A Novel QoS Routing Energy Consumption Optimization Method Based on Clone Adaptive Whale Optimization Algorithm in IWSNs

Algorithm 1

Clonal expansion and high-probability mutation.

 Input: The population sorted according to the energy consumption value from small to large is set to pop1, the number of individuals is pop_num,

 Output: The cloned population is set to pop2

1.  First perform multi-level cloning operations

2.  for p ∈ [1, pop_num]

3.    if p<pop_num×0.2

4.      Assign the individual of pop1(1) to pop2(p)

5.    else if p <pop_num×0.5

6.      Assign the individual of pop1(2) to pop2(p)

7.    else if p <pop_num×0.7

8.      Assign the individual of pop1(3) to pop2(p)

9.    else

10.      Assign the individual of pop1(4) to pop2(p)

11.    end if

12.  end for

13.  Then perform high-probability mutation operations

14.  for p ∈ [1, pop_num]

15.    r is a random number and r∈ [0,1]

16.    if r<0.3

17.      Perform mutation operation on pop2(p)

18.    end if

19.  end for

20.  Return pop_2