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Low Medium High Very High
Very low Low Medium High
Very High
1
1
0
0
0 25 50 75 100
Battery Level (%)
1 2 3 4 5 6 7 8 9 10 11 12
Number of hops
(a) Fuzzy Sets for Number of Hops.
(b) Fuzzy Sets for Battery Level.
Not adequate Low adequate Adequate Perfect
1
0
0.0 0.25 0.50 0.75 1.0
Node quality
(c) Output Fuzzy Sets.
Fig. 2.
Input Fuzzy sets
Nodes will compare the output of the evaluation for each neighbor node to
perform the parent selection process. Note that fuzzy input and output sets can
be customized depending on the application and on the circumstances of each
particular WSN. For example, in a network which needs real time data, it will
be interesting the use of the end-to-end delay as a decision parameter.
For that example, the fuzzy rule base includes rules such us the following:
if the
Number of hops
is
Low
and the
Battery Level
is
High
then the node
quality is
Adequate
. Here, since we have 4 fuzzy sets for
Battery level
input and
5for
Number of hops
input, we therefore have 20 rules, which are summarised
in Table 1.
6 Combining Synchronized MAC with Intelligent
Routing
The integration of a synchronous MAC protocol and an intelligent routing ap-
proach will make the network more accurate and ecient. Since SA-MAC uses
just the number of hops of a neighbor to be elected as parent, integration with
an ecient parent decision mechanism will be beneficial in terms of network
performance and network load balance, avoiding forwarder-node overload and
improving network lifetime. SA-MAC sends to NORIA the number of hops and
the battery level of the neighbor node, and NORIA's fuzzy-logic-based decision
process provides the node quality value. Then, the node with the best quality
value will be chosen as parent.
6.1 Performance Evaluation
In order to evaluate the performance of the combined proposal, we have imple-
mented both SA-MAC and NORIA in Omnet++ [14] simulator. We are going
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