chosen from a normal distribution with a mean of the respective old value. Speed values are constrained to a certain interval. If a newly chosen speed value is outside this interval, it is reset to the closed value inside the interval.
The concrete settings we used for the different mobility models during simula- tion are given in Section 7.8.
7.6
Simulation Results: Dissemination Effectiveness
This section presents several simulation results for calender week 45, 48, and 50 considering 10 meters and 100 meters as a user’s device communication range. We refer to a 10 meter communication range as Bluetooth scenario and to a 100 meter communication range as a WiFi scenario. For each week, the simulation was run 100 times (the figures display the averaged values) and with three different setups. In setup one, there are no Information Sprinklers to help with time shifted data dissemination (see Section 3.4.2). In setup two there are Information Sprinklers in place, and finally in setup tree, all Information Sprinklers are connected by a backbone network (see page 36). In this last case, as soon as an information item is passed from a user to an Information Sprinkler, this information item is available at all other Information Sprinklers at all other locations. For all runs, the user behavior was set up as follows. One user, chosen randomly, owns an information at startup. All other user are interested in the information and all users acted generously, i.e., they always pass the information on to others.Figure 7.4 shows the simulation results for calender week 45, Bluetooth scenario. Figure 7.4(a) shows the amount of overall fulfilled wishes observed at simulation time (broken down to hours). Without any Information Sprinklers in place, at the end of a simulated week, on average 53.97% of wishes are fulfilled. Deploying an Information Sprinklers at each location, this value increases to 65.49%. Finally, connecting all deployed Information Sprinklers to a backbone network increases the amount of overall fulfilled wishes to 85.77%.
Looking at the number of hops, i.e., opportunistic network nodes, the informa- tion travels within one week of simulation (depict in Figure 7.4(b)), most users are reached with either 3 or 4 hops. The maximum hop count observed is 12. Deploying Information Sprinklers most users are reached with 4 hops. Starting from 3 hops, the number of hops increases slightly, extending the maximum hop count observed to 13. Different from this, connecting the Information Sprinklers to a backbone network significantly increases the number of users reached with 3,4, and 5 hops and reduces the maximal observed hop count to 9. The reason for a jump in reached users from 2 hops to 3 hops is as follows: User Aipasses the information at a loca-
tion locl to an Information Sprinkler ISr(counts as 1 hop), next the information is
synced to all other Information Sprinklers in the network (counts as 1 hop). Finally, at any other location locmthe information is passed from an Information Sprinkler
ISsto another user Aj(counts as 1 hop). Thus, Information Sprinklers connected to
0 % 10 % 20 % 30 % 40 % 50 % 60 % 70 % 80 % 90 % 100 % 0 12 24 36 48 60 72 84 96 108 120 132 144 156 168
Percentage: Wishes fulfilled
Hour
IS off IS on IS on & connected
(a) Hour/fulfilled wishes ratio
0 5 10 15 20 25 30 35 40 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 # user reached # hop IS off IS on IS on & connected
(b) Hops/reached users ratio
7.6 SIMULATION RESULTS: DISSEMINATION EFFECTIVENESS 121 0 % 10 % 20 % 30 % 40 % 50 % 60 % 70 % 80 % 90 % 100 % 0 12 24 36 48 60 72 84 96 108 120 132 144 156 168
Percentage: Wishes fulfilled
Hour
IS off IS on IS on & connected
(a) Hour/fulfilled wishes ratio
0 5 10 15 20 25 30 35 40 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 # user reached # hop IS off IS on IS on & connected
(b) Hops/reached users ratio
that is provided by a deployed Information Sprinkler and second, the maximum number of hops observed is reduced.
Considering a device communication range of 100 meters, i.e., a WiFi scenario, the amount of fulfilled wishes observed is quite different. Figure 7.5(a) depicts that already without any Information Sprinkler in place, 94.30% of the users’ information wishes are fulfilled after one week. Next, there is not much effect from deploying Information Sprinklers at each location. At the end of the week, 95.62% of wishes are fulfilled. Connecting all Information Sprinklers increases the amount of fulfilled wishes to 99.58%. Looking at Figure 7.5(b), which depicts the number of hops it take for an information to reach users, the behavior resembles the observed results in the Bluetooth scenario, although the absolute numbers are higher.
Figures 7.7 and 7.9 present the simulation results for calender weeks 48 and 50, respectively. Although the number of logged locations is close to twice as much in calender week 48 (8056) and less than half as much in calender week 50 (1685), the results are comparable to calender week 45. For the Bluetooth scenario, both weeks see a significant increase in the overall number of fulfilled wishes when deploying and connecting Information Sprinklers and an about 10% increase by just putting Information Sprinklers in place. For the WiFi scenario, deploying Information Sprinklers (connected or not) does not have much effect on the overall information dissemination performance.