A Pragmatic Definition of Elephants in Internet Backbone Traffic

Studies of the Internet traffic at the level of network prefixes, fixed length prefixes, TCP flows, AS’s, and WWW traffic, have all shown that a very small percentage of the flows carries the largest part of the information. This behavior is commonly referred to as “the elephants and mice phenomenon”. Traffic engineering applications, such as re-routing or load balancing, could exploit this property by treating elephant flows differently. In this context, though, elephants should not only contribute significantly to the overall load, but also exhibit sufficient persistence in time. The challenge is to be able to examine a flow’s bandwidth and classify it as an elephant based on the data collected across all the flows on a link. In this paper, we present a classification scheme that is based on the definition of a separation threshold, that elephants have to exceed. We introduce two single-feature classification schemes, and show that the resulting elephants are highly volatile. We then propose a two-feature classification scheme that incorporates temporal characteristics and show that this approach is more successful in isolating elephants that exhibit consistency thus making them more attractive for traffic engineering applications

Identifiability of flow distributions from link measurements with applications to computer networks

We study the problem of identifiability of distributions of flows on a graph from aggregate measurements collected on its edges. This is a canonical example of a statistical inverse problem motivated by recent developments in computer networks. In this paper (i) we introduce a number of models for multi-modal data that capture their spatio-temporal correlation, (ii) provide sufficient conditions for the identifiability of nth order cumulants and also for a special class of heavy tailed distributions. Further, we investigate conditions on network routing for the flows that prove sufficient for identifiability of their distributions (up to mean). Finally, we extend our results to directed acyclic graphs and discuss some open problems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58107/2/ip7_5_004.pd

Bridging Router Performance and Queuing Theory

This paper provides an authoritative knowledge of through-router packet delays and therefore a better understanding of data network performance. Thanks to a unique experimental setup, we capture all packets crossing a router for 13 hours and present detailed statistics of their delays. These measurements allow us to build the following physical model for router performance: each packet experiences a minimum router processing time before entering a fluid output queue. Although simple, this model reproduces the router behaviour with excellent accuracy and avoids two common pitfalls. First we show that in-router packet processing time accounts for a significant portion of the overall packet delay and should not be neglected. Second we point out that one should fully understand both link and physical layer characteristics to use the appropriate bandwidth value

Facilitating Access Point Selection in IEEE 802.11 Wireless Networks

The performance experienced by wireless clients in IEEE 802.11 wireless networks heavily depends on the clients ’ ability to identify the Access Point (AP) that will offer the best service. The current AP affiliation mechanism implemented in most wireless clients is based on signal strength measurements received by the client from all the APs in its neighborhood. The client then affiliates with the AP from which it receives the strongest signal. It is well-known that such an algorithm can lead to suboptimal performance, due to its ignorance of the load at different APs. In this work, we consider the problem of AP selection. We identify potential bandwidth as the metric based on which hosts should make affiliation decisions, and define it as the (MAC-layer) bandwidth that the client is likely to receive after affiliating with a particular AP. We further limit ourselves to the use of passive measurements that do not require an end-host to affiliate with the AP, thus allowing the end-host to simultaneously evaluate the potential bandwidth to multiple APs in range. This can also facilitate more informed roaming decisions. We propose a methodology for the estimation of potential upstream and downstream bandwidth between a client and an AP based on measurements of delay incurred by 802.11 Beacon frames from the AP. Preliminary experiments conducted in a controlled environment demonstrate that the proposed methodology looks promising, yielding fairly accurate results under varying conditions.