Journal of Big Data

Table 1 Simulation parameters considered in implementing the HGDSMO Scheme

From: Hybrid gradient descent spider monkey optimization (HGDSMO) algorithm for efficient resource scheduling for big data processing in heterogenous environment

Type	Parameter	Value
Tasks	Number of tasks	100–1000
	Length of the task	90,000
	Size of the file	600
Users	Number of users	100
Users	Number of brokers	5
Data center	Number of data centers	2
VM	Policy type	Time-shared
	Number of VMs	10
	RAM	512 MB
	Size	10,000
	Operating system	Linux
	VMM	Xen
	Number of CPUs	1 on each VM
	Bandwidth	10,000
	MIPS	1000
Hosts	Storage	10,00,000
	RAM	2048 MB
	Bandwidth	10,000

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