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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

CQR 2011

Background

- Penetration of bandwidth-consuming applications(e.g., P2P file sharing and video streaming)
Traffic patterns in ISP networks become variable

- Need 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)

- Dynamic routing

[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.

CQR 2011

Fixed 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 arrivalsTCP performance may be degraded

- Traffic of every source-destination pair is routed on multiple paths

CQR 2011

Research 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

Formulation of Fixed Robust Routing Problem [3]

Linear semi-infinite programming problem(convertible to polynomial size linear programming problem [3])

Output

Input

: Maximum link load

subject to

: Fraction of traffic of the corresponding (i, j) pair routed on path p

: Candidate paths of every (i, j) pair

: capacity of link l

: Set of paths routed on link l

: Set of all links in the network

: Set of traffic matricesthat follow hose and pipe traffic model

Path 1

Node i

Node j

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.

CQR 2011

Performance Degradation of TCP over Fixed Robust Routing

4

3

Shorter Path

2

Packets on shorter path overtake

preceding packets on longer path

Source

Destination

1

Longer Path

Source

Destination

Out-of-order packet arrivals at destination host

1

2

Source host receives three duplicated

Acks and decreases its congestionwindow size

3

4

2

3

Reception of three

duplicated Acks

4

TCP throughput is degraded

1

Time

Time

CQR 2011

Evaluation of TCP Performance over Fixed Robust Routing: Simulation model

Bandwidth: 100 [Mbps]

Propagation delay: 2.0 + d [ms] for L

2.0 [ms] for S

- 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]

D1

S1

D2

S2

S3

D3

R1

R2

S4

D4

Bandwidth: 50 [Mbps]

Propagation delay: 0.2 [ms]

S5

D5

CQR 2011

Evaluation of TCP Performance over Fixed Robust Simulation modelRouting: Result

- Larger delay difference more candidates for overtaking packet
- Higher ratio of shorter path higher probability of three out-of-order packet arrivals

Lower TCP throughput

100

SLLL

80

60

SSLL

Total throughput [Mbps]

SSSL

40

20

0

0

0.4

1.6

0.8

1.2

2.0

2.4

2.8

d (delay difference between path L and path S) [ms]

CQR 2011

Proposal of Fixed Robust Routing Taking Account of TCP Performance (1/2): Basic Strategy

Our proposed fixed robust routing selects such candidate paths ( ) that avoid TCP performance degradation as much as possible

subject to

Linear semi-infinite programming problem

Output

Input

: Maximum link load

: Fraction of traffic of the corresponding (i, j) pair routed on path p

: Candidate paths of every (i, j) pair

: capacity of link l

: Set of paths routed on link l

: Set of all links in the network

: Set of traffic matrices that follow hose and pipe traffic model

CQR 2011

Proposal of Fixed Robust Routing Taking Account of TCP Performance (2/2): Algorithm

MDD-LF (Minimum Delay Difference with Limited Fraction)

Step. 1 Selection of candidate paths of every source-destination pair

Step. 1.1 We select Kshortest hop paths Step. 1.2 From the Kpaths, we select Mpathswith the minimum delay differencebetween the shortest and the longest delay paths

Step. 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

Node i

Node j

Path 4, 14ms

Path 5, 10ms

Simulation Model Performance (2/2): Algorithm

2.8ms

- 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

Link bandwidth: 1 [Gbps]

1.4ms

9.1ms

11.2ms

3.5ms

3.5ms

4.7ms

1.4ms

7.0ms

3.5ms

1.4ms

R4

3.5ms

3.5ms

0.7ms

[2%]

3.5ms

2.8ms

5.6ms

2.8ms

8.4ms

8.4ms

4.9ms

CQR 2011

Evaluation Results Performance (2/2): Algorithm

Compared to k-shortest,

MDD-LF: 27% higher throughput

Candidate path selection policy of MDD-LF is effective for improving TCP throughput

Compared to k-shortest,

MDD-LF: 2.3 times higher load

MDD-LF tends to select longer hop paths than k-shortest

1

10

0.8

8

0.6

6

Maximum link load

Average Throughput [Mbps]

