EEC – 289Q Project Presentation

1. EEC – 289Q Project Presentation Time-Oriented Interlink Locator (TOIL) Wen-Fu Kao, Ying Yu Tai, Howard Che-Hao Chang Instructor: Dr. Chen-Nee Chuah

2. Motivation and Limitation • Peer-to-Peer resource sharing among existing network infrastructure is desired • Request node doesn’t know where the target node is • Caused huge amount of network loading for searching the target

3. A B D C F G E Random Walk • Qin Lv et al. (ACM SIGMETRICS 2002) claims it has the best performance • Choose successor randomly • Every walker chooses only one link • Stops when TTL=0

4. TOIL Algorithm • Use RTT as the hint for selecting the nodes • Only search the top three nodes • Distributed, Breadth first • Stops when TTL=0

5. A B D C F G E TOIL Link Selection A B D C F G E

6. TOIL Searching Tree A B A D B C C A F E G A G C F C E C G

7. Experimental Method • Simulation for 100 nodes and 600 nodes graph • Generated by the GT-ITM • Matlab for simulating the k random walker • A C program for simulating TOIL • Exhaustive searches all possible path to see the best and the worst case

8. Network Topology 100 Node Graph 600 Node Graph

9. Performance Comparison Ⅰ • TOIL becomes stable when reaching enough TTL 100 Nodes Hit Rate 600 Nodes Hit Rate

10. Performance Comparison Ⅱ • Exponential growth vs. Linear growth • TOIL is a ternary tree 100 Nodes Traffic Load 600 Nodes Traffic Load

11. Performance Comparison Ⅲ • Hit Time Ratio (HTR)=T2/T1 • T1=E[hit time|walker finds the shortest path to the target for a given TTL] • T2=E[hit time|TOIL finds the shortest path to the target for a given TTL] 600 Nodes Hit Time Ratio

12. Conclusion and Future Work • TOIL has the potential; needs further improvement • The performance of TOIL depends on the network topology • Possible modification of TOIL • Binary vs. Ternary Tree • Replace one of the nodes into a randomly selected one from physically connected neighbors • Choose only one node instead of k nodes after certain TTL