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. 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 A B C D E F G

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. TOIL Link Selection A B C D E F G 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
100 Nodes Hit Rate
600 Nodes Hit Rate
TOIL becomes stable when reaching enough TTL

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

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