Algorithm 2: Pseudo-code for the proposed approach

Step1: Initialize the population of gray wolves Gi (i = 1, 2, …, n) Step2: Initialize a, A, C Step3: Calculate the fitness of each agent in search space Step4: Galpha = fittest wolf Step5: Gbeta = second best wolf Step6: Gdelta = third best gray wolf Step7: Repeat while itr < Round, then do Step7.1: for each gray_wolf do Step7.2: for each ith sensor in each best search agent gray wolf do Step7.2.1: Find ith maximum loaded CH Max and minimum loaded CH Min in Alpha, Beta and Delta. Step7.2.2: Perform load-balanced clustering for all the best search agents alpha, beta and Delta, respectively. Step7.2.3: If A < 1     [Search into Initial Solution Space i.e., Exploitation]     [//Call Exploitation();]     //Update Galpha     Step7.2.3.1: Set G_Load1 = Gbeta[i]     Step7.2.3.2: Set G_Load2 = Gdelta[i].          If G_Load1< Galpha[i] && G_Load1 < G_Load2            Galpha[i] = G_Load1          Else if G_Load2 < Galpha[i]            Galpha[i] = G_Load2          [End]     Step7.2.3.3: Set G_Load1 = Gbeta[i].     // Update Gbeta     Step7.2.3.4: Set G_Load2 = Gdelta[i].          If G_Load1 > G_Load2            Gbeta[i] = G_Load2          Else            Gbeta[i] = G_Load1          [End]      //Similarly update delta Step7.2.4: Else diverge or perform exploration     //Look in to global space     //Call Exploration();     Step7.2.4.1: Initialize G from the global search space.     //Update Galpha     Step7.2.4.2: Set G_Load1 = Galpha[i].            If G_Load1 > G                 Galpha[i] = G            Else                 [No change]            [End]     //Update Gbeta     Step7.2.4.3: Set G_Load2 = Gbeta[i].            If G_Load1 > G                 Gbeta[i] = G            Else                 [No change]            [End]     //Similarly update delta [End of if in Step7.2.3][End for loop] Step7.3: Update a, A, C Step7.4: Calculate the fitness of each gray wolf Step7.5: Update Galpha, Gbeta, Gdelta Step7.6: Increment itr [End while loop] Step8: Return best gray wolf Galpha