Conference Paper

Compact tree plus algorithms for application-level multicast communications in multihome networks

Dept. of Commun. Network Eng., Okayama Univ., Japan
DOI: 10.1109/ICON.2005.1635456 Conference: Networks, 2005. Jointly held with the 2005 IEEE 7th Malaysia International Conference on Communication., 2005 13th IEEE International Conference on, Volume: 1
Source: IEEE Xplore
ABSTRACT
Application-level multicast (ALM) communications replicate packets on host level to deliver them from a single source to multiple clients, so that it can efficiently realize a variety of network applications using moving pictures such as video conferences, distance learning, and video-on-demands. In this paper, we propose the CT+ (compact tree plus) algorithm for finding a better ALM routing tree in terms of delay minimization between hosts. CT+ consists of a tree construction stage from the existing CT algorithm, and a newly added iterative tree improvement stage. Then, we define the extended ALM routing problem and its heuristic algorithm ExCT+, to optimize the effectiveness of the multihome network in ALM communications by selecting multihomed hosts and connections in the ALM routing tree simultaneously. For their evaluations, we construct a network simulation model named MINET (multiple-ISP network simulator), where the topology is composed of multiple ISP backbone networks with IX connections, and the network traffic is generated by following the M/M/1 queuing process. The simulation results using MINET verify the effectiveness of our algorithms.

Full-text

Available from: Teruo Higashino, Nov 25, 2014
Compact
Tree
Plus
Algorithms
for
Application-Level
Multicast
Communications
in
Multihome
Networks
Nobuo
Funabiki*
Megumi
Isogai*
Toru
Nakanishi*
Teruo
Higashinot
*
Department
of
Communication
Network
Engineering,
Okayama
University,
3-1-1
Tsushimanaka,
Okayama
700-8530,
Japan
t
Graduate
School
of
Information
Science
and
Technology,
Osaka
University,
1-5
Yamadaoka,
Suita,
Osaka
565-0871,
Japan
Abstract-
Application-level
multicast
(ALM)
communications
replicate
packets
on
host
level
to
deliver
them
from
a
single
source
to
multiple
clients,
so
that
it
can
efficiently
realize
a
variety
of
network
applications
using
moving
pictures
such
as
video
conferences,
distance
learning,
and
video-on-demands.
In
this
paper,
we
propose
the
CT+
(Compact
Tree
Plus)
algorithm
for
finding
a
better
ALM
routing
tree
in
terms
of
delay
minimization
between
hosts.
CT+
consists
of
a
tree
construction
stage
from
the
existing
CT
algorithm,
and
a
newly
added
iterative
tree
improvement
stage.
Then,
we
define
the
extended
ALM
routing
problem
and
its
heuristic
algorithm
ExCT+,
to
optimize
the
effectiveness
of
the
multihome
network
in
ALM
communications
by
selecting
multihomed
hosts
and
connections
in
the
ALM
routing
tree
simultaneously.
For
their
evaluations,
we
construct
a
network
simulation
model
named
MINET
(Multiple-ISP
NETwork
simulator),
where
the
topology
is
composed
of
multiple
ISP
backbone
networks
with
IX
connections,
and
the
network
traffic
is
generated
by
following
the
M/M/1
queuing
process.
The
simulation
results
using
MINET
verify
the
effectiveness
of
our
algorithms.
1.
INTRODUCTION
Recently,
a
variety
of
network
applications
with
delivering
moving
pictures
such
as
video
conferences,
distance
learning,
and
video-on-demands
have
been
demanded
due
to
the
spread
of
broadband
networks
in
every
place.
In
these
applications,
the
multicast
communication
plays
a
key
technology
of
de-
livering
high
bandwidth
packets
from
a
single
source
to
multiple
destinations
while
reducing
server
loads
and
saving
network
transmission
bands.
In
multicast
communications,
intermediate
nodes
on
a
routing
path
replicate
packets
to
deliver
them
to
multiple
clients.
Currently,
the
application-
level
multicast
(ALM)
communication
has
been
noticed
as
a
practical
multicast,
where
packets
are
replicated
on
host
level,
instead
of
router
level
as
in
the
IP
multicast
(IPM)
[I]-[22].
ALM
has
several
advantages
over
IPM,
that
it
does
not
require
sophisticated
routers
to
handle
IPM
functions
and
multicast
IP
addresses,
and
it
allows
the
flow
control
and
the
packet
retransmission
scheme
at
the
transport
layer,
because
each
pair
of
hosts
is
connected
through
the
unicast
connection.
