Efficient Multicast Schemes for Optical Burst-Switched WDM Networks
Myoungki Jeong† , Yijun Xiong‡ , Hakki C. Cankaya‡ , Marc Vandenhoute‡ and Chunming Qiao†
Depts. of EE and CSE† , SUNY at Buffalo
Alcatel Corporate Research Center‡
Buffalo, NY 14260
Richardson, TX 75081
mjeong,qiao @cse.buffalo.edu
xionyi,cankhc,vandma @aud.alcatel.com
Abstract– In this paper, we study several multicast
schemes in optical burst-switched WDM networks taking
into consideration of the overheads due to control packets and guard bands (GBs) of bursts on separate channels
(wavelengths). A straightforward scheme is called Separate Multicasting (S-MCAST) where each source node constructs separate bursts for its multicast (per each multicast session) and unicast traffic. To reduce the overhead
due to GBs (and control packets), one may piggyback the
multicast traffic in bursts containing unicast traffic using a
scheme called Multiple Unicasting (M-UCAST). The third
scheme is called Tree-Shared Multicasting (TS-MCAST)
whereby multicast traffic belonging to multiple multicast
sessions can be mixed together in a burst, which is delivered via a shared multicast tree. The multicast schemes (MUCAST and TS-MCAST) are compared with S-MCAST in
terms of bandwidth consumed and processing load.
1 Introduction
As traffic demand increases exponentially in the Internet,
Wavelength Division Multiplexing (WDM) networks [3, 6, 12]
become a natural choice for the backbone. Recently, IP over
WDM networks (or so-called Optical Internet) have received a
considerable amount of attention (e.g. [1, 10]).
Multicasting (i.e. one-to-many communications) is becoming more and more popular and important in the Internet. Multicasting in IP over WDM networks can be done via IP multicast, multiple WDM unicast, or WDM multicast [4]. In this
paper, we will concentrate mainly on WDM multicast.
There are two WDM multicasting approaches, one based on
wavelength-routing as in [5, 11, 7], and the other based on optical burst switching (OBS) [8, 10] as in [4, 15]. In the former,
multicast data will be switched to one or more outgoing wavelengths according to the incoming wavelength that carries it (as
in wavelength-routing). In other words, a wavelength needs to
be dedicated to each branch of a multicast tree. This scheme is
suitable for high bandwidth multicast applications having a relatively long duration, such as video distribution. In the latter,
This research is supported in part by a grant from NSF under contract number ANIR-9801778.
no wavelengths need to be dedicated to a multicast tree and the
multicast data is transported via OBS which is more bandwidth
efficient than wavelength routing for bursty traffic. However,
there are two major overheads in using OBS, namely, control
packets and guard bands (GBs). More specifically, to send each
burst, a control packet needs to be sent to set up switches and
GBs are used in the burst to accommodate possible timing jitters at each intermediate node.
In this paper, we study several multicast schemes in optical burst-switched WDM networks taking into consideration of
the overheads due to control packets and guard bands (GBs) of
bursts on separate channels (wavelengths). These will result in
different bandwidth consumption (which is proportional to different amount of GBs) , different channel utilization (inversely
proportional to different burst lengths) and different processing
loads (proportional to the number of control packets generated)
under the same traffic condition. Specifically, we consider
three multicast schemes: Separate Multicasting (S-MCAST),
Multiple Unicasting (M-UCAST) and Tree-Shared Multicasting (TS-MCAST). Moreover, we propose three tree sharing
strategies in TS-MCAST based on Equal Coverage (EC), Super
Coverage (SC) and Overlapping Coverage (OC). The performance of the multicast schemes (M-UCAST and TS-MCAST)
are compared with that of S-MCAST in terms of bandwidth
consumed and processing load.
The rest of this paper is organized as follows. In Section 2,
we describe different multicast schemes for multicast traffic. In
Section 3, we discuss tree sharing strategies and develop algorithms to construct shared tree. In Section 4, we describe simulation model used and present numerical results of the proposed
multicast schemes. We conclude the paper in Section 5.
