Performance Evaluation of TCP over Multiple Paths in Fixed Robust Routing
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Performance Evaluation of TCP over Multiple Paths
in Fixed Robust Routing
Wenjie Chen, Yukinobu Fukushima, Takashi Matsumura, Yuichi Nishida, and Tokumi Yokohira
The Graduate School of Natural Science and Technology,Okayama University, Japan
1CQR 2011
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BackgroundBackground
Penetration of bandwidth-consuming applications(e.g., P2P file sharing and video streaming)
Traffic patterns in ISP networks become variableNeed for ISP networks to accommodate those
variable traffic patterns
Routing for variable traffic patterns Dynamic routing
Increases operational complexity Can lead to route instability
Fixed robust routing [1, 3] Low operational complexity No route instability (static routing)
CQR 2011 2
[1] M. Kodialam, T. V. Lakshman, and S. Sengupta, “Maximum throughput routing of traffic in the hose model,” in Proceedings of IEEE INFOCOM2006, pp. 1–11, Apr. 2006. [3] V. Tabatabaee, A. Kashyap, B. Bhattacharjee, R. J. La, and M. A. Shayman, “Robust routing with unknown traffic matrices,” in Proceedings of IEEE INFOCOM 2007, pp. 2436–2440, May 2007.
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Fixed Robust RoutingFixed Robust Routing
Tries to achieve the best worst-case performance (e.g., maximum link load), given variable traffic patterns Traffic patterns are assumed to vary within the region
specified by some traffic variation models (e.g., hose model)
Performs multipath routing Traffic of every source-destination pair is routed on multiple
paths
Multipath routing causes out-of-order packet arrivals
TCP performance may be degraded
CQR 2011 3
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Research ObjectiveResearch Objective
Investigation of TCP performance over general fixed robust routing
Proposal of fixed robust routing algorithm that tries to improve TCP performance in addition to decreasing maximum link load
CQR 2011 4
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Formulation of Fixed Robust Routing Problem [3]Formulation of Fixed Robust Routing Problem [3]
CQR 2011 5
Input
Output
: Candidate paths of every (i, j) pair
: Set of traffic matrices that follow hose and pipe traffic model
: Maximum link load
: Fraction of traffic of the corresponding (i, j) pair routed on path p
Linear semi-infinite programming problem(convertible to polynomial size linear programming problem [3])
: Set of all links in the network
: capacity of link l
Path 1
Path 2
Path 3
[3] V. Tabatabaee, A. Kashyap, B. Bhattacharjee, R. J. La, and M. A. Shayman, “Robust routing with unknown traffic matrices,” in Proceedings of IEEE INFOCOM 2007, pp. 2436–2440, May 2007.
subject to
Node i Node j
: Set of paths routed on link l
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Performance Degradation of TCP over Fixed Performance Degradation of TCP over Fixed Robust RoutingRobust Routing
CQR 2011 6
Time
Reception of threeduplicated Acks
Time
Source Destination
1
2
3
4
1
2
3
4
Packets on shorter path overtakepreceding packets on longer path
Out-of-order packet arrivals at destination host
Source host receives three duplicatedAcks and decreases its congestionwindow size
TCP throughput is degraded
Shorter Path
Longer Path
4 3
2
1SourceDestination
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Evaluation of TCP Performance over Fixed Evaluation of TCP Performance over Fixed Robust Routing: Simulation modelRobust Routing: Simulation model
Two kinds of path between R1 and R2 L (Long path): 2.0 + d [ms] S (Short path): 2.0 [ms]
Combination of paths: SLLL, SSLL, SSSL One TCP connection for every end-host pair (Si , Di)
Si ’s data transmission rate: 20 [Mbps]
CQR 2011 7
S1
S2
S3
S4
S5
R1 R2
D1
D2
D3
D4
D5
Bandwidth: 50 [Mbps]Propagation delay: 0.2 [ms]
Bandwidth: 100 [Mbps]Propagation delay: 2.0 + d [ms] for L 2.0 [ms] for S
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Evaluation of TCP Performance over Fixed Evaluation of TCP Performance over Fixed Robust Routing: ResultRobust Routing: Result Larger delay difference
more candidates for overtaking packet Higher ratio of shorter path
higher probability of three out-of-order packet arrivals
CQR 2011 8