Further-
more,
ALM
provides
the
flexibility
of
selecting
connections
between
hosts
by
users.
In
ALM,
the
routing
path
between
hosts
usually
becomes
a
tree,
where
each
vertex
represents
a
host
and
each
edge
represents
a
unicast
connection
between
two
hosts.
Therefore,
the
routing
path
is
called
an
ALM
routing
tree
in
this
paper.
The
proper
selection
of
an
ALM
routing
tree
is
very
important
for
the
delay
minimiization
that
is
essential
in
various
ALM
applications
involving
motion
picture
streaming
and
large
data
sharing
among
distributed
hosts
while
concering
the
resource
limitation
at
hosts.
This
ALM
routing
problem
has
been
formulated
as
an
NP-hard
combinatorial
optimization
problem,
and
several
algorithms
have
been
reported
[8]-[12].
The
compact
tree
(CT)
algorithm
[9]
has
been
known
as
a
typical
algorithm
for
this
problem.
CT
greedily
constructs
a
tree
by
selecting
connections
one-by-one
such
that
resulting
partial
trees
minimize
the
maximum
delay
between
any
pair
of
hosts
while
satisfying
the
constraint.
However,
the
solution
quality
of
CT
may
be
insufficient,
because
it
does
not
adopt
the
improvement
stage
that
has
usually
been
adopted
in
heuristic
algorithms
for
NP-hard
problems
[25].
Based
on
a
local
search
method,
the
improvement
stage
sometimes
drastically
refines
an
initial
solution
of
the
construction
stage.
ALM
has
several
drawbacks
in
the
increase
of
delay
due
to
longer
paths
than
IPM,
the
increase
of
host
loads
due
to
packet
replications
and
plural
connections
at
hosts,
and
the
increase
of
consumed
network
bands
due
to
transmissions
of
duplicated
packets
on
network
links.
These
drawbacks
are
particularly
undesirable
for
streaming
applications
including
video
conferences
where
the
data
synchronization
between
hosts
is
inevitable.
For
this
solution,
we
have
proposed
the
introduction
of
the
multihome
network
to
ALM.
In
the
mul-
tihome
network,
each
host
may
have
connections
with
one
or
more
internet
service
providers
(ISPs).
By
selecting
the
best
ISP
under
the
current
network
condition
after
measuring
RTT
and
the
available
bandwidth
[23],
the
multihome
network
can
alleviate
these
drawbacks
in
ALM.
To
be
more
precise,
the
multihome
network
can
reduce
communication
loads
on
1-4244-0000-7/05/$20.00
©2005
IEEE.
139
Page 1
the
access
links
between
hosts
and
ISP
nodes
(host
access
points)
by
using
different
ISP
links,
and
on
the
links
in
internet
exchangers
(IXs)
by
exchanging
ISPs
at
hosts
instead
of
exchanging
them
at
IXs.
In
addition,
the
multihome
network
provides
the
possibility
of
drastically
shortening
the
routing
path
by
using
single-ISP
connections
where
both
end
hosts
are
connected
with
the
same
ISP.
In
this
paper,
we
define
the
ALM
routing
problem
in
the
multihome
network,
and
propose
its
compact
tree
plus
algorithm
(CT+)
by
adding
the
improvement
stage
to
CT.
This
improvement
stage
repeats
the
replacement
of
a
randomly
se-
lected
connection
by
another
one
that
does
not
only
satisfy
the
constraint
but
also
minimizes
the
delay
among
candidates.
This
replacement
is
always
processed
regardless
of
the
increase
of
the
delay,
as
long
as
such
a
connection
exists.
This
mandatory
replacement
avoids
the
convergence
to
a
poor
local
minimum.
In
reality,
the
current
network
environment
does
not
allow
every
host
to
have
connections
with
multiple
ISPs.
Besides,
the
multihome
network
usually
costs
more
than
the
conventional
singlehome
network.
In
practical,
only
a
part
of
hosts
partic-
ipating
ALM
applications
should
be
multihomed.
Therefore,
in
this
paper,
we
define
the
extended
ALM
routing
problem
in
the
multihome
network
to
select
multihomed
hosts
and
connec-
tions
simultaneously
under
the
limitation
of
the
multihomed
cost,
and
present
its
extended
CT+
algorithm
(ExCT+).
