Internet Mapping: from Art to Science May 25, 2009

(i) Three most important things

1. We critically depend on the Internet for our professional, personal, and political lives but we know little about what keeps the Internet stable as the Internet becomes continuously challenging to research and analyze. The paper presents the design of an infrastructure and operating system platform known as Ark that supports large-scale active measurements studies of the global Internet for Internet topology mapping.

2.  Easy development and rapid prototyping are important factors in how they promote discovery. A researcher can explore more risky ideas which could have higher returns, by lowering the cost needed in time and effort to implement a measurement idea. Ark supports rapid prototyping by promoting software development at a high-level of abstraction using dynamic scripting languages and pre-built API’s and services.

3. It should be easy for researchers to use and to build upon the work of others at the granularity of services. Ark supports measurement services by providing a tuple space which acts as the unified mechanism for transport and messaging. A user can easily deploy a measurement service by writing a program that interprets tuples as commands, performs some measurement, and returns the result as a tuple.

(ii) Most glaring problem

The most glaring problem would be that paper doesn’t discuss much how Ark has helped study Internet topology. The paper mentions a couple researches that have implemented Ark but doesn’t really provide any actual results and conclusions.

(iii) Future Research Directions

Future research directions for this work would be to have Ark implemented by other research communities so that more data can be collected on Internet topology and expand Ark to perform more IPv6 topology measurements.

Internet Mapping: from Art to Science May 25, 2009

(i) The three most important things the paper says:

1) The building of their system based on a concept of easy development and rapid prototyping are important factors.  Claffy et al points out that this not only allows an increase of productivity, but also how they promote increased discovery.  I agree that this is the case because they allow researchers to focus on developing new strategies for research instead of tons of time on development.  Because if development of a program for research may take a long time, they may limit the types of experiments that they complete.  However if the facilities to perform this research is easy, then they may be encourage to perform more types of analysis.

2) The paper indicated that “In a few cases when we cannot determine a Provider-Customer relationship for a set of ASes accessing the same  router, we assign this router to the AS with the smallest outdegree.”  Basically in this case they are making assumptions using a best effort educated guess.  What I think its important is this type of approach, in which they are actively looking for ways to continue their research and not be bounded by external factors.   This is unlike the Claffy paper “Ten Things Lawyers Should Know About the Internet ”, which didn’t really address the limitations that they complained about.  Furthermore, they did mentioned that moving forward they will fill in these assumptions with accurate data as they get them.  This approach that they promote is very important to this study since so many bits of information are blank.

3) They are actively looking to obtain information about IPv6 as it is being deployed.  I believe this is an important fact, since they are in the unique position to capture information about a technology at its early adoption phase.  This type of “infrastructure data” is invaluable for future research as indicated in “Ten Things Lawyers Should Know About the Internet”. .   In addition, they have already indicated a good use of this data to help with dealing with IPv4 exhaustion.  This further reinforces the point that this is an important topic.

(ii) The most glaring problem with the paper:

The biggest problem with the paper is the fact that they didn’t talk about the errors in the ARK system.  No system is perfect and many assumptions were made in the building of ARK and in the measurement it collected (e.g. AS information in traces).  However, there was no mention about potential errors in the calculation of the topology, only assumptions.  Also, when it presented the assumptions that were made, Claffy et al didn’t address the implications of these underlying assumptions.  The reader is left to speculate the outcome.

(iii) The future research directions of the work:

The future research of the work would work to resolve inconsistency or gaps in their data by building business relationships.  Perhaps there is some investigation into the legal options in which they can partner with an ISP.  Ultimately this system seems like they are from the “outside looking in”.  However if we want something accurate and precise, we will need to have data on the inside.

Internet Mapping: from Art to Science May 25, 2009

1. Distributed and scalable measurement architecture

The paper suggests a measurement/monitoring architecture that allows different groups of users dispersed over geographically separated locations to make topology measurements. It also provides a common, shared database that is updated with all measurements made. This way, not only is support for a large user base provided, but also, diverse and time skewed measurements of the Internet topology is  obtained. It makes use of tuple-space co-ordination model to achieve this shared memory structure. Decentralized measurement also introduces randomness into measurements which more accurately captures topology data.

2. Incremental development

The architecture makes it feasible for the users to build upon the work and development done by others. It shields the users from underlying complexities and allows them to use a scripting language to develop their codes for the measurement.

3. Interpreting and processing gathered information

The paper suggests some interesting methods for deriving topology information from the raw data gathered. For eg. they mention a technique to obtain the IP addresses of hosts connected to a router from data obtained by measuring paths to a list of IP addresses covering all /24 prefixes in an address space.

Short-comings

A shared memory to update measurements and a common code to which any user can make additions mean a faulty or malicious code and compromise the entire structure. However, this is a trade-off one needs to make with any form of open-ware. In addition, there is no mention of accommodating for dynamic and changing network topologies while allowing different users to update the database with measurements made at different instances of time. The method of alias resolution mentioned by them seems to only support end routers with hosts directly connected to the router of concern.

Future Work

The idea is still young and can grow in multiple dimensions. The API can be developed further to provide for greater ease 0f use and deployment. Increased functionality can be added to their data interpretation tools to glean greater insight into the network topology from the raw data gathered by the system. Attempt can be made to increase the variety of data gathered by the system as well.