Difference between revisions of "Private:vikas kumar"
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Work Progress for Vikas. | Work Progress for Vikas. | ||
| + | |||
| + | === Priorities === | ||
| + | * Implement Mao's Algorithm | ||
| + | * Implement our customer only heuristic | ||
| + | * Get familiar with Nitin's peer matching simulation | ||
| + | * Collect real IP addresses from Bit - Torrent networks for evaluation | ||
| + | * Quantify AS dynamics | ||
| + | * Validate valley-free rule | ||
| + | * more efficient peer matching algorithm | ||
| + | * Better shortest path algorithm | ||
== Week 1: May 26 == | == Week 1: May 26 == | ||
| − | * Rewriting the code | + | * Rewriting the code for computing distance matrices between any pair of ASes based on Mao's Algorithm |
| + | |||
| + | |||
| + | == Week 2 : Jun 2 == | ||
| + | * Completed implementation of Mao's Algorithm | ||
| + | * Completed implementation of customer only heuristic and verified that output of both implementations are the same | ||
| + | * Starting peer matching simulation using Nitin's simulator | ||
| − | === | + | == Week 3: Jun 9 == |
| − | + | * Completed AS Dynamics | |
| − | + | * Working on Nitin's Simulator | |
| − | + | === 13th June's Meeting Minutes === | |
| − | + | * We want to compute AS Dynamics for only core ASes ( excluding customer only ASes) | |
| − | + | * Implement the simulator for ISP friendly matching | |
| − | + | * We also want to support the longest IP-prefix matching if receiver and sender are in the same AS | |
| − | + | * In addition to AS hop distance, also use IP hop distance to evaluate our ISP friendly matching. (Consider a couple of ISPs' graph at Rocketfuel project) | |
| − | + | ||
| + | == Week 4 + 5 Jun 15 == | ||
| + | * Completed AS Dynamics for core ASes( excluding customer only ASes ), for only providers ASes and also for others ASes( excluding only provider and only-customer ASes ). | ||
| + | * Implemented simulator for Random Matching, Network Order Matching and ISP Friendly Matching. | ||
| + | * Got the result for different population and different percentage popularity. We used real IPs for simulation of actual bit-torrent users. | ||
| + | === 26th June's Meeting Minutes === | ||
| + | * Fixing the bugs in simulator and ISP-algorithm | ||
| + | * Implementation of AS distance-cum IP prefix Matching Algorithm | ||
| + | * Get the real IP list from CBC | ||
| + | * How can we improve AS-graph given by CAIDA as suggested in Sigmetrics paper. | ||
| − | == Week | + | == Week 6 Jun 30 == |
| + | * Fixed the bugs in the simulator | ||
| + | * Implemented AS-cum-IP-PrefixMatching Algorithm | ||
| + | * Implemented code for checking IP distribution among ASes | ||
| + | * Simulated all the four algorithms on last 12 weeks AS maps by CAIDA and IPs list from nit torrent | ||
Latest revision as of 16:58, 3 July 2008
Work Progress for Vikas.
Priorities
- Implement Mao's Algorithm
- Implement our customer only heuristic
- Get familiar with Nitin's peer matching simulation
- Collect real IP addresses from Bit - Torrent networks for evaluation
- Quantify AS dynamics
- Validate valley-free rule
- more efficient peer matching algorithm
- Better shortest path algorithm
Week 1: May 26
- Rewriting the code for computing distance matrices between any pair of ASes based on Mao's Algorithm
Week 2 : Jun 2
- Completed implementation of Mao's Algorithm
- Completed implementation of customer only heuristic and verified that output of both implementations are the same
- Starting peer matching simulation using Nitin's simulator
Week 3: Jun 9
- Completed AS Dynamics
- Working on Nitin's Simulator
13th June's Meeting Minutes
- We want to compute AS Dynamics for only core ASes ( excluding customer only ASes)
- Implement the simulator for ISP friendly matching
- We also want to support the longest IP-prefix matching if receiver and sender are in the same AS
- In addition to AS hop distance, also use IP hop distance to evaluate our ISP friendly matching. (Consider a couple of ISPs' graph at Rocketfuel project)
Week 4 + 5 Jun 15
- Completed AS Dynamics for core ASes( excluding customer only ASes ), for only providers ASes and also for others ASes( excluding only provider and only-customer ASes ).
- Implemented simulator for Random Matching, Network Order Matching and ISP Friendly Matching.
- Got the result for different population and different percentage popularity. We used real IPs for simulation of actual bit-torrent users.
26th June's Meeting Minutes
- Fixing the bugs in simulator and ISP-algorithm
- Implementation of AS distance-cum IP prefix Matching Algorithm
- Get the real IP list from CBC
- How can we improve AS-graph given by CAIDA as suggested in Sigmetrics paper.
Week 6 Jun 30
- Fixed the bugs in the simulator
- Implemented AS-cum-IP-PrefixMatching Algorithm
- Implemented code for checking IP distribution among ASes
- Simulated all the four algorithms on last 12 weeks AS maps by CAIDA and IPs list from nit torrent