We
also
study
the
effect
of
the
increase
of
multihomed
hosts
in
the
delay
minimization
in
ALM.
For
evaluations
of
our
algorithms
and
schemes
for
ALM,
we
construct
a
network
simulation
model
named
MINET
(Multi-
ISP
NETwork
simulator).
The
network
topology
consists
of
multiple
ISP
backbone
networks
and
one
IX
for
ISP
connec-
tions.
The
IX
directly
connects
one
node
in
each
ISP
with
a
node
in
any
other
ISP.
The
ISP
backbone
network
exists
on
the
same
square
area.
The
topology
is
generated
by
following
the
Waxman
method
[24],
and
the
node
nearest
to
the
center
of
the
square
is
connected
to
a
node
in
IX.
The
delay
of
each
link
is
given
by
the
sum
of
the
transmission
delay,
the
switching
delay,
and
the
buffering
delay
[26].
The
background
traffic
is
provided
through
random
generations
and
terminations
of
unicast
connections
by
following
the
M/M/1
queuing
model
[27].
Each
connection
is
routed
along
the
shortest
path
when
any
buffering
delay
is
zero.
When
a
new
connection
arrives,
its
requested
bandwidth
is
consumed
on
every
link
along
the
path.
When
the
total
consumed
bandwidth
exceeds
the
link
capacity,
the
buffering
delay
occurs
there.
The
rest
of
this
paper
is
organized
as
follows:
Section
II
formulates
the
ALM
routing
problem
in
the
multihome
network
and
presents
CT+.
Section
III
defines
the
extended
ALM
routing
problem
and
presents
ExCT+.
Section
IV
out-
lines
MINET.
Section
V
evaluates
the
performance
of
our
algorithms
using
MINET
with
the
increase
of
multihomed
hosts.
Section
VII
concludes
this
paper
with
some
discussions
on
further
studies.
II.
CT+
FOR
ALM
ROUTING
PROBLEM
A.
ALM
Routing
Problem
in
Multihome
Network
In
the
ALM
routing
problem
in
the
multihome
network, con-
nections
between
hosts
are
described
by
a
directed
weighted
graph
G
(V,
E,
W).
A
vertex
v
E
V
represents
a
host
in
the
ALM
application.
A
directed
edge
e
E
E
is
assigned
a
weight
d(e)
E
W
to
represent
the
delay
of
the
packet
transmission
through
the
corresponding
connection.
When
one
end
host
of
a
connection
has
connections
with
a
ISPs
and
another
one
does
with
b
ISPs
in
the
multihome
network,
the
number
of
directed
edges
corresponding
to
this
connection
is
given
by
2
x
a
x
b.
In
ALM,
a
host
may
replicate
packets
to
send
them
to
mul-
tiple
hosts
individually.
If
the
number
of
packet
replications
is
too
large,
both
the
loads
of
the
host
and
the
access
link
connecting
the
host
and
the
access
point
of
an
ISP
become
too
high.
Thus,
the
limit
of
the
number
of
replications
or
host
connections
for
host
v
in
the
ALM
routing
tree
T
is
given
as
the
degree
constraint
A'degree
In
T,
the
both-way
delay
between
any
pair
of
hosts
should
be
minimized
for
motion
picture
streaming
applications.
From
the
above
discussion,
the
ALM
routing
problem
in
the
multihome
network
is
summarized
as
follows:
<
ALM
routing
problem
in
multihome
network
>
*
Input:
a
connection
graph
G
=
(V,
E,
W)
with
multiple
edges,
a
degree
limit
A'egree.
*
Output:
an
ALM
routing
tree
T
=
(V?
ET)
with
ETCE.
.
Constraint:
the
number
of
packet
replications
at
host
v
is
less
than
or
equal
to
its
limit:
degreeT(v)
.
A
degree
(I)
where
degreeT(V)
is
the
number
of
children
of
host
v
in
T.
Objective:
to
minimize
the
maximum
delay
between
any
pair
of
hosts
E:
E
=rmax
d(e)
-min
(2)
j
eE',3
)(
where
Pij
represents
the
routing
path
between
host
i
and
host
j
in
T.
B.
Delay
Observation
The
delay
of
a
connection
is
observed
by
sending
a
probe
packet
from
the
source
host
to
the
destination
and
calculating
the
difference
between
the
sending
time
and
the
receiving
one,
before
the
algorithm
is
applied.
