A Rate-based TCP Congestion Control Framework for Cellular Data Networks
COM2 Level 4
Executive Classroom, COM2-04-02
Abstract:
Modern 3G/4G cellular data networks have vastly different characteristics
from other wireless networks such as Wi-Fi networks. It is also becoming
more pervasive with the reducing cost of smartphones and cellular data
plans. In this thesis, we investigate the major issues of cellular data networks
and propose a radical TCP congestion control mechanism to overcome these
problems.
Firstly, cellular data networks are highly asymmetric. Downstream TCP
flows are thus affected by a concurrent uplink flow or a congested and slow
uplink due to the ACK packets being delayed. Secondly, packet losses are
very rare due to the hybrid-ARQ scheme used in the link-level protocol. Thus,
this causes the cwnd in the TCP congestion control algorithm to grow until
the buffer overflows. As ISPs typically provision huge buffers, this causes the
bufferbloat problem where the end-to-end delay becomes very large. Thirdly,
recent stochastic forecasting techniques have been used to predict the network
bandwidth to prevent excessive sending of packets to reduce the overall delay.
However, such techniques are complicated and require a long computation or
initialization time and often overly sacrifice on throughput.
To address these issues, we propose a new rate-based congestion control
technique and developed a TCP congestion control framework upon which
various algorithms can be built on. In our rate-based framework, the sending
rate is set by estimating the available bandwidth from the receive rate at the
receiver. To achieve stability and to adapt to changing network conditions,
we oscillate the sending rate above and below the receive rate which will
fill and drain the buffer respectively. By observing the buffer delay, we can
choose when to switch between the filling and draining of the buffer. By
controlling the various parameters, we can control the algorithm to optimize
for link utilization by keeping the buffer always occupied, or for latency by
keeping buffer occupancy low.
We implemented our framework into the TCP stack of the Linux kernel
and developed two rate-based algorithms, RRE and PropRate. The algorithms
were evaluated using the ns-2 simulator as well as using a trace-driven
network emulator, and also tested on real cellular data networks. We show
that by controlling the various parameters, the algorithms can optimize and
tradeoff between throughput and delay. In addition, we also implemented
two state-of-the-art forecasting techniques Sprout and PROTEUS into our
framework and evaluated them using our network traces. We found that
while forecasting techniques can reduce the delay, a quick reacting rate-based
algorithm can perform just as well, if not better by maintaining a
higher throughput.
Finally, our work advances the current TCP congestion control technique
by introducing a new framework upon which new algorithms can be built
upon. While we have showed that our new algorithms can achieve good
tradeoffs with certain parameters, how the parameters can be chosen to match
the current network conditions is room for further research. Similar to how
many cwnd-based congestion control algorithms have been developed in the
past, we believe that our framework opens new possibilities in the research
community to explore a rate-based congestion control for TCP in emerging
networks. In addition, because our framework is compatible with existing
TCP stacks, it is suitable for immediate deployment and experimentation.