2 Multicasting in Optical
Switched WDM Networks
Burst-
In this section, we describe three schemes for multicasting in
optical burst-switched WDM networks, namely, S-MCAST,
M-UCAST and TS-MCAST. We assume that each source
maintains one burst assembly queue for each multicast session
and each destination of unicast traffic.
In S-MCAST, each multicast group (session) constructs its
own source-specific multicast tree along which the assembled
bursts carrying multicast traffic for the group are delivered. In
other words, multicast traffic is transmitted independently of
unicast traffic. More specifically, in each multicast session, IP
packets arriving within a given assembly time Tbm are assembled into a burst. After the assembly time is over, the burst is
sent out along the multicast tree.
In M-UCAST, multicast traffic is treated as unicast traffic.
More specifically, during the burstification process, a copy of
multicast data can be assembled together with unicast data for
the same destination. In other words, multicast is accomplished
with multiple unicast and hence multicast traffic essentially
gets a “free” ride for GBs. By doing so, the control overhead
can be reduced since the GB can be shared by both traffic types
in a longer burst, and in addition, the number of control packets
also decreases. Hence, although M-UCAST wastes bandwidth
for multicast traffic (see e.g. [11]), it is possible that under certain network conditions (and in particular, depending on the GB
size), M-UCAST for multicast traffic is better than S-MCAST
(see Section 4).
In TS-MCAST, if there is a certain degree of membership
overlap or some special relation between multicast sessions in
Hi where Hi is a set of all multicast sessions originating from an
edge router i, the set Hi is split into a number of subsets based
on certain strategies (to be described in Section 3). Each subset,
called Multicast Sharing Class (MSC)1 , then either constructs a
new shared tree (ST) or uses one of the existing multicast trees
(one of the multicast sessions in the subset) depending on the algorithm used to construct or select the ST (also to be described
in Section 3). During the burstification process, IP packets belonging to the multicast sessions in a MSC are assembled together to form bursts. Therefore, the average burst length using
TS-MCAST will be longer than that without tree sharing. This
helps reduce the bandwidth waste due to GB as well as the number of control packets generated. Note that multicast traffic is
transmitted independently of unicast traffic.
set of Hi ( 2) multicast sessions rooted at an edge router i
should become a MSC. For simplicity, we use MSC j rather than
MSCi j to denote the jth MSC at an edge router i.
In EC, multicast sessions with the same membership are
grouped into the same MSC. Hence, s multicast sessions in
MSC j (as its elements) have the same set of member edge
routers, i.e., E j1 E j2
E js although each multicast
session in MSC j may have a different multicast tree (or path to
each member). Fig. 1 (left) shows an example of EC (where s =
2) in which multicast trees T1 (solid line) and T2 (dashed line)
have the same set of edge routers (i.e. E4, E6 and E8) as their
members. In such a case, one of the existing multicast trees, T1
or T2, is selected to be the new ST.
A less restricting tree sharing strategy is SC where all multicast sessions in MSC j do not necessarily have the same set of
edge routers. Specifically, if two multicast sessions, T1 and T2
have a special relation or in other words, T1 is a super tree for
MSC j , such that ET2 ET1 , then T1 and T2 are grouped into
the same MSC (i.e. MSC j ) (see Fig. 1 (middle)). Note that, IP
packets (belonging to T2) will also be delivered to E3 and E5
via T1 but subsequently discarded by E3 and E5.
Finally, OC is the most general strategy in that it allows a
number of multicast sessions having a sufficient degree of overlap in edge routers E, core routers C, links L or tree sharing gain
α (from (4)) to be grouped into the same MSC. More specifically, we define the degree of overlap as follows. Consider the
jth MSC (MSC j ) at an edge router i and assume that it has s
multicast sessions. That is, MSC j = (T j1 ,T j2 ,...,T js ) where T jk
= (C jk E jk L jk ) for k=1,2,...,s. Then, the degree of overlap can
be defined in terms of edge routers, core routers or links in the
MSC as follows:
γE
∑ E E
∑ C C
∑ L L
s
k 1
k
γC
3 Tree Sharing Multicasting
γL
In this section, we describe how to decompose a set of multicast
sessions (Hi ) into a number of MSCs where each MSC uses a
ST.