The
synchronization
of
clocks
in
every
host
is
necessary
in
this
scheme
where
it
can
be
realized
by
using
GPS
(global
positioning
system)
or
NTP
(network
time
protocol).
Here,
we
note
that
if
we
always
observe
the
delay
for
every
connection,
the
load
of
this
delay
observation
becomes
very
high,
because
n
hosts
require
0(n2)
observations
even
for
a
singlehome
network.
Thus,
we
need
to
confine
connections
for
delay
observations
in
the
implementation
of
CT+
by
pruning
the
connections
whose
delays
have
been
very
large
in
past
observations.
140
Page 2
111.
ExCT+
FOR
EXTENDED
ALM
ROUTING
PROBLEM
The
proposed
CT+
is
a
two
stage
heuristic
algorithm
for
the
ALM
routing
problem.
The
tree
construction
stage
adopts
the
procedure
of
CT,
and
the
tree
improvement
stage
adopts
the
state
transition
method
that
is
a
variant
of
a
local
search
method
[25].
1)
Tree
Construction
Stage
by
CT:
CT
greedily
constructs
an
ALM
routing
tree
T
by
initially
including
only
one
host
in
V
into
T
and
then,
sequentially
expanding
T
by
adding
a
connection
one-by-one
that
satisfies
the
degree
constraint
and
minimizes
the
maximum
delay
between
any
pair
of
hosts
in
the
resulting
tree.
In
our
implementation,
every
host
is
tried
as
the
initial
host
in
T,
and
the
best
result
in
terms
of
the
delay
among
all
the
trials
is
selected
as
the
final
solution
from
CT,
to
improve
the
solution
quality.
<
CT
>
1)
Initialize
T=
(VT,
ET)
by
VT
=v
E
V
and
ET
=
$
2)
Terminate
the
procedure
if
VT
=
V.
3)
Add
one
connection
to
T
such
that
(1)
it
connects
a
host
in
VT
and
another
one
in
VIVT,
(2)
it
satisfies
the
degree
constraint
in
T,
and
(3)
it
minimizes
the
maximum
delay
between
two
hosts
in
T
among
candidates.
4)
Return
to
step
2).
2)
Tree
Improvement
Stage:
The
tree
improvement
stage
repeats
modifications
of
T
by
replacing
a
randomly
selected
connection
in
T
by
a
different
one
that
satisfies
the
degree
constraint
if
it
exists.
This
compulsory
replacement
aims
the
avoidance
of
a
poor
local
minimum
convergence
that
can
often
occur
in
heuristic
algorithms.
<
CT+
>
1)
Adopt
T
from
CT
as
an
initial
tree,
set
the
best
found
tree
Tbest
=
T,
and
initialize
the
number
of
iterations
t
by
0.
2)
Terminate
the
procedure
if
t
=
K
x
IVI,
and
output
Tbest.
3)
Randomly
select
a
connection
in
ET
and
remove
it
from
T.
This
operation
separates
T
into
two
partitions.
4)
Add
a
different
connection
to
T
such
that
(1)
it
connects
the
two
partitions, (2)
it
satisfies
the
degree
constraint,
and
(3)
it
minimizes
the
maximum
delay
among
can-
didates.
If
such
a
connection
does
not
exist,
return
the
removed
connection
to
T.
5)
Memorize
T
as
Tbest
if
the
maximum
delay
between
two
hosts
in
T
is
smaller
than
that
in
Tbest.
6)
Increment
t
by
1,
and
return
to
step
2).
3)
Time
Complexity
of
CT+:
In
the
construction
stage,
step
3)
requires
O(1V12)
time.
In
the
improvement
stage,
step
4)
requires
O(1V13)
time
where
each
of
O(1V12)
connections
in
E
is
evaluated
with
O(IVI)
delay
calculations.
As
a
result,
the
time
complexity
of
CT+
is
O(KIVI4).
A.
Extended
ALM
Routing
Problem
in
Multihome
Network
As
mentioned
in
Section
1,
every
host
in
an
ALM
ap-
plication
may
not
be
multihomed
due
to
the
cost
and
ISP
infrastructures.
If
the
total
cost
for
multihomed
hosts
is
limited,
multihomed
hosts
should
be
selected
with
appropriate
ISP
connections
simultaneously
when
the
ALM
routing
tree
is
constructed.
Therefore,
we
define
the
extended
ALM
routing
problem
in
the
multihome
network
to
cope
with
this
issue.
