A Fuzzy LSP Regulator for Preemption Control
in a DiffServ-Aware MPLS Internet
N. M Din & H.Z. Abidin
Department of Electrical Engineering,
College of Engineering,
Universiti Tenaga Nasional,
KM 7, Jalan Kajang-Puchong,
43009 Kajang, Selangor, Malaysia
{norashidah, husna)@uniten. edu. my
Abstract This paper describes a proposal for a fuzzy
logic LSP regulator for preemption control in a DiffServ-
aware MPLS Internet network based on the Russian Doll
bandwidth allocation scheme. The fuzzy logic regulator
regulates the incoming traffic based on class by either
rerouting or resizing existing less prioritized traffic or
rejecting the admission request. Three DiffServ traffic class
types were used in the DiffServ-aware MPLS network under
study, i.e. premium, assured and best effort traffic. The fuzzy
logic regulator uses the premium traffic utilization value, the
assured and best effort traffic amount of borrowed
bandwidth information as inputs and the preemption decision
as output. A simulation study was performed for the fuzzy
logic regulator using ns-2. A comparative analysis was
conducted with preemption, no preemption and with fuzzy
logic regulator preemption. The results show that the fuzzy
logic pre-emption scheme gave better performance in terms
of connection blocking probability and throughput.
Index Terms- DifJServ, Fu-y Logic, MPLS, Preemption
UINTRODUCTION
The DiffServ architecture [1] combined with MPLS [2]
has become a promising mechanism of achieving QoS with
the scalability required by the Internet. MPLS achieves fast
forvarding of packets through its connection-oriented
framework. The MPLS edge router assigns packets with
labels. Label switched routers in the MPLS core network
direct the packets based on their labels. Labels have local
significance, and because of this their actual values can
change as a packet traverses an MPLS network. However,
the packet's path through the network is
completely determined by the initial label the ingress LSR
assigns it. This path is known as label switched path (LSP).
Each distinct flow traversing the LSP is known as a
Forwarding Equivalent Class (FEC). The FEC of a
packet can be determined by a number of parameters, i.e.
DiffServ Code Point, IP protocol ID, Source and/or
destination IP addresses or netwvork addresses. MPLS
imposes a connection-oriented framework on an IP-based
S.F. A. Rahman & N. Fisal
Telekom s Laboratory
Faculty of Electrical Engineering
Universiti Teknologi Malaysia
813 10 Skudai, Johor Bahru
Johor, Malaysia
intemet and thus provides the foundations for reliable
traffic contracts allowing traffic engineering to take place.
What can be seen from the DiffServ and MPLS
architectures are that they both provide support for service
differentiation which complement each other. The PHBs in
DiffServ and FECs in MPLS can be mapped to provide
QoS.This paper describes work on a fuzzy logic LSP
regulator for preemption decision making in a DiffServ-
aware MPLS domain. Section II describes related work in
literature whereas Section III describes the fuzzy logic
regulator. Section IV discusses the simulation work and
Section V the conclusion.
II.RELATED WORK
A.Fu zy Logic in Traffic Contr-ol
Fuzzy logic-based traffic control had been proposed by
several earlier works mainly addressing ATM networks,
such as in [3, 4, 5]. In [3], a congestion management
scheme to support ATM's Available Bit Rate traffic to
utilize available bandwidth without causing congestion was
proposed. A fuzzy inference engine was used to determine
the explicit rate for the source of an ATM network whereas
a neural fuzzy mechanism is used for generating fuzzy
rules for predicting future cell loss. Work by [4] proposed
an admission control mechanism that uses a type-2 fuzzy
logic system where a group decision making comprising 30
subject matter experts is captured into the
inference mechanism instead of taking from only one
expert. A type-2 fuzzy set is characterized by a fuzzy
membership function, i.e. the membership value for each
element of a set is a fuzzy set in [0,1] unlike a type-I
where the membership value is a crisp value in [0,1].
Research conducted by [5] uses fuzzy logic to implement
admission control and usage parameter control (UPC) for
an ATM switch. A fuzzy switch controller for queue size
management used in admission control was introduced.
Three types of traffic flow were accommodated, i.e. voice,
video and data. The fuwzzy input was source transmission
rate for each of the source type and the output is the queue
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