We plot the optimal values of lifetime when
mpr is varied from 0 to 2580 to analyze the e?®ect of periodic messages on
the lifetime of ExScal in Figure 6 when hierarchical sensing and LPL both are
used. We notice that if there were no periodic messages, ExScal??™s life increases
to 1157.1 hours (or 48.2 days). This represents an improvement of 31.67%.
Fig. 6. Optimal ExScal network lifetime in the low power listening mode and hierarchical
sensing when the number of periodic control messages (mpr) is varied from
0 to 2580 messages per hour.
4.7 E?®ect of In-Network Data Aggregation on the Lifetime
In this section, we analyze the e?®ect of in-network data aggregation on the
lifetime of a WSN. The lifetime of a WSN with data aggregation is still given
by (5) and (6), but with new values for me and mpp. The amount of data
aggregation that can be performed in a WSN depends on the application
tra?±c generated and on the topology as well as the routing protocol used.
We can perform the following data aggregation in ExScal, assuming the most
optimistic scenario:
279 Chapter 11 Maximizing the Lifetime of an Always-On WSN Application
0 500 1000 1500 2000 2500 3000
400
500
600
700
800
900
1000
1100
1200
Number of Periodic Control Messages per hour m
pr
??’??’>
XSM Lifetime l
hr
(in hours) ??’??’>
tlpl
slp
=0.4 s
tlpl
slp
=0.2 s
tlpl
slp
=0.1 s
Santosh Kumar, Anish Arora, and Ten H. Lai
1.
Pages:
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455