We can combine the detection message for all three sensors at an XSM
into one message. This will result in reducing me by a factor of 1/3 to 17.
2. We can perform aggregation of detection messages flowing upward in a
routing tree. Assuming that both intruder types are equally likely to occur,
an average of (30+10)/2 = 20 XSMs detect an event (from Table 3).
Since the routing load is distributed on 8 XSMs, each XSM forwards the
detection messages from at most three other XSMs, all of whose data can
be combined into one packet. Since each XSM generates two messages
for every event, separated in time, an XSM close to the base station will
need to forward two packets per event. Assuming a retransmission factor
of 1.43, and six events per hour, each XSM close to the base station will
forward 18 messages. Therefore, mpp = 18.
Substituting me = 17, mpp = 18, and isensor = 0.292 mA in (6), we obtain
a graph of ?„“hr, shown in Figure 7, for the lifetime of ExScal, if hierarchical
sensing and LPL mode continue to be used. The maximum life achievable is
now 954.6 hours (or 39.78 days). This represents an increase of 8.91% in the
lifetime of ExScal over that achieved by using only the hierarchical sensing
and LPL mode. In practice, it may not be feasible to achieve this extent of
data aggregation. So, the increase in lifetime that we can achieve using data
aggregation will be at most 8.91%.
Fig. 7. ExScal network lifetime in the low power listening mode with PIR as the
wakeup sensor and in-network data aggregation, as a function of radio sleep period,
tlpl
slp.
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