review: A comparison of mechanisms for improving TCP performance over wireless
- How can we improve the end-to
end performance of TCP over lossy, wireless hops? Must the connection be split into a
lossy and a reliable section?
Should the packet loss be detected in the link layer or the
- A comparative analysis of
several distinct techniques to improve end-to-end performance in lossy
network segments. A presentation of
the different methods for improvement followed by an actual study of their
performance in practice.
A. The 3 techniques
for increasing end to end throughput and goodput are:
A reliable Link Layer protocol that uses knowledge of
TCP. (example: LL-TCP-AWARE)
A split-connection approach to divide the lossy and
reliable sections. (example: SPLIT-SMART based selective acknowledgement)
End to end schemes (example: E2E-IETF-SACK)
- The performance of the
TCP-aware link-layer schemes is about 1.75-2 times better than E2E-SMART
and about 9 times better than TCP-RENO.
It also has noticeably better goodput than SPLIT-START.
- The objective of the new
wireless protocols is to provide a mechanism by which the transport
protocol can be made aware of losses unrelated to network congestion and
react appropriately to such losses.
- Critique the main
System researchers and
builders should recognize that the lossy wireless links in an end to end
connection do not necessarily have to be segregated from a normal reliable
section. They must use different
acknowledgements or perform reliability at the link-layer, but do not have
to be split. As we continue to add
more heterogeneous types of network segments to the internet there is
increasing demand to provide seamless integration without making changes
to the internet as a whole.
- Significance- 2
The article is more of an evaluation of the
current implementations than an actual discovery. There evidence is somewhat conclusive,
but should be considered more of a review than a discovery.
- Convincing- 3 Each of the implementations are well explained and
they do present some actual network data.
But the data they present is over a small spectrum and not
necessarily representative in all cases.
Many of their claims lack scientific proof or adequate data.