d (delay difference between path L and path S) [ms]
0
20
40
60
80
100
0 0.4 0.8 1.2 1.6 2 2.4 2.8
Tota
l th
rou
gh
pu
t [M
bp
s]
d [ms]0.4 0.8 1.2 1.6 2.0 2.4 2.80
0
20
40
60
80
100
Tot
al t
hro
ughp
ut [
Mbp
s]SLLL
SSLL
SSSL
Lower TCP throughput
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Proposal of Fixed Robust Routing Taking Account of TCP Proposal of Fixed Robust Routing Taking Account of TCP Performance (1/2): Basic StrategyPerformance (1/2): Basic Strategy
CQR 2011 9
Input
Output
: Maximum link loadsubject to
Linear semi-infinite programming problem
Our proposed fixed robust routing selects such candidate paths ( ) that avoid TCP performance degradation as much as possible
: Set of all links in the network
: capacity of link l: Set of paths routed on link l
: Set of traffic matrices that follow hose and pipe traffic model
: Candidate paths of every (i, j) pair
: Fraction of traffic of the corresponding (i, j) pair routed on path p
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Proposal of Fixed Robust Routing Taking Account of TCP Proposal of Fixed Robust Routing Taking Account of TCP Performance (2/2): AlgorithmPerformance (2/2): Algorithm
10
Step. 1 Selection of candidate paths of every source-destination pair Step. 1.1 We select K shortest hop paths Step. 1.2 From the K paths, we select M paths with the minimum delay difference between the shortest and the longest delay pathsStep. 2. We solve the formulated problem and obtain maximum link load (t) and fraction (xp) of traffic routed on every path. When solving the problem, we bound fraction of traffic routed on the shortest delay path by α
Path 1, 15ms
Path 2, 8ms
Path 3, 3ms
Path 4, 14ms
Path 5, 10ms
Node i Node j
MDD-LF (Minimum Delay Difference with Limited Fraction)
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Simulation ModelSimulation Model
One TCP connection for every node-pair (Ri , Rj) Source host’s data transmission rate: 10 [Mbps] Parameter settings in MDD-LF
K = 5 M = 2 α = 0.25
Comparison: k-shortest A straightforward fixed robust routing algorithm that selects M (= 2) shortest hop paths as candidate paths for every node-pair
CQR 2011 11
R4[2%]
4.7ms
2.8ms
7.0ms
3.5ms 2.8ms 3.5ms
3.5ms
3.5ms
3.5ms3.5ms
8.4ms
8.4ms
4.9ms
5.6ms
11.2ms
2.8ms
9.1ms
0.7ms
1.4ms
1.4ms
1.4msLink bandwidth: 1 [Gbps]
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0
0.2
0.4
0.6
0.8
1
k-shortest MDD-LF
Ma
xim
um
lin
k lo
ad
0
2
4
6
8
10
k-shortest MDD-LF
Th
rou
gh
pu
t [M
bp
s]Evaluation ResultsEvaluation Results
Compared to k-shortest, MDD-LF: 27% higher throughput
Candidate path selection policy of MDD-LF is effective for improving TCP throughput
CQR 2011 12
0
2
4
6
8
10
Ave
rag
e T
hrou
ghpu
t [M
bps]
k-shortest MDD-LF k-shortest MDD-LF0
0.2
0.4
0.6
0.8
1
Max
imum
link
load
Compared to k-shortest, MDD-LF: 2.3 times higher load MDD-LF tends to select longer hop paths than k-shortest
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Conclusions and Future WorkConclusions and Future Work
Conclusions Investigation of TCP throughput over fixed robust routing
Larger delay difference Higher ratio of shorter path
Proposal of fixed robust routing algorithm that tries to improve TCP throughput
MDD-LF: 27% higher throughput but 2.3 times higher load
Future work Performance evaluation of our proposed algorithm in detail Modification of our proposed algorithm
Selection of link-disjoint paths as candidate paths
CQR 2011 13
Lower TCP throughput
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Number of Candidates for Overtaking packetsNumber of Candidates for Overtaking packets
CQR 2011 14
d (delay difference between path L and path S) [ms]
0
20
40
60
80
100
0 0.4 0.8 1.2 1.6 2 2.4 2.8
Tota
l th
rou
gh
pu
t [M
bp
s]
d [ms]0.4 0.8 1.2 1.6 2.0 2.4 2.80
0
20
40
60
80
100
Tot
al t
hro
ughp
ut [
Mbp
s] SLLL
SSLL
SSSL
# of candidates for overtaking packets
0 1 2 3 4 5 6
TimeTime
Source Destination
1
2
3
4
1
2
3
4
d = 1.0
0.4
Average packet transmission interval
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Evaluation of TCP Performance over Fixed Evaluation of TCP Performance over Fixed Robust Routing: ResultRobust Routing: Result Larger delay difference
more candidates for overtaking packet Higher ratio of shorter path
higher probability of three out-of-order packet arrivals
