An Enhanced Algorithm for Fair Traffic Conditioning
in Differentiated Services Networks
Abiola Adegboyega, Rupinder Makkar, Kayvan Mosharaf, Ioannis Lambadaris
Broadband Networks Laboratory
Carleton University Ottawa, Ontario, Canada, K1S 5B6
{agboyega, rup, mosharaf, ioannis}@sce.carleton.ca
Abstract—Fair bandwidth sharing among traffic flows with
different characteristics in Differentiated Services (Diffserv)
networks is the focus of the current research. This paper
examines and enhances an algorithm developed to enforce
fairness among disparate TCP flows in the Assured Forwarding
(AF) service in Diffserv. Equation Based Marking (EBM) [1] was
introduced by K. Shin et al to enforce fairness in AF by
monitoring existent network conditions used in marking
decisions. The estimation of packet losses by the algorithm is
integral to marking. The loss rates of different connections were
demonstrated to converge hence enforcing a fair marking
regardless of the metrics of individual flows. In this paper, EBM
is analyzed for fairness and enhanced by implementing a more
efficient technique for loss rate estimation. Comparison is made
between EBM and the enhanced technique with results showing
appreciable improvements in the maintenance of fairness.
Furthermore, a service definition required by QoS standards is
met with the implementation of the additional algorithm to EBM.
Keywords-Diffserv, QoS, TCP, Fairness, loss rate
I. INTRODUCTION
Differentiated Services (Diffserv) [2] offers a scalable
service provisioning architecture in IP networks by the
allocation of network resources based on application
requirements. Diffserv philosophy, in providing end-to-end
Quality of Service (QoS) moves architectural complexity to
the ‘edge’ of the Diffserv domain where ingress traffic is
conditioned and marked for differentiation into classes while
the ‘core’ forwards aggregated traffic streams and enforces
QoS during network congestion.
The Assured Forwarding (AF) Per-Hop Behavior (PHB)
[3] is a Diffserv forwarding mechanism that has been
standardized by the Internet Engineering Task Force (IETF).
AF maintains traffic profiles for ingress traffic and marks
packets at the network edge as IN-profile provided they adhere
to the service profile of the network or OUT-of-profile
otherwise. The basis of this marking is the comparison of the
subscription rate of incoming streams with the Committed
Information Rate (CIR) and Peak Information Rate (PIR)
assigned for the Diffserv domain. If the ingress traffic rate is
lower than the CIR, it is marked as IN and assigned the lowest
drop precedence AFx1. When the traffic rate exceeds the CIR
but not the PIR, packets are marked as OUT with drop
precedence AFx2. Ingress traffic with rates greater than the
PIR are marked as OUT with the highest drop precedence
AFx3. The AF PHB can be achieved in core routers by a tiered
dropping scheme that ensures service differentiation by
dropping packets during congestion beginning with the highest
drop precedence AFx3, then AFx2 and eventually AFx1 only
when all other precedences are dropped. A common
implementation of this dropping scheme is done by an active
queue management (AQM) scheme like Random Early
Detection (RED) [4] with some variations e.g. RED with IN
and OUT (RIO), with two thresholds one each for conformant
and non-conformant traffic [5].
It was shown in [6] that AF is unable to provide
bandwidth assurance when competing TCP traffic streams are
different based on the flow metrics of packet size, Round Trip
Time (RTT), target rate and the number of microflows
aggregated in a flow. Furthermore, while TCP flows are able
to slow down their sending rates during congestion, non-
responsive flows (e.g. UDP traffic) maintain their network
subscription rates regardless of congestion.
One approach of mitigating unfairness is by using ‘TCP-
aware’ traffic conditioners, employing one or more of TCP’s
characteristics [7][8][9]. This paper presents an enhanced
version of the traffic conditioner in [1] that employs the
inverse of a modeled steady-state TCP equation in marking
functions. Our contributions to the existing algorithm include
the implementation of a more efficient loss rate estimation
technique, which is integral to packet marking. Loss History
Discounting provides enhancements to EBM with more details
given in section IV.
The rest of the paper is organized as follows. Section II
discusses related work in mitigating unfairness in AF services.
Section III presents EBM [1] and its use of loss rate estimation
in marking decisions. Section IV presents our version of the
modified conditioner. We compare the original and enhanced
algorithms with simulations in section V and conclusions are
made in section VI.
II. RELATED WORK
Intelligent traffic conditioning for the provision of fairness
in Diffserv networks has been researched extensively. In [6],
Seddigh et al employed simulations to illustrate the impact of
the flow metrics of RTT, packet size, microflows and target on
fairness and the distribution of surplus bandwidth. In [10]
simulations were employed to demonstrate that TCP/UDP
interactions and RTT have a direct impact on achievable
throughput of competing flows.
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