1. Internet Research Group at Clemson University
Issues associated with Application Level Metrics and Assessments for Transport Services – An Overview
Kalyan CHINTALAPATI
7/18/2019
Internet Research Group at Clemson University

2. Let me ask you something
Suppose that you approach an ISP and ask him/her about their dial-up connection.
ISP: We guarantee you a maximum bandwidth of 56.6Kbps.
You: Then what about the access ?
ISP: it is “fast”.
You: How “fast”?
ISP: Well...err...umm.. It is “Fast”...<<that's all he/she can tell you about it>>
Now consider the case where a multi-national firm wants to build a world-wide-intranet and they approach the service-provider and ask them the same questions and imagine their reaction if they get the same answers.
7/18/2019
Internet Research Group at Clemson University

3. Internet Research Group at Clemson University
Project Goals
Develop web-based metric (s) at the application-level, which we think reflect the Quality user experiences. And for this purpose, we need to analyze network traces for which we need a tool. The traces that we intend to collect will be over different setups – traces collected at a DSL site /Dial-Up site etc and traces collected while running different combinations of the popular browsers over different OSs like IE6.x/WinXP, Netscape 6.x/Linux 8.0 (RedHat), Netscape 6.x/Win
Why? Current metrics being used are based on PING
Remember last Thursday CSDHCP27 aka neo, Problems...
7/18/2019
Internet Research Group at Clemson University

4. Internet Research Group at Clemson University
Description
So, the primary goal we have in mind now is to develop a tool which does the processing of traces and gives us the results in the format we want. For that we have selected RApid Model Parameterization tool aka RAMP. We have chose RAMP because it has the capability to quickly parameterize models from data and it already deals with both the network level as well as user level. RAMP can convert live measurements into simulation models which then be used to generate realistic synthetic traffic.
7/18/2019
Internet Research Group at Clemson University

5. Internet Research Group at Clemson University
RAMP
The input of RAMP is a tcpdump-format file, recorded at a single tap point of the network, that contains only TCP/IP header information. The output of RAMP is a set of CDF (Cumulative Distribution Function) files that model the corresponding traffic. Specifically, the CDF files consist of two types of data. One set of CDF files model user/application level statistics of the traffic, such as user session arrival, page/file size etc.
7/18/2019
Internet Research Group at Clemson University

6. RAMP – the tool we intend to modify/re-engineer
Net work characteristics
Link BW
# of nodes
RTT
User behavior
# of users
User inter-arrival
# of page per user
Page size
Page arrival
# of Object per page
Object size
Object arrival
tcpdump trace
RAMP NS
7/18/2019
Internet Research Group at Clemson University

7. Internet Research Group at Clemson University
RAMP – The Working
(1) filter tcpdump trace for TCP port 80
(2) run http_connect
OUTPUT: summary of http connections
(3) run http_active
OUTPUT: summary of http client request & server response
(4) compute delay based on each SYN/SYN-ACK pair
OUTPUT: CDF that characterizes the averaged RTT
(5) compute and output CDF files that model Web traffic
7/18/2019
Internet Research Group at Clemson University

8. To do <<immediately>>
We intend to develop an ad hoc method to collect data this month (from 2 clients in our lab, 1 dialup (how to do this??), and 1 DSL connected client). This will help us 'prototype' our method and get some data quickly. Phase 2 might be an improved collection method, additional clients/servers and a longer collection period. Then phase 3 is to take the analysis into the outer lab.
7/18/2019
Internet Research Group at Clemson University

9. Internet Research Group at Clemson University
Current Status
Having gone through the RAMP code, we have an understanding of how it works. Now, we are trying to extend RAMP to gather “loss” statistics. Also, we have to gather the tcpdumps over different platforms/browsers and at different sites while collecting PING-based statistics at the same time. We still need to figure a way to do that in a timely fashion, i.e., open the browser and visit a given number of sites <<homepages and some random links on their homepages>>
7/18/2019
Internet Research Group at Clemson University

10. Internet Research Group at Clemson University
RAMP does not deal with “loss”, but we will have to define what we mean by loss. Because, we just have the traces collected at the user-end. So, how do we identify “loss” at the user-end ? Currently my work is headed in the direction of defining a heuristic for “loss” and extend RAMP to feature “loss” statistics.
7/18/2019
Internet Research Group at Clemson University

11. Internet Research Group at Clemson University
Loss Contd...
There are a variety of TCP/IP Protocol stacks over the internet and different OSs (ab)use them in their own way.
A study by Sally Floyd and Jitendra Padhye (On Inferring TCP Behavior), they have gathered statistics over 6000 webservers all over the world and the table shows the usage of each TCP stack.
7/18/2019
Internet Research Group at Clemson University

12. Internet Research Group at Clemson University
Loss Contd...
In Tahoe TCP - Retransmit Timeout before the retransmission of lost packet, but under certain conditions it goes for an unnecessary retransmission.
In NewReno TCP- a Fast Retransmit for the lost packet, no additional Fast Retransmit or Retransmit Timeouts, and no unnecessary retransmissions.
In Reno TCP - a Fast Retransmit for the lost packet, a Retransmit timeout, no unnecessary retransmissions.
7/18/2019
Internet Research Group at Clemson University

13. Questions, Comments and Suggestions...
7/18/2019
Internet Research Group at Clemson University