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The Strength of Vicinity
Annexation in Opportunistic
        Networking
   Tiphaine Phe-Neau*, Marcelo Dias de Amorim*,
                and Vania Conan+

            * UPMC Sorbonne Universités, France
         + Thales Communications & Security, France



The Fifth IEEE International Workshop on Network Science for
   Communication Networks (NetSciCom 2013), Torino, Italy

                    April, 19th 2013                           	
  
                                                               	
  
PEOPLE       NETWORK
         =
                       	
  
                       	
  
Disruption-Tolerant
         Networks (DTN)	
  


	
  




	
  

         t = t1   t = t2   t = t3    	
  
                                    3	
  
Now	
  

t0                             t1
                                            F
             F                                      G
     B                   G
                                    B
A                              A                D


         C       D                      C
                     E                              E




                                                        4	
  
K-vicinity	
  
K in N*


               A



          1-vicinity (k = 1)
                               5	
  
K-vicinity	
  
K in N*


                 A



          2-vicinity (k = 2)
          	
                   6	
  
Now with The Vicinity	
  

t0                             t1
                                             F
               F                                     G
     B                     G
                                     B
A                              A                 D


           C       D                     C
                       E                             E




               No                     Infinite
         Waiting Delay              Waiting Delay
                                                         7	
  
Infocom05 (41)   Rollernet (61)




                      RandomTrip
                         (20)




  Unimi (48)       Community (50)   8	
  
Which K-Vicinity?	
  
              Infocom05
         Neighbor distribution
                                 k=1

                                 k=2
 0,7    1,5         3            k=3   1,4
                                 k=4

                                 k=5
1,5
       2,3                       k=6

                                 k=7
                                       3
                  4,4            k=8




  No meaningful evolution
       beyond k = 4.                         9	
  
Average waiting Times	
  
                   Average WAITing times (seconds)
                                                               18300
         contact                                      18232s
500      κ=2
         κ=3
         κ=4                    40%                            18200
         κ=5
400
         κ=6
                                                               18100
300                  80%                              1%
                                                               18000
200
                                                               17900
100       57%                             40%         17792s

                                                               17800
  0
      Random Trip Community Infocom05 Rollernet      Unimi*

             Higher K brings
          better waiting delays.                                       10	
  
Message Overhead: Regular	
  
                                                    Infocom05
                    100000


                    10000
    No (messages)




                                                     κ=3
                     1000                                    κ=4
                                           κ=2
                      100
                                                                    κ = 5+
                                 Contact
                       10


                        1
                             0    5000 10000 15000 20000 25000 30000 35000
                                                 Time t (seconds)


 Overhead increase with K until k = 4.
                                                                             11	
  
Message Overhead: On
      Demand	
  
                                                Infocom05


                                      κ=2
                                                κ=3
                   1000
   N0 (messages)




                    100
                                                                κ=5+
                                  contact

                    10                          κ=4



                      1
                          10000      15000    20000    25000    30000   35000
                                             Time t (seconds)

Sensing the 3+-vicinity is cheaper
      than the 2-vicinity.                                                      12	
  
Take THIS Away !	
  
•  Sensing direct contacts in DTN is
   not enough.

•  k-vicinity reduces waiting delays.

•  Network knowledge is costly so
 limit it to k=4 !
                                        13	
  
www.phe-neau.com
                	
  

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The Strength of Vicinity Annexation in Opportunistic Networking

  • 1. The Strength of Vicinity Annexation in Opportunistic Networking Tiphaine Phe-Neau*, Marcelo Dias de Amorim*, and Vania Conan+ * UPMC Sorbonne Universités, France + Thales Communications & Security, France The Fifth IEEE International Workshop on Network Science for Communication Networks (NetSciCom 2013), Torino, Italy April, 19th 2013    
  • 2. PEOPLE NETWORK =    
  • 3. Disruption-Tolerant Networks (DTN)       t = t1 t = t2 t = t3   3  
  • 4. Now   t0 t1 F F G B G B A A D C D C E E 4  
  • 5. K-vicinity   K in N* A 1-vicinity (k = 1) 5  
  • 6. K-vicinity   K in N* A 2-vicinity (k = 2)   6  
  • 7. Now with The Vicinity   t0 t1 F F G B G B A A D C D C E E No Infinite Waiting Delay Waiting Delay 7  
  • 8. Infocom05 (41) Rollernet (61) RandomTrip (20) Unimi (48) Community (50) 8  
  • 9. Which K-Vicinity?   Infocom05 Neighbor distribution k=1 k=2 0,7 1,5 3 k=3 1,4 k=4 k=5 1,5 2,3 k=6 k=7 3 4,4 k=8 No meaningful evolution beyond k = 4. 9  
  • 10. Average waiting Times   Average WAITing times (seconds) 18300 contact 18232s 500 κ=2 κ=3 κ=4 40% 18200 κ=5 400 κ=6 18100 300 80% 1% 18000 200 17900 100 57% 40% 17792s 17800 0 Random Trip Community Infocom05 Rollernet Unimi* Higher K brings better waiting delays. 10  
  • 11. Message Overhead: Regular   Infocom05 100000 10000 No (messages) κ=3 1000 κ=4 κ=2 100 κ = 5+ Contact 10 1 0 5000 10000 15000 20000 25000 30000 35000 Time t (seconds) Overhead increase with K until k = 4. 11  
  • 12. Message Overhead: On Demand   Infocom05 κ=2 κ=3 1000 N0 (messages) 100 κ=5+ contact 10 κ=4 1 10000 15000 20000 25000 30000 35000 Time t (seconds) Sensing the 3+-vicinity is cheaper than the 2-vicinity. 12  
  • 13. Take THIS Away !   •  Sensing direct contacts in DTN is not enough. •  k-vicinity reduces waiting delays. •  Network knowledge is costly so limit it to k=4 ! 13