Performance Analysis of Cloud Computing Center with Queueing Model

2018 ◽  
Author(s):  
S. Anand Gnana Selvam ◽  
S. Rita ◽  
M. Reni Sagayaraj
Keyword(s):  
Cloud Computing ◽  
Performance Analysis ◽  
Queueing Model ◽  
Computing Center

scholarly journals Zero Queueing for Multi-Server Jobs

2021 ◽  
Vol 5 (1) ◽  
pp. 1-25
Author(s):  
Weina Wang ◽  
Qiaomin Xie ◽  
Mor Harchol-Balter
Keyword(s):  
Cloud Computing ◽  
Stability Region ◽  
Transient Analysis ◽  
Queueing Systems ◽  
Sufficient Conditions ◽  
Hard Problem ◽  
Queueing Model ◽  
Multiple Servers ◽  
First Results ◽  
Multi Server

Cloud computing today is dominated by multi-server jobs. These are jobs that request multiple servers simultaneously and hold onto all of these servers for the duration of the job. Multi-server jobs add a lot of complexity to the traditional one-server-per-job model: an arrival might not "fit'' into the available servers and might have to queue, blocking later arrivals and leaving servers idle. From a queueing perspective, almost nothing is understood about multi-server job queueing systems; even understanding the exact stability region is a very hard problem. In this paper, we investigate a multi-server job queueing model under scaling regimes where the number of servers in the system grows. Specifically, we consider a system with multiple classes of jobs, where jobs from different classes can request different numbers of servers and have different service time distributions, and jobs are served in first-come-first-served order. The multi-server job model opens up new scaling regimes where both the number of servers that a job needs and the system load scale with the total number of servers. Within these scaling regimes, we derive the first results on stability, queueing probability, and the transient analysis of the number of jobs in the system for each class. In particular we derive sufficient conditions for zero queueing. Our analysis introduces a novel way of extracting information from the Lyapunov drift, which can be applicable to a broader scope of problems in queueing systems.

A Remote Monitoring System Based on Measuring Instrument Cloud

2014 ◽  
Vol 1014 ◽  
pp. 525-529 ◽  
Author(s):  
Jun Zhang ◽  
Yuan Sheng Liu ◽  
Lin Xue
Keyword(s):  
Cloud Computing ◽  
Monitoring System ◽  
Environmental Parameters ◽  
Mobile Terminal ◽  
Measuring Instrument ◽  
Remote Monitoring System ◽  
Front End ◽  
Remote Lab ◽  
Computing Center ◽  
Network Equipment

A remote lab room monitoring system based on measuring instrument cloud is presented in this paper. The system consists of cloud computing center, embedded front-end acquisition hardware, mobile terminal device, and network equipment. Measuring service software system located in cloud computing center sends control commands to front-end acquisition hardware and collects acquisition data. Then processing, analysis and integration of signals are completed in the cloud computing framework. Finally, all the information can be interacted with mobile terminals by Web service. The system can monitor environmental parameters of lab rooms located in different campuses, such as temperature, humidity, light, smoke, and flooding. When environmental parameters exceed the preset thresholds, light and audio alarms will be immediately switched on and the administrator will be noticed on Web management page.

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