Adaptive Congestion

Control for Unpredictable

Cellular Networks

Flow

Highlight the unpredictability of cellular network

Verus

Comparing with TCP and its variants

Experiment Set-up

1. 2 commercial networks Du and Etisalat

2. Rack server

3. Laptop tethered to a mobile phone

1. Burst Scheduling

2. Competing Traffic

3. Channel Unpredictability

Verus

W(t+1) Next Sending Window

f Delay profile function

d(t) Network delay

𝛿(t) Delay increment/decrement

Verus

Delay Estimator Delay Profiler Window Estimator Loss Handler

Verus

1. Delay Estimator

Round trip delay(Dp,i) = current time – packet sent time

Verus

2. Delay Profiler

Verus

3. Window Estimator+

Verus

Loss Handler

Delay Profile Initialization and

Maintenance

Timeouts and Retransmissions

Timeout = 3 * delay

Finding the right values for the

parameters

Epoch Ɛ

Delay Profile Updates

𝛿1 and 𝛿2

Experiment

OPNET network simulator.

4 Android smartphones and 1 server. Both endpoints,

server and smartphones, send UDP packets with an

MTU size of 1400 bytes

Data rate for each device is set to 5 Mbps and 2.5

Mbps for downlink and uplink, respectively.

7 different scenarios with different mobility properties.

Finding the right values for the

parameters

Epoch Ɛ: Smaller, better. 5ms

Delay Profile Updates: 1s

𝛿1:1ms and 𝛿2:2ms

Evaluation

Macro-Evaluation

Throughput

Delay

Characteristics

Micro-Evaluation

Fairness

Adaptation

Macro-Evaluation: Comparison with Other TCP Variants

TCP Cubic

TCP New Reno

Sprout

TCP Cubic

Macro-Evaluation

Real-world

EvaluationTrace-driven

Evaluation

Real-world Evaluation

Etisalat network

Verus mobile device, TCP Verus, TCP Cubic,

Sprout laptop

Mode of each phone connect to appropriate

network to test both 3G and 4Gs

Performed at fixed places with no mobility and

simultaneously

Each run was 2 minutes and each experiment was

repeated 5 times

Trace-driven Evaluation

OPNET simulator

Traffic shaper

Shared Queue: Min of 3MBit, Max of 9MBit, Drop

Probability = 10%

Mobility

Fairness

Micro-Evaluation

3 laptops connected to a switch which is

connected to the server

Linux Traffic Control

1) Control server outgoing bandwidth

2) Imitate some form of delay for each client

1. Rapidly Changing Network

1. Rapidly Changing Network

2. Newly Arriving Flows

3. Verus vs TCP

4. Effect of Verus Delay Curve

Related

Work:

Legacy Congestion Control Protocols

Router-feedback-based Protocols

Recent Congestion Control Protocols

Cellular Performance

Points for

Discussion

Formulas

Choice of values for parameters

Real-World Evaluation

3G vs LTE experiments

Work:

Advanced 5G-TCP: Transport protocol for 5G Mobile Networks,

http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7983089

Radio Link and Transport Protocol Engineering for Future-Generation Wireless

Mobile Data Networks,

http://onlinelibrary.wiley.com/doi/10.1002/wcm.297/pdf

References Used:

Adaptive Congestion Control for Unpredictable Cellular Networks,

https://cs.nyu.edu/~jchen/publications/sigcomm15-zaki.pdf

TCP Congestion Control Comparison,

http://www.satnac.org.za/proceedings/2012/papers/2.Core_Network_Techn

ologies/15.pdf

Stochastic Forecasts Achieve High Throughput and Low Delay over Cellular

Networks, https://www.usenix.org/system/files/conference/nsdi13/nsdi13-

final113.pdf

Thank you ☺