Let Nc be the set of all core routers, Ne be the set of all edge
routers and Nl be the set of all links in the network. In the following discussion, we model a multicast session (or tree) in the
network using a triple T = C E L where C Nc is the set of
core routers, E Ne is the set of edge routers, and L Nl is the
set of links on the multicast tree, respectively.
3.1 Tree Sharing Strategies
We consider three strategies, namely Equal Coverage, Super
Coverage and Overlapping Coverage, for deciding which sub1 subset and MSC will be used interchangeably
may contain only one multicast session.
and as a special case, a MSC
k
jk
jk
k
jk
(1)
k
jk
(2)
k
jk
j
jk
s
k 1
E MSC 1
C MSC 1 L MSC 1
j
jk
s
k 1
k
jk
jk
j
(3)
Note that according to such a definition, γE = 1 in EC and γE
1 in SC and OC.
For a MSC j at an edge router i, denoted by MSCi j , we define the bandwidth gain due to tree sharing as the ratio between
the average amount of multicast traffic carried per link without/with tree sharing. Let ri j be the data rate of a session j at
an edge router i and si j be the number of links on the multicast
tree for the session j. In addition, let ri j be the sum of the data
rate of all the sessions in MSCi j and si j be the number of links
on the shared multicast tree used for MSCi j . Assuming that G
is the guard band size, then the bandwidth gain α j for MSCi j
due to tree sharing is equal to
αj
r rG TG sT s ∑k
MSCi j
ij
m
b
ik
m
b
ij
ik
(4)
E3
E3
E4
E4
E3
Core Router
Core Router
T1
T1
Edge Router
C5
Edge Router
Edge Router
E1
C3
T2
C4
E6
Link
E2
C3
E7
C1
T2
C2
C2
T2
OBS Network
OBS Network
OBS Network
E8
E8
E6
Link
E2
E7
E7
C1
C6
E5
E1
E6
Link
E2
T1
E5
E5
E1
E4
Core Router
E8
Figure 1: Tree Sharing Strategies: Equal Coverage (left), Super Coverage (middle) and Overlapping Coverage (right).
One may apply the OC strategy as follows. First, one of the
four criteria, namely, the edge router overlap, core router overlap, link overlap, and tree sharing gain is selected. Then from
a set of given multicast sessions, choose a pair of two-session
with either the highest value of γE (γC or γL ) or the highest value
of α depending on the criterion applied. Afterwards, a third session (one of other multicast sessions not belonging to the pair
selected) is combined with the pair if this increases the value of
the criterion selected, and so on. Regardless of the initial criterion selected, traffic sharing gain α for the candidate MSC is
evaluated. If α is more than a threshold value η (say 1.0), the
MSC is formed. The same process is repeated for remaining
multicast sessions (if 2) to form another MSC, and so on.
Note that if α is used as the initial criterion, α is applied two
times (first for selection and second for examination). Fig. 1
(right) shows an example for OC where if the combination of
T1 and T2 has the highest value of the criterion applied, and its
traffic gain is over a given threshold, the two trees are grouped
into the same MSC.
3.2 Construction of Shared Trees
After one has decomposed a set of multicast sessions (Hi ) at an
edge router i into a number of MSCs according to one of the
tree sharing strategies, each MSC has to construct a ST by treating all the members in the subset of the multicast sessions as a
new multicast group for the purpose of burstification (forming
bursts) and burst delivery. Note that the cases for EC or SC are
trivial because one can use any existing tree in EC, and a super
tree in SC, respectively. For OC, we propose three ST construction algorithms to construct a ST TS = (V S , LS ) where V S is the
set of all nodes (edge and core routers), and LS is the set of all
links on ST, respectively. In addition, we consider an algorithm
for the purpose of comparison, called ST-NEW, in which a new
multicast tree for a MSC is constructed with all members in the
MSC by applying the multicast tree construction algorithm of
the multicast session.
3.2.1 Greedy Algorithm
In this algorithm, all nodes (core and edge routers) and links
belonging to the existing multicast trees of a MSC are used to
construct ST for MSC. More specifically, the following algorithm called ST-GREEDY is used.
