Page 8 - 2023-Vol19-Issue2

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If ( ),
Vary attractiveness (RE) with distance r (SH) via move
firefly I towards J;
(Represent distance from node to sink (SH) and (RE) and
find best f(n) value)
Evaluate new solution and update light intensity; (update
energy exhaustion for each node)
End If
End for J
End for I
Rank fireflies and find the current best; (find the optimum
path)
End while
Post-processing the results and visualization (use the
optimum path)
End
The following equation states the update formula [16].
Xit+1 = Xit + ß0e-? ri2j (X t - Xit ) + at eit (2)
j reach to network partition quickly. The mention of Dijkstra
Where; Xi is the initial population of fireflies, r is distance, ? ing algorithm. Lifetime is evaluated by alive nodes no. out of
is the light absorption coefficient, ß is the attractiveness, a
is a randomization parameter, is a vector of random numbers
drawn from a Gaussian distribution or uniform distribution.
IV. EXPERIMENTAL SETTING
Simulation is achieved by using MATLAB. A 100mx100m
topological zone area is used in the simulation. A 100 ran-
domly scattered nodes for the topological zone area. The topo-
logical area has one fixed sink with position of (90mx90m).
Each node work with max transmission distance amounting
to 30m. Each node starts with initial energy amounting to
0.5J. The used value of packet length is amounting to 200-bit.
The hop count limit has the value of 15 hops. The values of
w1 and w2 are 0.2 and 2, respectively. The first order radio
paradigm submitted via [17] is used for simulation as follows:
ET X (pktlength) = Eelec * pktlength + Eamp * pktlength * d2 (3)
ERX (pktlength) = Eelec * pktlength (4)
Table I explain symbols for this paradigm.
To evaluate this routing method packet delivery ratio (PDR)
has been involved. Routing protocol is good with PDR is
more than 0.96 percent. The PDR can be calculated using the
following equation [13],[14].
PDR = No. o f Success f ully delivered Packets to Sink (5)
Total No. o f Packets Sent
Leabi
TABLE I.
REPRESENTATION OF PARADIGM SYMBOL
SYMBOL REPRESENTATION
ET X , ERX Power depletion for broadcasting data,
send and receive
pktlength No. bits for either packet
Eelec Per bit power depletion, set to 50 nJ/ bit
Eamp Per bit per meter square power depletion,
set to 100pJ/bit/m2
V. RESULTS
The simulation is achieved for the mentioned topological zone
area. The result of the submitted routing is compared by Di-
jkstra method, Fuzzy routing method [13], and ACO routing
method [14]. Dijkstra routing method is well known tech-
nique. It involves determining shortest path from node to sink.
sometimes it called shortest path algorithm. So, the same path
from nodes to sink is involved. This makes the use of some
nodes continually and except others. This will enhance the
routing algorithm is to make a comparison with classical rout-
either round. Some network metrics is compared for the two
routing protocols like lifetime, partition time, and PDR.
Fig.2 illustrates the zone area of randomly scattered nodes.
This area has dimensions of 100mx100m. A 100 randomly
scattered nodes for either topological area. The topological
area has one fixed sink with position of (90mx90m).
Fig.3 demonstrates network lifetime with regard to both zones
till network partition. The figure. shows that the proposed
routing algorithm beat Dijkstra, Fuzzy, and ACO methods.
Furthermore, demonstrates maximization with lifetime equal
to 2781 round with PDR 0.993. while Dijkstra routing rank
1001 round with PDR 1, Fuzzy routing rank 1932 round with
PDR 1, and ACO routing rank 2259 round with PDR 1. Round
is sample of time that all nodes send packets to sink. Further-
more, optimal path is reached and energy consumption is
balanced for the suggested FFA routing method. Network par-
tition is fast for Dijkstra routing due to the use of same paths.
Fuzzy and ACO methods involve balanced energy exhaustion
but partition time is less the suggested FFA routing. And
this demonstrates the improvement of the proposed routing
algorithm. Table II states lifetime, partition time, with PDR
for results and for the four submitted methods.
Fig.4 demonstrates residual energy for the compared rout-
ing algorithms for the submitted areas. The suggested FFA
routing algorithm has residual energy lower than the other
methods due to use of more nodes and energy consumption
lead to balance. And this reflect energy consumption is Dijk-
stra routing is not balanced. Fuzzy and ACO methods have