Computer Science Department
School of Computer Science, Carnegie Mellon University
The Impact of False Sharing on Shared Congestion Management
Srinivasa Aditya Akella, Srinivasan Seshan, Hari Balakirshman*
Keywords: Congestion control, shared congestion management,
Several recent proposals have been made for sharing congestion
information across concurrent flows between end-systems, where the
proposed granularity for sharing has ranged from all flows to a common
host, to all hosts on a shared LAN. This paper addresses the problem
of false sharing caused by these proposals: two or more flows
sharing congestion state may in fact not share the same bottleneck.
We characterize the origins of false sharing into two distinct cases:
(i) networks with QoS enhancements such as differentiated services,
where a flow classifier segregates flows into different queues, and
(ii) networks with path diversity where different flows to the same
destination address are routed differently, a situation that occurs in
dispersity routing, load-balancing, and with network address
translators (NATs). We evaluate the impact of false sharing on flow
performance and consider whether it might cause a bottleneck link to
become persistently overloaded. We then consider how false sharing
can be detected by a sender and how different metrics (loss rate,
delay distribution, and reordering) compare for this purpose.
Finally, we consider the issue of how a sender must respond when it
detects false sharing.
Our simulation results show that persistent overload can be avoided
with window-based congestion control even for extreme false sharing,
but higher bandwidth flows run at a slower rate. We find that delay
and reordering statistics can be used to develop robust detectors of
false sharing and are superior to those based on loss patterns. We
also find, somewhat surprisingly, that it is markedly easier to detect
and react to false sharing than it is to start by isolating flows and
merging their congestion state together afterwards.
*MIT Laboratory for Computer Science, 2000 Technology Square, Cambridge, MA 02139