SLLL: 0.012 SSLL: 0.063 SSSL: 0.11
CQR 2011 15
d (delay difference between path L and path S) [ms]
0
20
40
60
80
100
0 0.4 0.8 1.2 1.6 2 2.4 2.8
Tota
l th
rou
gh
pu
t [M
bp
s]
d [ms]0.4 0.8 1.2 1.6 2.0 2.4 2.80
0
20
40
60
80
100
Tot
al t
hro
ughp
ut [
Mbp
s]SLLL
SSLL
SSSL
Lower TCP throughput
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Traffic Variation Models Assumed in Fixed Traffic Variation Models Assumed in Fixed Robust RoutingRobust Routing
Hose traffic model
Pipe traffic model
CQR 2011 16
T =
t11 t12 t1n ・・・t21 t22 ・・・ t2n
t21 t22 ・・・ t2n
・・・
・・・
・・・・・・
: Upper bound on traffic volume that enters the network at node i (e.g., bandwidth of external ingress link of node i)
: Upper bound on traffic volume that leaves the network at node j (e.g., bandwidth of external egress link of node j)
T =
t11 t12 t1n ・・・t21 t22 ・・・ t2n
t21 t22 ・・・ t2n
・・・
・・・
・・・・・・
: Upper bound on traffic volume from node i to node j (The value is determined based on traffic histories or service level agreement)
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Evaluation ResultsEvaluation Results
Compared to k-shortest, MDD: 22% higher throughput MDD-LF: 27% higher throughput
candidate path selection policy of MDD and MDD-LD are effective for improving TCP throughput
CQR 2011 17
0
2
4
6
8
10
k-shortest MDD MDD-LF
Th
rou
gh
pu
t [M
bp
s]
0
0.2
0.4
0.6
0.8
1
k-shortest MDD MDD-LF
Ma
xim
um
lin
k lo
ad
0
2
4
6
8
10
Ave
rag
e T
hrou
ghpu
t [M
bps]
k-shortest MDD MDD-LF k-shortest MDD MDD-LF0
0.2
0.4
0.6
0.8
1
Max
imum
link
load
Compared to k-shortest, MDD: 1.7 times higher load MDD-LF: 2.3 times higher load
MDD and MDD-LF tend to select longer hop paths than k-shortest
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Evaluation of TCP Performance over Fixed Evaluation of TCP Performance over Fixed Robust Routing: ResultRobust Routing: Result Larger delay difference
more candidates for overtaking packet Higher ratio of shorter path
higher probability of three out-of-order packet arrivals
SLLL: 0.012 SSLL: 0.063 SSSL: 0.11
CQR 2011 18
d (delay difference between path L and path S)
0
20
40
60
80
100
0 0.4 0.8 1.2 1.6 2 2.4 2.8
Tota
l th
rou
gh
pu
t [M
bp
s]
d [ms]0.4 0.8 1.2 1.6 2.0 2.4 2.80
0
20
40
60
80
100
Tot
al t
hro
ughp
ut [
Mbp
s]SLLL
SSLL
SSSL
Lower TCP throughput
Average packet transmission interval
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Proposal of Fixed Robust Routing Taking Account of TCP Proposal of Fixed Robust Routing Taking Account of TCP Performance (2/2): AlgorithmPerformance (2/2): Algorithm
19
Step. 1 Selection of candidate paths of every source-destination pair Step. 1.1 We select K shortest hop paths Step. 1.2 From the K paths, we select M paths with the minimum delay difference between the shortest and the longest delay pathsStep. 2. We solve the formulated problem and obtain maximum link load (t) and fraction (xp) of traffic routed on every path. In MDD-LF, we bound fraction of traffic routed on the shortest delay path by α
Path 1, 15ms
Path 2, 8ms
Path 3, 3ms
Path 4, 14ms
Path 5, 10ms
MDD (Minimum Delay Difference) MDD-LF (MDD with Limited Fraction)and
Node i Node j
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Simulation ModelSimulation Model
One TCP connection for every node-pair (Ri , Rj) Each source host’s data transmission rate: 10 [Mbps] Parameter settings in MDD and MDD-LF
K = 5 M = 2 α = 0.25
Comparison: k-shortest A straightforward fixed robust routing that selects M (= 2) shortest hop paths as candidate paths for every node-pair
CQR 2011 20
R4[2%]
4.7ms
2.8ms
7.0ms
3.5ms 2.8ms 3.5ms
3.5ms
3.5ms
3.5ms3.5ms
8.4ms
8.4ms
4.9ms
5.6ms
11.2ms
2.8ms
9.1ms
0.7ms
1.4ms
1.4ms
1.4msLink bandwidth: 1 [Gbps]
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Conclusions and Future WorkConclusions and Future Work
Conclusions Investigation of TCP throughput over fixed robust routing
Larger delay difference Higher ratio of shorter path
Proposal of fixed robust routing algorithms that try to improve TCP throughput
MDD: 22% higher throughput but 1.7times higher load MDD-LF: 27% higher throughput but 2.3 times higher load
Future work Performance evaluation of our proposed algorithms in detail Modification of our proposed algorithms
Selection of link-disjoint paths as candidate paths
CQR 2011 21
Lower TCP throughput