As
the
input
to
this
problem,
we
assume
the
following
conditions:
1)
Every
host
has
already
been
connected
with
one
ISP.
2)
The
list
of
available
ISPs
is
given
at
each
host,
and
the
delay
of
any
connection
between
hosts
using
an
additional
ISP
in
the
list
can
be
observed
without
an
extra
cost.
3)
The
total
cost
for
multihomed
hosts
is
limited
by
a
constant
Zcost-
Then,
for
this
problem,
the
following
multihome
cost
con-
straint
is
imposed
additionally
to
the
ALM
routing
problem:
(3)
E
c(v,
k)
<
Acost
(v,k)
EM
where
c(v,
k)
is
the
cost
for
using
the
k-th
ISP
connection
at
host
v,
and
M
is
the
set
of
additionally
used
ISP
connections
in
T.
B.
Proposal
of
ExCT+
In
the
proposed
ExC'T+,
any
additional
ISP
connection
is
used
only
if
it
satisfies
the
multihome
cost
constraint.
Specifically,
in
step
3)
of
the
construction
stage
and
step
3)
of
the
improvement
stage
in
CT+,
an
additional
ISP
connection
is
selected
there
when
either
of
the
following
two
conditions
is
satisfied
in
addition
to
satisfying
the
conditions
for
CT+:
.
the
additional
ISP
connection
has
already
been
used
at
the
host,
the
total
cost
does
not
exceed
Acost
when
the
ISP
connection
is
newly
used
at
the
host.
Besides
in
the
implementation,
in
step
2)
of
the
improve-
ment
stage,
if
the
removed
connection
from
T
uses
an
addi-
tional
ISP
connection
and
no
other
in
T
uses
it
at
the
host,
the
multihome
cost
is
decreased
by
its
cost.
IV.
MULTI-ISP
NETWORK
SIMULATOR
MINET
A.
Topology
The
topology
of
MINET
consists
of
multiple
ISP
backbone
networks
(10
ISPs
in
simulations)
and
one
IX
as
illustrated
in
Figure
1.
The
topology
of
an
ISP
backbone
network
is
generated
by
the
Waxman
method
[24],
where
nodes
(100
nodes
in
simulations)
are
randomly
located
on
a
square
called
the
network
field
(3,
OOOkm
on
each
side
in
simulations).
In
each
ISP
network,
the
node
nearest
to
the
center
in
the
network
field
is
selected
as a
node
in
IX.
IX
connects
any
pair
of
nodes
directly.
141
C
Proposal
of
CT+
Page 3
'SPI
1SP3
>
node
Fig.
].
MINET
topology.
B.
Link
Delay
The
delay
of
a
link
is
given
by
the
sum
of
the
transmission
delay,
the
switching
delay,
and
the
buffering
delay.
The
transmission
delay
is
the
time
required
to
propagate
packets
physically
through
the
signal
transmission
line,
and
is
given
by
dividing
the
line
length
with
the
light
speed
(300,
OOOkm/s).
The
switching
delay
is
the
time
to
switch
received
packets
to
their
destination
ports
at
the
router,
and
can
be
constant
(lOms
in
simulations).
The
buffering
delay
is
the
time
for
packets
to
stay
in
buffers
to
wait
for
their
delivery
from
output
ports,
and
is
given
by
dividing
the
queued
packet
size
with
the
transmission
bandwidth
of
the
link.
The
buffering
delay
appears
when
the
amount
of
packetflows
through
a
link
exceeds
the
link
capacity.
In
simulations,
the
link
capacity
is
set
5Gbps
for
IX
and
lGbps
for
ISP.
C.
Background
Traffic
The
goal of
the
algorithms
in
this
paper
is
to
find
an
ALM
routing
tree
with
the
minimum
delay
between
any
pair
of
hosts
under
conventional
network
conditions.
As
the
network
background
traffic
in
MINET,
unicast
connections
are
randomly
generated
and
terminated
between
any
pair
of
nodes
by
following
the
M/M/1
queuing
model
at
each
node.
That
is,
a
connection
arrives
at
a
node
by
the
Poisson
probability
with
a
randomly
selected
destination
node,
and
it
continues
by
the
exponential
probability.
The
connection
is
routed
through
the
shortest
path
from
the
source
node
to
the
destination
when
any
buffering
delay
is
zero.
The
amount
of
packet
flows
of
the
links
along
the
path
is
increased
by
the
given
traffic
of
the
connection,
which
is
randomized
between
100Kbps
and
1OMbps
in
simulations.
