Today, we will play around a bit with the ONE simulator, specifically with the Epidemic routing protocol. We will simulate two scenarios and look at the results. Detailed analysis of the results are left out for the time being.
Parameters
Here are few common parameters for the simulations.
- Group.movementModel = RandomWaypoint
- Group.msgTtl = 300 (5 hours)
- MovementModel.worldSize = 450, 340
- Scenario.endTime = 14400 (4 hours)
Stats are collected from MessageStatsReport from a single run.
Scenario #1
In the first scenario, we vary the density of the nodes for a single speed range. In particular, we consider:
- Epidemic routing with (10, 50, 100, 150, 200, 250, 300) nodes
- Speed: 0.5, 1.5
- The number of nodes keeping the simulation geography (usually rectangular) size constant
- The geography size keeping the number of nodes constant
- Both the number of nodes and the size of the geography
At first we look at the average delivery latency (in seconds) of the messages as a function of the number of nodes. As it can be observed from the data and the adjoining plot, the latency decreases with the increasing node density. This is due to the reason that with increased number of nodes, a message gets more chance to be delivered and that too quickly. Indeed, the latter set of data and the corresponding plot indicates that the delivery ratio increases with the node density.
Average Latency
10 1032.6966
50 887.4016
100 773.9650
150 653.5246
200 610.9147
250 617.7339
300 573.6033
Delivery Probability
10 0.1813
50 0.2587
100 0.2912
150 0.2485
200 0.2627
250 0.2525
300 0.2464
Scenario #2
In the second scenario, we consider a constant number of nodes, but vary their speeds in different ranges, as enumerated below:
In the second scenario, we consider a constant number of nodes, but vary their speeds in different ranges, as enumerated below:
- Speeds: [0.5,1.5; 1.5,2.5; 2.5,3.5; 3.5,4.5; 4.5,5.5; 5.5,6.5; 6.5,7.5]
- # of nodes: 100
Avg latency
1 773.9650
2 440.8467
3 453.5573
4 582.5417
5 678.5824
6 899.6848
7 985.1136
Delivery probability
1 0.2912
2 0.3055
3 0.2668
4 0.2444
5 0.1853
6 0.1874
7 0.1792
The corresponding results -- average delivery latency and delivery probability -- are shown above.
What can you infer from these results?
Revision history:
12 Feb 2014: Expanded the discussion
I'm a beginner and may l ask how to draw those pics such as avg Latency and Delivery probability?
ReplyDeleteYou can use GnuPlot to plot your data.
DeleteI want more information about The one. Can you give me ? Because my final year project is going on with this.
ReplyDelete