Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA
Algorithm 2 Hybrid immune and bat scheduling algorithm (HIBSA).
(1)
The scheduling population P0 is randomly generated, the population size is n, and the initialization generation t = 0
(2)
According to the individual evaluation algorithm, all the individuals of rank 0 and rank 1 in P are put into the set and , respectively
(3)
If ()
select the optimal solution in as the result and the algorithm ends
(4)
else
(5)
while (t < T)
(6)
A solution is randomly selected from as the historical optimal position of the current population, and BA is implemented for Pt to get
(7)
Clear set ,. According to the individual evaluation algorithm, all the individuals of rank 0 and rank 1 in the set are put into the set and , respectively
(8)
If ()
(9)
select the optimal solution in as the result and the algorithm ends
(10)
else
(11)
For , the immune clonal selection algorithm is implemented to get
(12)
Clear set and . According to the individual evaluation algorithm, all the individuals of rank 0 and rank 1 in the set are put into the set and , respectively
(13)
If ()
(14)
select the optimal solution in as the result and the algorithm ends
(15)
else
(16)
According to the individual evaluation algorithm, put the first n individuals in the set into Pt+1
(17)
t = t + 1
(18)
end if
(19)
end if
(20)
end while
(21)
end if
(22)
select a solution randomly from as the result and the algorithm ends