In
order
to
generate
heterogeneous
network
loads,
we
intro-
duce
the
dispersion
of
connection
arrival
rates
and
burst
con-
nections.
In
the
former
scheme,
all
the
nodes
are
categorized
into
a
high-load
group
and
a
low-load
group
by
a
constant
ratio
(1:
4
in
simulations).
Then,
the
connection
arrival
rate
is
randomly
selected
between
the
highest
value
and
the
lowest
one
for
each
node.
In
simulations,
these
values
are
set
0.8s-1
/
0.2s-1
for
the
high-load
group,
and
0.4s-1
/
0.1s-1
for
the
low-load
group.
The
termination
rate
is
randomly
selected
between
ls-1
and
0.1s-1
at
any
node.
For
the
latter
scheme,
a
constant
fraction
of
connections
(10%
in
simulations)
is
selected
as
burst
connections,
where
the
link
capacity
(lGps)
becomes
fully
occupied
for
ls.
V.
EVALUATIONS
BY
SIMULATIONS
A.
Simulation
Steps
The
performance
of
the
proposed
CT+
and
ExCT+
is
evaluated
through
simulations
using
MINET.
Actually,
each
MINET
simulation
is
performed
through
the
following
steps:
1)
The
host
configuration
is
set
up.
2)
The
network
state
transits
from
the
initial
one
to
a
stationary
one
by
calculating
background
traffics
for
1,
OOOs.
3)
The
delay
of
a
connection
between
each
pair
of
hosts
through
every
available
ISP
connection
is
observed
for
lOOs.
4)
The
algorithm
finds
an
ALM
routing
tree.
5)
The
delay
of
a
connection
between
each
pair
of
hosts
through
the
ALM
routing
tree
is
observed
for
lOOs,
and
the
maximum
delay
between
two
hosts
is
calculated,
while
an
ALM
application
(1.5Mbps)
is
executed.
B.
Host
Configuration
The
number
of
hosts
n
for
an
ALM
application
is
set
10
and
50
in
our
simulations.
The
host
locations
are
random-
ized
within
the
network
field.
The
number
of
additional
ISP
connections
at
each
host
is
fixed
to
one.
Thus,
two
ISPs
are
selected
randomly
for
each
host,
where
the
first
one
becomes
the
established
connection,
and
the
second
is
the
additional
one.
The
nearest
node
in
the
corresponding
ISP
backbone
network
from
the
host
location
is
selected
as
the
access
node
to
the
host.
The
same
tree
degree
limit
A'gree
is
set
3
or
4
for
every
host.
The
multihome
cost
c(V,
k)
is
set
1
for
any
ISP
connection
at
any
host.
Thus,
the
cost
limit
Acost
is
equivalent
to
the
upper
bound
on
the
number
of
multihomed
hosts.
C.
Delay
Observation
The
delay
of
a
connection
is
calculated
by
the
sum
of
delays
associated
with
the
links
along
the
path
from
its
source
host
to
the
destination.
For
accuracy,
the
delay
observation
is
applied
100
times
at
every
1
second
for
any
connection,
and
their
average
value
is
used
for
evaluations.
D.
Simulation
Results
Figures
2-5
show
changes
of
the
maximum
delay
between
two
hosts
by
using
ALM
routing
trees
found
by
CT
(dashed
line),
CT+
(double
dashed
line),
and
ExCT+
(solid
line),
when
the
percentage
of
multihomed
hosts
among
all
the
hosts
increases
from
0%
to
100%.
142
Page 4
3
2.5
C's
0
2
0
1.5
9
I
0.5
0
CT
0
20
40
60
multihomed
host
percentage
(%)
80
100
Fig.
2.
Maximum
delay
at
ALM
application
(n
=
10,
Aldegree
=
3).
1)
Comparison
between
Three
Algorithms:
In
any
figure,
the
delay
by
CT+
is
slightly
smaller
than
the
delay
by
CT,
whereas
the
delay
by
ExCT+
is
much
smaller
than
the
delays
by
others
when
a
part
of
hosts
are
multihomed.
The
combination
of
the
improvement
stage
and
the
multihomed
host
selection
in
ExCT+
is
very
effective
in
reducing
the
delay
of
the
ALM
routing
tree.
Thus,
the
repetition
of
the
simultaneous
selection
of
connections
and
multihomed
hosts
is
critical
for
providing
a
high-quality
ALM
routing
tree.
