spatial Aggregation on the Characteristics of Origin-Destination Pair Traffic in Funet

Juva¹,

Susitaival²,

Peuhkuri³

et al.

Next Generation Teletraffic and Wired/Wireless Advanced Networking

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In this paper we analyze measurements from the Finnish University Network (Funet) and study the effect of spatial aggregation on the origin-destination flows. The traffic is divided into OD pairs based on IP addresses, using different prefix lengths to obtain data sets with various aggregation levels. We find that typically the diurnal pattern of the total traffic is followed more closely by the OD pairs as their volume increases, but there are many exceptions. Gaussian assumption holds well for all OD pairs when the aggregation level is high enough, and we find an approximate threshold for OD pair traffic volume after which they tend to be Gaussian. Also the functional mean-variance relation holds better when the aggregation level is higher.

show abstract

Traffic characterization for traffic engineering purposes: analysis of Funet data

Cited by 13 publications

References 11 publications

Characteristics of origin-destination pair traffic in Funet

Characteristics of origin-destination pair traffic in Funet

Blind maximum likelihood estimation of traffic matrices under long-range dependent traffic

Effects of Spatial Aggregation on the Characteristics of Origin-Destination Pair Traffic in Funet

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