Hard Disk Drive Failure Prediction for Mobile Edge Computing Based on an LSTM Recurrent Neural Network

Algorithm 1

The algorithm for calculating the health degree of a soon-to-fail HDD.

	Input:
	(1) Health samples of a drive: healthsamples
	(2) The number of sample features: featuresNum
	(3) Transformation function:
	(4) Weights of health status and time: ,
	Output:
	Health degree of a drive: drive_health_degree
	Begin
	(1) last = healthsamples [len (healthsamples) – 1]
	(2) for sample in healthsamples
	(3)  while i < featuresNum
	(4)   o ⟵ o + pow (sample [i] – last[i], 2.0)
	(5)   i ⟵ i + 1
	(6)  Endwhile
	(7)  O. append (sqrt (o))
	(8) endfor
	//Standardizing the values of O to [−1, 1]
	(9) O ⟵ standard (O)
	(10) while i < len (healthsamples)
	(11)  E[i] ⟵ f(i)
	(12)  i ⟵  i + 1
	(13) Endwhile
	(14) E ⟵ standard (E)
	(15) while i < len(healthsamples)
	(16)   health_degree [i] ⟵ ω1O[i] + ω2E[i]
	(17) Endwhile
	(18) return health_degree
	End