2)
Effect
of
Multihome
Network:
In
any
figure,
the
delay
decreases
as
the
percentage
of
multihomed
hosts
increases.
Thus,
the
results
confirm
the
effectiveness
of
the
multihome
network
in
reducing
the
delay
in
ALM
by
increasing
the
number
of
single-ISP
connections
in
the
tree.
However,
this
effect
becomes
small
for
the
case
of
n
=
50,
because
many
connections
even
in
the
singlehome
network
can
be
single-ISP
ones,
as
the
number
of
ISPs
is
fixed
10.
We
note
that
when
20%
of
hosts
can
be
multihomed,
ExCT+
achieves
almost
the
same
delay
for
100%.
Thus,
a
small
number
of
multihomed
hosts
can
reduce
the
delay
in
ALM.
The
detailed
investigation
on
the
relationships
between
the
number
of
multihomed
hosts,
the
number
of
ISPs,
and
the
delay
reduction
by
our
algorithms
will
be
in
our
future
studies.
VI.
RELATED
WORK
In
[1],
Sheu
et
al.
first
introduced
the
peer-to-peer
technique
for
video
streaming
applications.
In
[2],
Aharoni
et
al.
first
proposed
the
concept
of
ALM
communications.
In
[3],
Cohen
et
al.
defined
a
family
of
minimum
path
set
problems
for
ALM
communications,
and
proposed
the
maximum
bottle-
neck
tree
algorithm
for
its
maximum
bottleneck
version.
In
[4],
Pendarakis
et
al.
presented
a
centralized
middleware
of
generating
the
minimum
spanning
tree
for
ALM
communi-
cations
called
ALMI.
In
[5][61,
Chu
et
al.
proposed
an
ALM
protocol
of
generating
the
shortest
widest
path
tree
for
ALM
communications
on
a
mesh-type
overlay
network.
In
[9][l0],
Shi
et
al.
proposed
CT
for
ALM
communications
using
MSNs
(multicast
service
nodes)
that
have
been
deployed
around
net-
2.5
0
V
2
,
1.5
1
0.5
0
0
20
40
60
80
100
multihomed
host
percentage
(%)
Fig.
3.
Maximum
delay
at
ALM
application
(n
=
10,
Qderee
=
4)
3
2.5
0
V)
2
_
I,
0.5
0
20
40
60
80
100
mulihomed
host
percentage
(%a)
Fig.
4.
Maximum
delay
at
ALM
application
(n
=
50,
A'
=-3).
degree
works
as
multicast
routers
performed
at
host
level.
They
also
proposed
several
modifications
of
CT
so
that
as
many
ALM
requests
as
possible
can
be
afforded
in
the
MSN
network.
In
[II],
Banerjee
et
al.
formulated
the
minimum
average-latency
degree-bounded
directed
spanning
tree
problem
for
the
MSN
network,
and
proposed
its
distributed
iterative
approach
where
the
performance
is
compared
with
optimum
solutions
and
CT
solutions.
In
[12],
Yun
et
al.
proposed
a
genetic
algorithm
for
an
ALM
routing
problem
with
two
objectives.
In
[13],
Tran
et
al.
proposed
an
ALM
solution
called
ZIGZAG
organizing
an
efficient
routing
tree
with
height
logarithmic
by
the
number
of
clients
and
a
node
degree
bound
by
a
constant.
In
[14],
Zhang
et
al.
proposed
a
hybrid
multicast
framework
called
Host
Multicast
of
automating
the
interconnection
of
IP-multicast
enabled
islands
and
providing
the
multicast
delivery
to
end
hosts
where
IP
multicast
is
not
available.
In
[15],
Cheuk
et
al.
also
proposed
the
similar
scheme
called
Island
Multicast
using
overlay
connections
between
IP-multicast
enabled
islands
and
supporting
IP-multicast
for
intra-islands.
In
[16],
Bawa
et
al.
argued
that
masking
peer
transience
is
the
primary
challenge
of
ALM
communications
for
short
lifetime
hosts
participating
143
Page 5
0
Ca
id
-e
----~
.5
.
.........-
..........
.
.
-----........-----
.t-
......
-*
....................
05CT+
.5
CT+
_---.
0
20
40
60
multihomed
host
percentage
(%)
Fig.
5.
Maximum
delay
at
ALM
application
(n
=
51
in
long-durationed
multicast
sessions,
and
outl]
layer
to
separate
policy
decisions
in
handling
from
end-applications.
