1 research outputs found
Shared Bottleneck Detecction Based on Trend Line Regression for Multipath Transmission
The current deployed multipath congestion control algorithms couple all the
subflows together to avoid bandwidth occupation aggressiveness if the subflows
of multipath transmission protocol share common bottleneck with single path
TCP. The coupled congestion control algorithms can guarantee well fairness
property in common bottleneck but result in rate increase conservativeness in
none-sharing bottleneck situation. Thus, the throughput of multipath session
can be further improved when combing with effective shared bottleneck detection
mechanism. This paper proposes a delay trend line regression method to detect
if flows share common bottleneck. Deduced from TCP fluid model, the packet
round trip delay signal shows linear increase property during the queue
building up process of the narrowest link and the delay trend line slopes of
two flows are in close proximity if they traverse the same bottleneck link. The
proposed method is implemented on multipath QUIC golang codebase and extensive
simulations are performed to validate its effectiveness in detecting out flows
traversing common bottleneck. If the subflows are detected out via a common
bottleneck, the sender would perform coupled congestion control algorithm and
perform congestion control seperately on flow level in none sharing bottleneck
case. Results show a multipath session with two subflows can obtain 74\% gain
on average in throughput compared with single path connection when Linked
Increases Algorithm (LIA) is in combination with trend line regession shared
bottlenck detection algorithm in none shared bottleneck, and show well fairness
property in common bottleneck scenarios