Paper Info
Title
Load balanced task scheduling for cloud computing: a probabilistic approach
Abstract
Load balancing is the process of distributing customer tasks among multiple computing resources, such as virtual machines (VMs), servers and networks. It is a major concern in cloud computing as the number of customers demanding the service is growing exponentially. An efficient load balancing approach can monitor the load of the VMs proactively and assigns the customer tasks to the VMs accordingly. This paper presents a load balanced task scheduling algorithm in the cloud, which is based on probability theory. The proposed algorithm is shown to be a 2-approximation algorithm with a time complexity of O(lm), where l is the number of customer tasks and m is the number of VMs. The algorithm is simulated extensively. The simulation results demonstrate that our proposed algorithm can remarkably balance the load of the VMs as compared to the existing algorithms in four different performance measures, namely standard deviation of VM loads, maximum load, minimum load and zero load. The performance is also validated through statistical test by means of analysis of variance and 95% confidence interval.
Year
DOI
Venue
2019
10.1007/s10115-019-01327-4
Knowledge and Information Systems
Keywords
Field
DocType
Cloud computing, Load balancing, Task scheduling, Virtual machine, Quality of service, Probability theory
Data mining,Virtual machine,Computer science,Load balancing (computing),Scheduling (computing),Server,Quality of service,Probabilistic logic,Time complexity,Distributed computing,Cloud computing
Journal
Volume
Issue
ISSN
61
3
0219-3116
Citations 
PageRank 
References 
0
0.34
29
Authors
2
Name
Order
Citations
PageRank
Sanjaya Kumar Panda14712.46
Prasanta K. Jana273944.84