Research Article

Improving Packet Delivery Performance in Water Column Variations through LOCAN in Underwater Acoustic Sensor Network

Algorithm 1

Cat Optimized Cognitive Acoustic Networks (COCAN) for UWASN.
Begin
Input parameters to the algorithm
Initialize the nodes (), , and SPC based on water column variation parameter
While (termination criteria not satisfied or )
Calculate the fitness function value for all the nodes and sort them
Xs = Node with best solution
  For
   If
   Start seeking mode
   Xnp = new position of nodes in underwater network
   Xcp = current position of nodes in underwater with parameters
   R = random number varies between 0 and 1 based on co-channel interference
   Pi = probability of current node based on water column variations
   FSi = fitness value of node based on current Doppler effect and GS
   FSmax = maximum value of fitness function, FSmin = minimum value of fitness function for different water column variations and channel selection
            
            
   Else
   Start tracing mode
   Xbest,d = position of the cat with the best solution in water column variation
   Xi,d = position of the cat in dimension of water variation parameters
   c1 = a constant
   r1 = a random value in range [0,1]
   Xi,d,new = the new position of cat in dimension varying water column and selects the channel
   Xi,d,old = current position of cat in dimension varying water column with current channel
            
            
   End if
  End for i
End while
   Post-processing the results and visualization
End