0.4

4

0.2

2

0

0

k-shortest

k-shortest

MDD-LF

MDD-LF

CQR 2011

Conclusions and Future Work Performance (2/2): Algorithm

- 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

- Investigation of TCP throughput over fixed robust routing
- Future work
- Performance evaluation of our proposed algorithm in detail
- Modification of our proposed algorithm
- Selection of link-disjoint paths as candidate paths

Lower TCP throughput

CQR 2011

Number of Candidates for Overtaking packets Performance (2/2): Algorithm

d = 1.0

Average packet transmission interval

Source

Destination

100

1

0.4

SLLL

80

2

60

SSLL

3

Total throughput [Mbps]

2

SSSL

40

4

3

# of candidates for overtaking packets

20

1

1

2

3

4

5

6

0

4

0

0

0.4

1.6

0.8

1.2

2.0

2.4

2.8

d (delay difference between path L and path S) [ms]

Time

Time

CQR 2011

Evaluation of TCP Performance over Fixed Robust Performance (2/2): AlgorithmRouting: 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

Lower TCP throughput

100

SLLL

80

60

SSLL

Total throughput [Mbps]

SSSL

40

20

0

0

0.4

1.6

0.8

1.2

2.0

2.4

2.8

d (delay difference between path L and path S) [ms]

CQR 2011

Traffic Variation Models Assumed in Fixed Robust Routing Performance (2/2): Algorithm

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

・

Hose traffic model

Pipe traffic model

: Upper bound on traffic volume that

enters the network at node i

(e.g., bandwidth of external ingress link of node i)

t11

t12

t1n

t21

t2n

t22

T =

: Upper bound on traffic volume that

leaves the network at node j

(e.g., bandwidth of external egress link of node j)

t21

t2n

t22

: Upper bound on traffic volume from node i to node j

(The value is determined based on traffic histories or service level agreement)

t11

t12

t1n

t2n

t21

t22

T =

t21

t2n

t22

CQR 2011

Evaluation Results Performance (2/2): Algorithm

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

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

1

10

0.8

8

0.6

6

Maximum link load

Average Throughput [Mbps]

0.4

4

0.2

2

0

0

MDD

k-shortest

MDD

k-shortest

MDD-LF

MDD-LF

CQR 2011

Evaluation of TCP Performance over Fixed Robust Performance (2/2): AlgorithmRouting: 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

Lower TCP throughput

100

SLLL

80

60

SSLL

Total throughput [Mbps]

SSSL

40

20

Average packet transmission interval

0

0

0.4

1.6

0.8

1.2

2.0

2.4

2.8

d (delay difference between path L and path S)

CQR 2011

Proposal of Fixed Robust Routing Taking Account of TCP Performance (2/2): Algorithm

MDD (Minimum Delay Difference)

and

MDD-LF (MDD with Limited Fraction)

Step. 1 Selection of candidate paths of every source-destination pair

Step. 1.1 We select Kshortest hop paths Step. 1.2 From the Kpaths, we select Mpaths with the minimum delay difference between the shortest and the longest delay paths

Step. 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

Node i

Node j

Path 4, 14ms

Path 5, 10ms

Simulation Model Performance (2/2): Algorithm

2.8ms

- 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

Link bandwidth: 1 [Gbps]

1.4ms

9.1ms

11.2ms

3.5ms

3.5ms

4.7ms

1.4ms

7.0ms

3.5ms

1.4ms

R4

3.5ms

3.5ms

0.7ms

[2%]

3.5ms

2.8ms

5.6ms

2.8ms

8.4ms

8.4ms

4.9ms

CQR 2011

Conclusions and Future Work Performance (2/2): Algorithm

- 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

- Investigation of TCP throughput over fixed robust routing
- Future work
- Performance evaluation of our proposed algorithms in detail
- Modification of our proposed algorithms
- Selection of link-disjoint paths as candidate paths

Lower TCP throughput

CQR 2011

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