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

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

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

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

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

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

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

Network Topology 100 Node Graph 600 Node Graph

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

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

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

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