Based
on
their
concept
an
ALM
solution
called
PeerCast
[171.
In
[18
presented
a
middleware
with
the
multipath
rou
ALM
communications.
In
[19],
Yamashita
(
a
middleware
for
multiparty
video
communi(
Li
et
al.
proposed
a
QoS-aware
routing
pro
communications
on
overlay
networks
called
Zhu
et
al.
proposed
schemes
of
applying
the
with
a
two-redundant
multicast
graph
to
imp:
throughput
in
ALM.
In
[22],
Abad
et
al.
sur
of
ALM
solutions,
and
classified
them
accor
teristics
such
as
overlay
building
technique,
m
scalability.
VII.
CONCLUSION
This
paper
has
presented
the
CT+
(Comr
algorithm
for
the
ALM
(Application-Level
Mi
problem,
and
the
ExCT+
(Extended
CT+)
a
timize
the
effectiveness
of
the
multihome
ne
communications.
Using
the
MINET
(Multipl,
simulator),
the
effectiveness
of
these
algoritl
Our
future
studies
will
include
discussions
on
t]
tree
modification
to
deal
with
joins
and/or
during
ALM
applications,
the
use
of
availab]
connections
in
algorithms,
and
the
introductic
concepts
in
MINET.
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    [Show abstract] [Hide abstract] ABSTRACT: Multicast services can be provided either as a basic network service or as an application-layer service. Higher level multicast implementations often provide more sophisticated features and can provide multicast services at places where no network layer support is available. Overlay multicast networks offer an intermediate option, potentially combining the flexibility and advanced features of application layer multicast with the greater efficiency of network layer multicast. In this paper, we introduce the multicast routing problem specific to the overlay network environment and the related capacity assignment problem for overlay network planning. Our main contributions are the design of several routing algorithms that optimize the end-to-end delay and the interface bandwidth usage at the multicast service nodes within the overlay network. The interface bandwidth is typically a key resource for an overlay network provider, and needs to be carefully managed in order to maximize the number of users that can be served. Through simulations, we evaluate the performance of these algorithms under various traffic conditions and on various network topologies. The results show that our approach is cost-effective and robust under traffic variations.
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    [Show abstract] [Hide abstract] ABSTRACT: In this paper, we analyze several models of overlay multicast routing problem, and bring forward a new model based on multi-objective programming, discussing the solution of the model simultaneously. Then we employ the Prufer sequence as chromosome code and then propose a genetic algorithm to solve the model. Finally, we analyze the complexity of the algorithm.
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  • Source
    [Show abstract] [Hide abstract] ABSTRACT: All of the advantages of application-layer overlay networks arise from two fundamental properties: 1) the network nodes in an overlay network, as opposed to lower-layer network elements such as routers and switches, are end systems and have capabilities far beyond basic operations of storing and forwarding; 2) the overlay topology, residing above a densely connected Internet protocol-layer wide-area network, can be constructed and manipulated to suit one's purposes. We seek to improve end-to-end throughput significantly in application-layer multicast by taking full advantage of these unique characteristics. This objective is achieved with two novel insights. First, we depart from the conventional view that overlay nodes can only replicate and forward data. Rather, as end systems, these overlay nodes also have the full capability of encoding and decoding data at the message level using efficient linear codes. Second, we depart from traditional wisdom that the multicast topology from source to receivers needs to be a tree, and propose a novel and distributed algorithm to construct a two-redundant multicast graph (a directed acyclic graph) as the multicast topology, on which network coding is applied. We design our algorithm such that the costs of link stress and stretch are explicitly considered as constraints and minimized. We extensively evaluate our algorithm by provable analytical and experimental results, which show that the introduction of two-redundant multicast graph and network coding may indeed bring significant benefits, essentially doubling the end-to-end throughput in most cases.
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    [Show abstract] [Hide abstract] ABSTRACT: Network layer multicast is know as the most efficient way to support multicast sessions. However, for security, QoS and other considerations, most of the real-time application protocols can be better served by upper layer (transport or application) multicast. We propose a scheme called M-RTP for multicast RTP sessions. The idea behind this scheme is to set up the multicast RTP session over a set of unicast RTP sessions, established between the various participants (source and destinations) of the multicast session. We then address the issue of finding a set of paths with maximum bottleneck for an M-RTP session. We show that this problem is NP-complete, and propose several heuristics to solve it
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  • Source
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  • Source
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