Differential Grey Wolf Load-Balanced Stochastic Bellman Deep Reinforced Resource Allocation in Fog Environment

Algorithm 1

Differential Evolution-based Grey Wolf Optimization.

	Input: Dataset “” task “,” fog nodes “”
	Output: Latency-minimized optimal load balancing
(1)	Initialize “,” “ ,” “”
(2)	Begin
(3)	For each dataset “” with task “” and fog nodes “”
(4)	Formulate cloud data centers with “” numbers of servers “” as in equations (1) and (2)
(5)	Model “” processing different numbers of tasks “” as in equations (3) and (4)
(6)	Update positions of wolves or the computing nodes by handling overutilization of fog as in equations (5) and (6)
(7)	Handle under-utilized fog detection using equations (9–11)
(8)	Estimate the final position vectors of the current individual as in equations (12–14)
(9)	Handle migration between virtual machines as in equation (15)
(10)	Return optimal load balancing fog computing nodes
(11)	End for
(12)	End