Comparison of Tarry’s Algorithm and Awerbuch’s Algorithm CS 6/73201 Advanced Operating System...
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Transcript of Comparison of Tarry’s Algorithm and Awerbuch’s Algorithm CS 6/73201 Advanced Operating System...
Comparison of Tarry’s Algorithm and Awerbuch’s Algorithm
CS 6/73201 Advanced Operating System
Presentation by: Sanjitkumar Patel
Outline
• Goal• Introduction• Experiments Setup• Results and Analysis• Conclusion and Future Work
Goal
• To compare Tarry’s and Awerbuch’s Algorithm.• Theoretically, Time complexity of Awerbuch’s algorithm
is better than Tarry’s algorithm Tarry ( 2 x Number of edges) Awerbuch ( 4 x Number of nodes) - 2• Theoretically, Message complexity of Tarry’s algorithm
is better than Awerbuch’s algorithm Tarry ( 2 x Number of edges) Awerbuch ( 4 x Number of edges)• How they perform in real world?
Introduction
• Tarry’s Algorithm:– Initiator forwards the token to one of its neighbors, each
neighbor forwards the token to all other nodes and when done returns the token.
• Awerbuch’s Algorithm:– A node holding the token for the first time informs all
neighbors except its father.– Prevents token forwarding over frond edges -each process
knows which neighbors were visited before it forwards the token.
Experiments Setup
• Graphs are usually random for these experiments• We need to measure time and message complexities while
varying size and density of network• Number of nodes are entered from terminal.• Based on the input provided by user, random graph is
generated.• E.g. user entered number of nodes = 4 then, 4x4 matrix is
generated.• Matrix is initialized by randomly generating 0 and 1. • 1 means there is an edge between nodes and 0 means there
is no edge between nodes
Experiments Setup
• Suppose randomly generated matrix is as follows: 1 2 3 4
1 0
1 0 1
2 1 0 1 1
3 0 1 0 1
4 1 1 1 0
Experiments Setup
• Suppose randomly generated graph is as follows: 1 2 4 3
1 2 3 4
1 0
1 0 1
2 1 0 1 1
3 0 1 0 1
4 1 1 1 0
Experiments Setup
• Data are collected by varying number of nodes and connection probability.
• Connection probability means if there is an edge between nodes or not.
• Since 2 nodes don’t help, nodes taken into consideration for experiments were from 3 to 50.
• Significant difference was noticed while nodes count was reaching to 50.
• Connection probability considered was 25%, 50% and 75%.
Results and Analysis
• Comparison of time complexity at connection probability of 25%
Time Complex.
Number of nodes
4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 500
100
200
300
400
500
600
700
TarryAwerbuch
Results and Analysis
• Comparison of time complexity at connection probability of 50%
Time complex.
Number of nodes
4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 500
200
400
600
800
1000
1200
1400
TarryAwerbuch
Results and Analysis
• Comparison of time complexity at connection probability of 75%
Time Complex.
Number of nodes
4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 500
200
400
600
800
1000
1200
1400
1600
1800
2000
TarryAwerbuch
Results and Analysis
• Comparison of message complexity at connection probability of 25%
Message Complex
Number of nodes
4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 500
200
400
600
800
1000
1200
1400
TarryAwerbuch
Results and Analysis
• Comparison of message complexity at connection probability of 50%
Message Complex
Number of nodes4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50
0
500
1000
1500
2000
2500
3000
TarryAwerbuch
Results and Analysis
• Comparison of message complexity at connection probability of 75%
Message Complex
Number of nodes4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50
0
500
1000
1500
2000
2500
3000
3500
4000
TarryAwerbuch
Conclusion
• Awerbuch’s algorithm is more effective than Tarry’s algorithm in time complexity
• Tarry’s algorithm is more effective than Awerbuch’s algorithm in message complexity
• Both time and message complexity of Tarry’s algorithm, and message complexity of Awerbuch’s algorithm are sensitive to the density of graph, but time complexity of Awerbuch’s algorithm is not sensitive to the density of graph
Future Work
• Experiment on larger N• Experiment on real distributed systems
Thank You