ST-GREEDY Algorithm
/* i is the source (root) edge router of MSC j */
φ; V S
VS
i ; LS
φ;
VS
for each tree T jk MSC j do
C jk
E jk ;
VS VS
LS
LS
L jk ;
end for
Note that it is possible that the ST contains redundant links (e.g.
the links (C1 C2) and (C2 C3) in Fig. 1 (left)).
3.2.2 Breadth First Search (BFS) Algorithm
In this algorithm, we apply BFS to construct a ST based on
the existing trees of a MSC. Starting at the source edge router
(root), every link from u to a node v ( one of neighbors) is examined to see if v was on any existing tree T jk (i.e. if v E jk )
but not on the ST yet. If so, both the link and node v are added
to the ST, and the node v is added to a queue Q for future consideration. Then the process repeats for each node in the queue
Q until Q is empty. Note that the algorithm eliminates some redundant links but does not eliminate all (e.g. the link (C1 C2)
in Fig. 1 will still be there but the link (C2 C3) not.). The algorithm called ST-BFS is as follows.
ST-BFS Algorithm
/* i is the source edge router of MSC j */
V S = i ; LS = φ; Q = φ;
enqueue(Q i);
while (Q φ) do
u dequeue(Q);
for each link e from u to a neighbor v do
s E
s C
if ((v
k 1 jk
k 1 jk ) & (v
VS
v ;
VS
LS
LS
e ;
enqueue(Q v);
end for
end while
V S ))
3.2.3 Member-Initiated Algorithm
In this algorithm, we start with an existing multicast tree with
the largest number of members as the base of the new ST. Then
all other members perform an operation similar to a ”join” in
CBT [13] (or ”graft” in DVMRP [9]) by doing so, arguments
the base tree with additional nodes and links. The algorithm
called ST-MEMBER is as follows.
ST-MEMBER Algorithm
Tmax
Max(T jk ) where i=1,2,...,s;
VS
φ; LS
φ;
for each node v Tmax and its link l Lmax do
v ; LS
LS
l ;
VS VS
end for
s E do
for each edge router v
k 1 jk
while (v V S ) do
find upstream node vup on an existing tree T jk (
link v vup towards the source;
LS
LS
v vup ;
VS
VS
v ;
vup ;
v
end while
end for
Cloud of core routers
IP subnet
Edge router
Core router
Tmax ) and
Note that, if the existing trees T jk have been constructed using an efficient algorithm, then by putting the links on the existing tree whenever possible will result in a more efficient ST
than that constructed by ST-BFS. In addition, in ST-MEMBER,
there are no redundant links as in ST-GREEDY and ST-BFS.
As an example, in Fig. 1 (right), after choosing T2 as the T max ,
E4 and E7 will join a new ST (which is the same as T2 initially) according to the algorithm. Then the constructed new
ST will include links (C4,C1), (C1,C2), (C2,C3) and (C3,C6)
(just showing the links between core routers only). However,
ST-GREEDY and ST-BFS will have redundant links (C4,C5)
and (C5,C6) (ST-GREEDY only).
4 Simulation Study
4.1 Network Model and Assumptions
The network model used consists of edge routers and core
routers as shown in Fig. 2. Each edge router is an access point
to a backbone network consisting of core routers. For simulation, a random backbone network is generated. We assume
that there is a WDM link between nodes (the terms node and
router are used interchangeably) with an unlimited bandwidth
(i.e. a sufficient number of wavelengths available so that all
traffic at a source edge router can be routed to desired destination edge routers without blocking). Such an assumption
makes sense since we are only interested in the average amount
of bandwidth consumed per link by multicast traffic using different multicast schemes. More specifically, we inject a fixed
amount of unicast traffic, and a fractional amount of multicast
traffic into the network and measure, for instance, the average
amount of multicast traffic carried on each link. By making the
amount of multicast traffic injected to the network the same for
different multicast schemes, the measured amount of multicast
traffic per link represents the amount of bandwidth consumed
by the multicast traffic per link, and thus, the larger the amount,
the less efficient a multicast scheme is.
For unicast traffic, Dijkstra’s algorithm [2] is employed to
construct a routing table at each node. We assume that the aggregate data rate of unicast traffic from one edge router to all
other edge routers is 1 unit per second (e.g. 100 Gbps when
1 unit = 100Gb). All unicast traffic has an equal distribution of
the destination edge routers and thus the average data rate of the
Figure 2: An optical burst-switched WDM network.
unicast traffic from one edge router to another is 1 Ne
1
units per second.
