Networking Problems in Cloud Computing Projects

2 Kickass: Implementation PROJECT 1

Background  Kickass is a transport layer congestion control mechanism.  Uses IP fragmentation to enable communication between routers and end points.  Designed to operate well alongside TCP.  Currently only a proof-of-concept implementation exists.

Project Goals  Develop an improved end point implementation of Kickass. – C, Linux kernel programming  Provide more reliable and stable implementation of the system.  Explore practical improvements that could be made to the design.

Deliverables  Compiling and working with existing version (4/21)  Full outline of implementation plan in the kernel (5/12)  New receiver operating on network testbed (End of quarter)

6 Kickass: Wireless AP PROJECT 2

Background  Since the last mile is a common bottle-neck its a reasonable to place a Kickass router as the home router.  Implementing Kickass in a manner that would allow easy install would greatly improve usability.  DD-WRT offers a convenient Linux-Based method of controlling routers.

Project Goals  Implement the Kickass router protocol for DD-WRT open source firmware. – C  Explore the challenges of operating Kickass in a wireless environment. – Limited resources, limited computing power

Deliverables  Compile current version of DD-WRT and flash to router (4/21)  Initial module design for constraints of the router (5/12)  Working prototype of Kickass DD-WRT kernel module (End of quarter)

10 Kickass: Benchmarks PROJECT 3

Background  Current benchmarks are manual and ad-hoc, requiring significant manual interaction.  Improved benchmarks would allow improved further study. – Reproducibility – Variety (i.e. could explore more designs) – Ease-of-use

Project Goals  Develop automated benchmark suite to test network performance in different scenarios – C, Python  Explore scenarios that would be worth testing (ie explore the strengths and weaknesses of the protocol).  Generate various traffic models and evaluate performance.

Deliverables  Develop basic outline of benchmarking model (4/21)  Develop extensible framework for implementing benchmarking and performance comparisons (5/12)  Final system including a handful of working benchmarks (End of Term)

14 Synthoid: Mobile PROJECT 4

Background  Synthoid is a privacy tool which performs automated browsing in order to pollute user ad profiles  Currently only implemented in desktop operating systems  Would be extremely valuable in mobile (Android in particular)

Project Goals  Improve on previous proof of concept.  Develop solutions to remaining challenges in the mobile environment. – Power usage – User experience – Data size limitations

Deliverables  A tool to perform arbitrary programatic browsing on Android (4/21)  Add topic selection and complete browsing patterns (5/12)  Working prototype of mobile system (End of Term)

18 Synthoid: Search PROJECT 5

Background  Search engines employ high levels of search personalization based on user history.  The Synthoid model of generating false history stands to be effective in such a scenario.  Search offers fresh challenges (feedback, generating meaningful queries).

Project Goals  Develop a system which allows measurement of user profile without explicit information from the search provider.  Allow users to audit the profiling done by the search engine. – Improve existing obfuscation techniques.  Understand what information is being used about a user.

Deliverables  Mechanism to measure differences in search results (4/21)  Profile Construction scheme to build the observed profile (5/12)  Prototype of the working system (end of term)

CDN Performance Evaluation PROJECT 6

Background  Modern web services use CDN for traffic delivery  Performance from different CDN providers is not transparent  How can we evaluate the performance of CDNs?  Different web services?  Different locations?  Different content type?  HTTP vs. HTTPS?

Project Goals  Focus on HTTP(S) requests  CDN performance evaluation over different parameters  Locations  Edge server selection  Unstable environment (high package lost)

Deliverables  A tool to record the CDN provider performance  Input: HTTP(S) request log  Output: CDN provider name, IP, responding time, and etc.  Analysis of CDN performance  Different locations, time, edge server, etc;  Redundant requests to multiple servers;

Milestones  Mid-Term:  Collecting test data  Get testing environment ready PlanetLab  End-Term:  Analysis results

Chromium: Web Page Performance PROJECT 7

Background  Chromium (Chrome): open source browser  Web pages are getting more complex  There might be hundreds of requests triggered by a single page;  Protocols: DNS, HTTPS, SPDY, WebSockets…  How to optimize the web page performance from different scenarios?  From laptop/mobile devices?  From cable/mobile Internet?

Project Goals  Focus on web pages  Build the tools for browsers  Log the DNS, HTTP(S) performance when loading a web page

Deliverables  A Chrome plugin to log web page performance: timing details  WProf  Runnable browser for Linux/Android  Web page performance analysis results  Top websites  Random websites

Milestones  Compiled Chrome for Linux (4/21)  Compiled Chrome for Linux (5/12)  End-Term:  Test data generation  Analysis results

Mobile TCP Evaluation PROJECT 8

Background  Accessing mobile Internet (3G/4G) is getting more popular  However, TCP is not particular designed for mobile environment:  High lost rate  Unstable throughput  Broken connections

Project Goals  Focus on TCP performance under mobile environment  Build the tools for TCP analysis  Ruby/Python for log analysis  Analysis with simulation and real world test  What is the main reason for slow mobile performance?  Is there an easy way to fix the problem?

Deliverables  Tools to analysis TCP performance  Scripts for tcpdump  Runnable scripts for linux/andriod  Ruby/Python/Java  Selenium for browser automation

Milestones  Scripts for Linux (4/21)  Scripts for Android (5/12)  End-Term:  Test data generation  Analysis results