Abstract
This paper contains data on Performance Prediction for Cloud Service Selection. To measure the performance metrics of any system you need to analyze the features that affect these performance, these features are called " workload parameters". The data described here is collected from the KSA Ministry of Finance that contains 28,147 instances from 13 cloud nodes. It was recorded during the period from March 1, 2016, to February 20, 2017, in continuous time slots. In this article we selected 9 workload parameters: Number of Jobs in a Minute, Number of Jobs in 5 min, Number of Jobs in 15 min, Memory Capacity, Disk Capacity,: Number of CPU Cores, CPU Speed per Core, Average Receive for Network Bandwidth in Kbps and Average Transmit for Network Bandwidth in Kbps. Moreover, we selected 3 performance metrics: Memory utilization, CPU utilization and response time in milliseconds. This data article is related to the research article titled "An Automated Performance Prediction Model for Cloud Service Selection from Smart Data” (Al-Faifi et al., 2018) [1].
Highlights
This paper contains data on Performance Prediction for Cloud Service Selection
Computer Science Performance prediction, cloud computing Tables Data was collected from the KSA Ministry of Finance that contains 28,147 instances from 13 cloud nodes
Raw data with class labels A set of attributes include the number of Jobs in a Minute, number of Jobs in 5 min, a number of Jobs in 15 min, memory capacity, disk capacity, number of CPU cores, CPU speed per core, average receive for network bandwidth in Kbps, and average transmit for network bandwidth in Kbps
Summary
Abdullah Mohammed Al-Faifi n, Biao Song, Mohammad Mehedi Hassan, Atif Alamri, Abdu Gumaei. This paper contains data on Performance Prediction for Cloud Service Selection. The data described here is collected from the KSA Ministry of Finance that contains 28,147 instances from 13 cloud nodes. It was recorded during the period from March 1, 2016, to February 20, 2017, in continuous time slots. We selected 3 performance metrics: Memory utilization, CPU utilization and response time in milliseconds. This data article is related to the research article titled "An Automated Performance Prediction Model for Cloud Service Selection from Smart Data” (Al-Faifi et al, 2018) [1].
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