For multicast traffic, it is assumed that all core routers are
multicast-capable and that every multicast session has one
source, a pre-determined membership and the same data rate
which is r 1 units per second (even though in the analysis in
Section 3 we used ri j for the data rate of the multicast session,
here we will use a percentage of unicast traffic). In addition, for
each multicast session, a source-specific multicast tree is constructed based on the shortest-path heuristic (SPH) [14].
One of the simulation parameters is the total number of multicast sessions Ns , whose source will be evenly distributed
among all the edge routers. In other words, the average number
of multicast sessions per edge router is Ns
Ne . In addition, for a given multicast session, every edge router (other than
source itself) has a probability p of being a member, so the average number of members (edge routers) per multicast session
is Ne
1 p (excluding the source).
In addition to some of the parameters mentioned so far, there
are a number of other parameters that affect the performance
of the multicast schemes. The following are parameters examined and their default values. First, the number of core routers
in the network is 40 and the average nodal degree of each core
router is 4. The GB size is perhaps the most important parameter affecting the performance of the several multicast schemes
and its default size in the simulation is 2 percent of the average
payload of unicast traffic. For example, if the average data rate
of the unicast traffic from one edge router to another is 1 Gbps
and the burst assembly time is 500 µs, then the average payload
length is 500 Kbits and the G is equal to 10 Kbits. The burst assembly time for unicast/multicast traffic is 500µs and 1000µs,
respectively. In addition, the amount of multicast traffic as a
percentage of that of unicast traffic is 5 percent by default in
the simulation and the number of multicast sessions per source
edge router is 15 on average. Finally, the average number of
members per multicast session is 70 percent of the total number of edge routers (i.e. p is 0.7) and the number of edge routers
per core router is 1.
Note that in simulation of TS-MCAST using the OC strategy, the default criterion is tree sharing gain, and the default
algorithm for ST construction is ST-MEMBER.
In this subsection, we present the simulation results. Whenever appropriate, we use the performance of S-MCAST as the
base, that is, we determine the ratio of the average amount of
multicast traffic per link using the two multicast schemes (MUCAST and TS-MCAST) over that using S-MCAST.
A. Effect of the number of core routers
Fig. 3 shows the effect of the network size (number of core
routers) on the ratio of the average amount of multicast traffic per link obtained by M-UCAST and TS-MCAST to that
obtained by the S-MCAST scheme. Note that in Fig. 3, the
GB size is the same for all network sizes. As can be seen
from Fig. 3, the relative performance of M-UCAST degrades
quickly. This is because as the network size increases (from 10
to 70), which results in the increase of the average path length
(from about 3.5 to 5.3 hops), the increase in the penalty due to
multiple transmissions of the same burst far exceeds the benefit of sharing GB with unicast traffic. It is also clear that TSMCAST with the OC strategy shows the best performance, although all TS-MCAST schemes show a gradual decrease in the
performance as the average path length (or number of hops) increases. If the number of hops is more than 5.5, there is no
gain from tree sharing. This, as well as the results showing that
the performance of TS-MCAST (EC) and TS-MCAST (SC)
quickly approach that of S-MCAST, indicates that the degree
of overlap among different multicast trees (sessions) reduces as
the network size increases.
1.5
S-MCAST
M-UCAST
TS-MCAST(EC)
TS-MCAST(SC)
TS-MCAST(OC-link)
TS-MCAST(OC-core)
TS-MCAST(OC-member)
TS-MCAST(OC-gain)
Ratio of multicast traffic per link to S-MCAST
1.4
1.3
1.2
1.1
GB size. In addition, Fig. 4 also shows the relative performance
of TS-MCAST (OC) when applying different criteria. We observe that with a small GB size the performance difference is
not much, but as the GB size increases, the performance difference becomes larger with the tree sharing gain being the best
criterion. It is not difficult to envision that in a mesh network
M-UCAST may outperform even TS-MCAST in terms of multicast traffic in some network conditions since no overhead due
to GBs (and control packets) exists for multicast traffic. Note
that the performance of EC/SC is not shown because it is very
close to that of S-MCAST, and whenever appropriate hereafter.
