1. Burst Metric In packet-based networks Initial Considerations for IPPM burst metric Tuesday, March 21, 2006

2. Why Need to better size network resources Improve Performance management Network traffic is bursty; Bursty applications Network congestions Asymmetric nature of interactive traffic TCP applications Unbalanced parallel streams Unstable network, poorly sized network resources on sender side Burstness of the traffic may affect the application performance Packet drops/ buffer overflow Poor video / voice quality A single stream may be bursty while the combined flow from n streams may not Need to understand and measure traffic characteristics We have measures for packet loss, gap, burst loss (RFC3611), loss patterns ( RFC 3357) not packet burst Burstness metric ( requests) may be used to size the servers Burstneess metric may be used to design and optimize network resources Bandwidth allocation Buffer sizing Burstness metric maybe used to dimension QoS class parameters

3. Some measures Degree of burstness –Ratio of peak to average transmission rate over time interval Hurst Index –Measure of self-similarity of traffic Token bucket burst measures –Amount of traffic that can be sent within a given unit of time Index of dispersion for counts (IDC) –Ratio between the variance and expected number of arrivals (N t ) over interval (t) IDC t = Var(N t )/E(N t )

4. To do list Develop IPPM Burst metric –Need to define the phenomena we want to measure –Need a definition of metric –Need a metric –Need operationalization

5. References RFC 3611 - RTP Control Protocol Extended Reports (RTCP XR) RFC 3357 - One-way Loss Pattern Sample Metrics draft-auerbach-mgcp-rtcpxr-03.txt draft-clark-avt-rtcpxr-video-01.txt Why is the Internet traffic bursty in short time scales? Hao Jiang, Constantine Dovrolis- College of Computing Georgia Institute of Technology –Well understood cause-effect relationship in large scales (> 1 second) Leland et al. (TNet’94): asymptotic self-similarity and LRD behavior, assuming stationarity Major causes: –Willinger et al. (Sigcomm’95): heavy-tailed ON-OFF behavior in traffic interarrivals –Crovella/Bestavros (TNet’99): heavy-tailed ON-OFF behavior in Web transfers –Also well understood is the role of TCP congestion control in sup-RTT time scales Figueiredo et al. (CompNets’02): pseudo-self similar behavior in a range of medium time scales –From a single RTT to tens/hundreds of RTTs Cause: strong correlations due to TCP congestion control and timeouts