Dynamic Q-Learning-Based Optimized Load Balancing Technique in Cloud

Algorithm 1

Dynamic programming algorithm to load utilization corresponding to bandwidth and network availability.

(1)	Data centre = ∑ Load, Let VMid = the VM which will start
(2)	for every data in PT = load in to DC
	Capacity in DC
(3)	Let Thres_bottom = the btbottom threshold for the load of VM
(4)	Let Thres_stop = the tttop threshold for a load of VMMC
(5)	Let n = the amount of hosts that the VM might be running on
(6)	Input: VMid, bt, tt, n
(7)	Output: Nill
(8)	End for Loop
(9)	For {Get the t hours load predictions of the starting VM}
(10)	VMPreload < -Get-LpLoadPrediction (VMid)
(11)	{Get load prediction of each VM on host}
(12)	HRes < -Get_ResFromLoad (VMs, PreLoads, eachhost)
(13)	endFor
(14)	For: each server PM in datacenter
(15)	PM.Tcpu > β
(16)	workloadBalance in Data center()
(17)	End Function