Ratio of multicast traffic per link to S-MCAST
4.2 Numerical Results
2.3
2.2
2.1
2
1.9
1.8
1.7
1.6
1.5
1.4
1.3
1.2
1.1
1
0.9
0.8
0.7
0.6
0.5
0.4
S-MCAST
M-UCAST
TS-MCAST(OC-link)
TS-MCAST(OC-core)
TS-MCAST(OC-member)
TS-MCAST(OC-gain)
0
1
2
3
4
5
6
7
8
9
10
11
Size of guard band (%) - percentage of average burst length of unicast traffic
Figure 4: Effect of the GB size: comparison of several multicast schemes with different criteria.
Fig. 5 shows the relative performance of TS-MCAST (OC)
when applying different ST construction algorithms. STGREEDY performs the worst and the performance difference
for other three algorithms is not much. However, the ST-BFS
and ST-NEW schemes requires more processing load than STMEMBER to construct the shared tree. Note that the performance of ST-MEMBER is very close to that of ST-NEW with
much less processing load.
1
Size of guard band (%)
0.9
0.01
1
2
5
7
10
1.0
0.99883
0.97369
0.77896
0.67928
0.57561
0.8
GREEDY
0.7
0.6
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
BFS
1.0
0.99760
0.94613
0.64570
0.53602
0.43014
MEMBER
1.0
0.99755
0.94580
0.64522
0.53562
0.42973
NEW
1.0
0.99750
0.94557
0.64555
0.53562
0.42972
Number of core routers
Figure 3: Effect of the number of core routers: comparison of
several multicast schemes.
B. Effect of the GB size
Note that the GB size is perhaps the most important parameter affecting the performance of various multicast schemes.
Fig. 4 shows the effect of the GB size. From Fig. 4, we observe that M-UCAST scheme performs the worst with a small
GB size, and becomes better as the GB size increases. This is
because as the GB size increases, the benefit of amortizing GB
with both multicast and unicast traffic increases. This is also
why the performance of TS-MCAST (OC) is improved with the
Figure 5: Comparison of the shared tree construction algorithms.
C. Effect of the membership size
The efficiency of tree sharing depends on the average membership size of each multicast session. Fig. 6 shows the effect
of the membership size on the performance of the multicast
schemes. As can be seen from Fig. 6, the relative performance
of all other multicast schemes to S-MCAST increases as the
membership size increases since more multicast trees will be
overlapped. The performance of the two tree sharing strategies,
EC and SC, improves drastically when the membership size is
above 80 percent. TS-MCAST (OC) results in the best performance which consumes only a half of the bandwidth when
compared to S-MCAST. However, M-UCAST scheme does
not provide any improvement in performance over S-MCAST.
1.4
Ratio of multicast traffic per link to S-MCAST
1.3
1.2
1.1
1
0.9
S-MCAST
M-UCAST
TS-MCAST(EC)
TS-MCAST(SC)
TS-MCAST(OC-link)
TS-MCAST(OC-core)
TS-MCAST(OC-member)
TS-MCAST(OC-gain)
0.8
0.7
0.6
UCAST and TS-MCAST. The first one is natural and the other
two are proposed to reduce the amount of GBs (and the number
of control packets) per unit of multicast data.
We have developed three tree sharing strategies, criteria and
shared-tree (ST) construction algorithms for allowing multiple
multicast sessions to mix data when assembling bursts, which
are then delivered via a ST. We have evaluated the performance
of various multicast schemes and our results suggest that the
proposed TS-MCAST scheme performs better than S-MCAST
in all cases as expected and that M-UCAST may perform better
than S-MCAST under certain conditions.
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0.5
0.4
20
30
40
50
60
70
80
90
100
Average percentage of edge routers as members of the multicast session
110
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Number of multicast sessions in the network
Figure 7: Effect of the number of multicast sessions in the network: comparison of several multicast schemes.
5 Conclusions
In this paper, we have studied three multicast schemes in optical burst-switched WDM networks, namely S-MCAST, M-
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