ReadMe					      |
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*************P2M2Sim: A Privacy Preserving Mobility Monitoring Simulator**************|
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Contributors:S.Venkatesan, Richard Gobel, Yuvaraj Rajendra, Nachiket Tapas, Om Prakash|
Vyas, Sandeep Kumar Shukla, Ranjana Vyas					      |	
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About										      |
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This tool simulates the network graph based on the user parameters and enable the     |
individuals to move randomly along with the fake individuals. The privacy metric is   |
computed according to the monitoring model.					      |
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0.Requirement									      |
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The tool is written using the Golang and the Linux system should have golang installed| 
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1.Files:									      |
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movement_fake.go      ----> Includes the code for node activities and the declaration |
                            of various parameters				      |
2. Execution									      |
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To run the tool, do the following						      |
a) Move to the location in the terminal where the file is stored 		      |
b) go run movement_fake.go							      |
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3. Output Interpretation [Need more attention for interpretation]		      |
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a) It shows the introduce of nodes/users and stop or kill of nodes/users	      |
b) Displays the users and locations statistics 					      |
c) At the end, diplays the Users at different locations in various rounds. Also other |
   informations.								      |
d) The output finally contains Trajectory Leakage of User with and without dummy.     |
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4. Modification Required							      |
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a) Set the constants in movement_fake.go as per your requirement.		      |
b) No other change required							      |
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5. Files created while execution						      |
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Produces the following CSV files						      |
   I.   d-destinationprivacy.csv  - Results of privacy computation of a user  	      |
                                    based on destination metric with dummy.	      |
   II.  d-sourcprivacy.csv        - Results of privacy computation of a user 	      |
                                    based on source metric with dummy.		      |
   III. location.csv              - Locations with users with anonymous		      |
                                    (that is 1) identity.			      |
   IV.  location-real.csv         - Locations with users with real identity.	      |
   V.   route.csv                 - Individuals at different locations 		      |
                                    in different rounds.                              |      
   VI.  destinationprivacy.csv    - Results of privacy computation of a user  	      |	
                                    based on destination metric without dummy.        |
   VII. locationfake.csv          - Locations with users including dummy 	      |
                                    with anonymous (that is 1) identity. 	      |
   VIII.sourcprivacy.csv          - Results of privacy computation of a user 	      |
                                    based on source metric without dummy.	      |
   IX.  d-presentprivacy.csv      - Results of privacy computation of a user  	      |
                                    based on present location metric with dummy.      |
   X.   locationfake-real.csv     - Locations with users including dummy              |
                                    with real identity.				      |
   XI.  presentprivacy.csv        - Results of privacy computation of a user          |
                                    based on present location metric without dummy.   |
   XII. weight.csv                - The routes and number of users with dummy 	      |
                                    travelled. For example [1,2,4], between 1 and 2   |
				    4 users have travelled.			      |	
   XIII. dummylessweight.csv      - The routes and number of users without dummy      |
				    travelled.					      |
   XIV. routetime.csv		  - The time (second) of the user movement	      |
				    from the start of the simulation.		      |
   XV. labelsourceprivacy.csv    - Results of privacy computation of a user based     |
                                    on source metric with source labelling.           |
   XVI. dlabelsourceprivacy.csv    - Reults of privacy computation of a user based    |
                                    on source metric with dummy and source labelling. |
   XVII. pdsourceprivacy.csv       - Reults of privacy computation of a user based    |
                                    on source metric with probabilistic contribution, |
				    dummy and source labelling. 		      |
6. Contact									      |
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venkat@iiita.ac.in								      |
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