reducing multicast traffic load for cellular networks using ad hoc networks
DESCRIPTION
Reducing Multicast Traffic Load for Cellular Networks using Ad Hoc Networks. Li Lao (UCLA) Jun-Hong Cui (UCONN). Background. Hybrid cellular/ad hoc networks for unicast applications Increase the coverage of base stations Avoid dead spots - PowerPoint PPT PresentationTRANSCRIPT
Reducing Multicast Traffic Load
for Cellular Networks using Ad Hoc Networks
Li Lao (UCLA)Jun-Hong Cui (UCONN)
August 23, 2005 QShine 2005 2
Background Hybrid cellular/ad hoc networks for unicast applicati
ons Increase the coverage of base stations Avoid dead spots Re-direct traffic from congested cells to non-congested Improve system throughput
Hybrid cellular/ad hoc networks for multicast applications Enhance network performance, especially for heterogeneou
s receivers (Park & Kasera, WCNC’05) Focus on individual groups only and do not consider QoS wh
en multiple groups co-exist in the network
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Our Focus A base station handles multiple multicast
groups simultaneously Cellular mode: base station may be overloaded
NOTE: we use point to point link for multicast Ad hoc mode: ad hoc net may be congested
NOTE: broadcast is not assumed Our approach: to balance between two modes
Goal: Minimize the workload on the base station while
maximizing the utilization of the ad hoc network (without exceeding its capacity)
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The ProblemGroup Selection Problem:
Base station determines:
How many groups? Which groups?
To be switched to ad hoc mode
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An Example
DE
C
A
FG
H
BT1
T2
T3
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Roadmap Problem Formulation
Network Model Problem
Proposed Algorithms Performance Evaluation Conclusions
August 23, 2005 QShine 2005 7
Network Model Network N(V, E) (for a cell)
|V| = m, |E| = n For a node i, its capacity is Ci
Multicast groups G |G| = ng
For a group gj G, its required data rate is rj
Bandwidth for gj in cellular mode is: |gj|x rj
A multicast routing algorithm
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Wireless Interference IEEE 802.11 uses CSMA/CA
RTS/CTS/DATA/ACK
X X
X
AB
Observation I: Neither the sender’s neighbors nor the receivers’ neighbors can transmit or receive data
C
D
E
FG
Observation II: If we want to reserve a unit of bandwidth at two nodes, we must also reserve a unit of bandwidth at their neighbors
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Bandwidth Requirement of Multicast Groups For a multicast group gj,
Compute its multicast tree tj
For each link on tj, compute the required bandwidth at corresponding nodes
Obtain a bandwidth vector bwj = (bw1j, bw2j, …, bwm
j), where bwij represents the required bandwidth at node i for gj
For a set of multicast groups G’ The required bandwidth at node i for these groups:
'Gg
ij
j
bw
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Example
AB
C
D
EF
G
LinkAffected nodes
C-A A,B,C,D,E
A-B A,B,C,E,F
B-E A,B,E,F
B-F A,B,E,F,G
Bandwidth Vector for (A,B,C,D,E,F,G): (4,4,2,1,4,3,1)
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Problem Formulation Multicast Group Selection Problem
Input: Ad hoc network with Ci (iV), a set of multicast groups G with bwj and rj (gjG)
Output: a subset G’ G to maximize the bandwidth savings Constraint: (iV)
Essentially a Multi-dimensional Knapsack Problem Input: A knapsack with m-dimensional size (b1, …, bm), and a s
et of items S = 1, …, n, each having a size rj = (r1j, …, rmj) and a value vj
Output: A subset S’ S that maximizes the values Constraint: (i[1,m])
'
||Gg
jj
j
rg
'Gg
iij
j
Cbw
Group Item Ad hoc network Knapsack
'Sj
iij br 'Sj
jv
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Roadmap Problem Formulation Proposed Algorithms
Integer Linear Program Dynamic Algorithm Naive Dynamic Algorithm
Performance Evaluation Conclusions
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Integer Linear Program Define:
Objective: maximize bandwidth savings
Constraint: node capacity
otherwise ,0
selected is group if ,1 jxj ],1[ gnj
gn
j
ijij Cxbw1
],1[ mi
gn
j
jjj xrg1
||max
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Dynamic Algorithm Utility function for each group gjG
Group g join: O(mn+mng) Admit g in ad hoc mode and reserve bandwidth if enough resource Otherwise, try to swap g with an existing group g’ in ad hoc mode s
uch that u(g’) < u(g) If g’ releases its bandwidth, g can be admitted If there are more than one such groups, the one with the smallest utility s
hould be selected as g’ Group g leave: O(mnng)
Release bandwidth Try to select a group g’ to be swapped in
Vi
ij
jjj
bw
rggu
||)( Bandwidth savings if the group is selected
Total amount of required bandwidth
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Naive Dynamic Algorithm Group join
If enough resource in the ad hoc network, admit this group in ad hoc mode and reserve bandwidth
Otherwise use cellular mode O(mn)
Group leave If ad hoc mode, release bandwidth O(m)
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Roadmap Problem Formulation Proposed Algorithms Performance Evaluation Conclusions
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Simulation Settings Wireless network
Up to 120 nodes A cell of 500*500 m2
Communication range: 115m Channel capacity: 100~500 units
Multicast groups Group size uniformly distributed (mean: 20~100) Group members randomly distributed in the network and
one member randomly selected as source Group arrivals follow a Poisson distribution and lifetime
follows an exponential distribution Each group requires 1 unit of bandwidth 80 active groups
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Metrics Number of admitted members Number of admitted groups
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Impact of Network Density
0
100
200
300
400
500
600
700
800
900
1000
20 40 60 80 100 120 140Total number of nodes
Nu
mb
er o
f ad
mit
ted
mem
ber
s
ILP
Dynamic
Naive
0
5
10
15
20
25
30
35
40
45
50
20 40 60 80 100 120 140Total number of nodes
Nu
mb
er o
f ad
mit
ted
gro
up
s ILPDynamicNaive
Average group size: 20, Channel capacity: 500
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Impact of Channel Capacity
0
100
200
300
400
500
600
0 100 200 300 400 500 600Channel capacity
Nu
mb
er o
f ad
mit
ted
mem
ber
s
ILPDynamicNaive
0
5
10
15
20
25
30
0 100 200 300 400 500 600Channel capacity
Num
ber
of a
dmitt
ed g
roup
s
ILPDynamicNaive
Network nodes: 120, Average group size: 20
August 23, 2005 QShine 2005 21
Impact of Group Size
0
50
100
150
200
250
0 20 40 60 80 100 120Average group size
Nu
mb
er o
f ad
mit
ted
mem
ber
s
ILPDynamicNaive
0
1
2
3
4
5
6
0 20 40 60 80 100 120Average group size
Nu
mb
er o
f ad
mit
ted
gro
up
s
ILP
DynamicNaive
Network nodes: 120, Channel capacity: 100
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Roadmap Problem Formulation Proposed Algorithms Performance Evaluations Conclusions
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Conclusions Developed a simple and effective model for
computing bandwidth requirement of multicast groups in wireless networks
Formulated the multicast group selection problem as a multi-dimensional knapsack problem
Proposed an ILP formulation and a utility-based dynamic algorithm
Simulation study has shown that the dynamic algorithm can achieve near-optimal solutions
Future Work: Member dynamics Distributed implementation
August 23, 2005 QShine 2005 24
Questions?