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Table 4: Average waiting time (AWT) in seconds for RRc on Current Machine and RRp Previous Machine

Table 4 Average waiting time (AWT) in seconds for RRc on Current Machine and RRp Previous Machine

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CC delivers three different service models which are categorized, as depicted in Figl, into: infrastructure as a service (IaaS), platform as a service (PaaS), and software as services (SaaS) [5]. In IaaS, the resources, storage and processing power are provided in the form of virtual machines. PaaS provides a computing platform which includes operating systems, programming languages, and web based applications. In SaaS, the software and database access is allowed for a user according to a particular usage based payment model. Nowadays, CC becomes one of the most significant and attractive technology trend in the IT market since it efficiently provides dynamic, flexible, reliable, sustainable, scalable and _ self- managed computing infrastructure [7]. Moreover, there is no need to purchase new hardware, to pay for training practices or to license new programs. So, the cost saving is a major benefit for both small and large enterprises which allow them to focus on
CC delivers three different service models which are categorized, as depicted in Figl, into: infrastructure as a service (IaaS), platform as a service (PaaS), and software as services (SaaS) [5]. In IaaS, the resources, storage and processing power are provided in the form of virtual machines. PaaS provides a computing platform which includes operating systems, programming languages, and web based applications. In SaaS, the software and database access is allowed for a user according to a particular usage based payment model. Nowadays, CC becomes one of the most significant and attractive technology trend in the IT market since it efficiently provides dynamic, flexible, reliable, sustainable, scalable and _ self- managed computing infrastructure [7]. Moreover, there is no need to purchase new hardware, to pay for training practices or to license new programs. So, the cost saving is a major benefit for both small and large enterprises which allow them to focus on
Figure2: Steps of task scheduling in cloud computing
Figure2: Steps of task scheduling in cloud computing
Table 1: Information about Job Scheduling Algorithms
Table 1: Information about Job Scheduling Algorithms
Figure 8: Dynamic task scheduling using MRR Qt1=5, Qt2=9, Qt3=6 , Ot4=8, Ot5=4 ,OQt6=6 ,At7=4 OtB=6 ,Ot9=10, Qt10=4
Figure 8: Dynamic task scheduling using MRR Qt1=5, Qt2=9, Qt3=6 , Ot4=8, Ot5=4 ,OQt6=6 ,At7=4 OtB=6 ,Ot9=10, Qt10=4
15% September 2018. Vol. 96. No 17 © 2005 — ongoing JATIT & LLS
15% September 2018. Vol. 96. No 17 © 2005 — ongoing JATIT & LLS
Table 2: Job Scheduling Algorithms Pseudo Codes and Examples
Table 2: Job Scheduling Algorithms Pseudo Codes and Examples
burst time by dividing the value of SReg by the number of tasks residing in the ready queue. 3.1 METHODOLOGY
burst time by dividing the value of SReg by the number of tasks residing in the ready queue. 3.1 METHODOLOGY
The highest layer in the CloudSim stack is the user code where the basic cloud entities are exposec such as number of machines in hosts and thei specification, number of tasks and __ thei requirements in the application, the number ot users and their application types, and_ broke scheduling policies.
The highest layer in the CloudSim stack is the user code where the basic cloud entities are exposec such as number of machines in hosts and thei specification, number of tasks and __ thei requirements in the application, the number ot users and their application types, and_ broke scheduling policies.
Figure 11: Average waiting time when MRR was used over different number of VMs for different Cloudlet amount
Figure 11: Average waiting time when MRR was used over different number of VMs for different Cloudlet amount
Figure 13: Average waiting time versus number of VMs for 100 cloudlets run using MRR and Rk
Figure 13: Average waiting time versus number of VMs for 100 cloudlets run using MRR and Rk
The average waiting time (AWT) using MRR is less than the AWT when using RR as shown in Table 5. For this experimented data set, the MRR is faster than RR in average waiting time for the selected quantum by up 5 times.
The average waiting time (AWT) using MRR is less than the AWT when using RR as shown in Table 5. For this experimented data set, the MRR is faster than RR in average waiting time for the selected quantum by up 5 times.
Figure 14: Comparison of experimental and theoretical MRR complexity
Figure 14: Comparison of experimental and theoretical MRR complexity
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