Enhancing Cloud Computing Scheduling based on Queuing Models
TL;DR: Experimental results indicate that the proposed model for cloud computing scheduling based on multiple queuing models increases utilization of global scheduler and reduce waiting time.
read more
Abstract: paper presented a proposed model for cloud computing scheduling based on multiple queuing models. This allowed us to improve the quality of service by minimize execution time per jobs, waiting time and the cost of resources to satisfy user's requirements. By taking advantage of some useful proprieties of queuing theory scheduling algorithm is proposed to improve scheduling process. Experimental results indicate that our model increases utilization of global scheduler and reduce waiting time. Keywordscomputing; Queuing models; Scheduling process.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
An effective scheduling strategy based on hypergraph partition in geographically distributed datacenters
TL;DR: A workflow job scheduling algorithm is proposed, which aims to reduce the response time and considers the cloud state, and the task scheduling algorithm based on the hypergraph partition is designed with the goal of reducing the completion time and energy consumption for the tasks.
30
Applying queue theory for modeling of cloud computing: A systematic review
TL;DR: This work summarizes and classifies the research efforts conducted on applying queue theory for modeling of cloud computing (AQTMCC), providing a good starting point for further research in this area.
28
Service load balancing, task scheduling and transportation optimisation in cloud manufacturing by applying queuing system
TL;DR: Recently, there is a great deal of attention in Cloud Manufacturing as a new service-oriented manufacturing paradigm, to integrate the activities and services through a CMfg.
28
Message Queuing Model for a Healthcare Hybrid Cloud Computing Platform
Roxana Marcu,Iulian Danila,Dan Popescu,Oana Chenaru,Loretta Ichim +4 more
- 25 Mar 2017
TL;DR: Experimental results indicate that proposed model is able to support a great number of arrival requests providing short response time related to priority classes, and performance is measured in terms of the number of requests, waiting time, response time, and requests drop rate for each priority class defined.
Analysis of Cloud Network Management Using Resource Allocation and Task Scheduling Services
TL;DR: From the results, it was concluded that using virtualization in a cloud DataCenter servers will result in enhanced server performance offering lower average wait time even with a higher request rate and longer duration of resource use (service availability).
References
•Book
Simulation Modeling and Analysis
Averill M. Law,W. David Kelton +1 more
- 01 Jan 1982
TL;DR: The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering, business, computer science and operations research.
10.9K
A Taxonomy and Survey of Cloud Computing Systems
Bhaskar Prasad Rimal,Eunmi Choi,Ian Lumb +2 more
- 25 Aug 2009
TL;DR: This paper develops a comprehensive taxonomy for describing cloud computing architecture and uses this taxonomy to survey several existing cloud computing services developed by various projects world-wide, to identify similarities and differences of the architectural approaches of cloud computing.
1.6K
A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing
Martin Randles,David Lamb,Azzelarabe Taleb-Bendiab +2 more
- 20 Apr 2010
TL;DR: This paper investigates three possible distributed solutions proposed for load balancing; approaches inspired by Honeybee Foraging Behaviour, Biased Random Sampling and Active Clustering.
583
•Book
Handbook of Cloud Computing
Borko Furht,Armando J. Escalante +1 more
- 01 Jan 2018
TL;DR: This handbook presents the systems, tools, and services of the leading providers of cloud computing; including Google, Yahoo, Amazon, IBM, and Microsoft.
567
•Book
Scheduling and Load Balancing in Parallel and Distributed Systems
Behrooz Shirazi,Krishna M. Kavi,Ali R. Hurson +2 more
- 01 Apr 1995
TL;DR: This book discusses how to schedule the processes among processing elements to achieve the expected performance goals, such as minimizing execution time, minimizing communication delays, or maximizing resource utilization.
436