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Chapter 11
DOI: 10.4018/978-1-4666-8676-2.ch011
ABSTRACT
Cloud computing is rapidly growing for its on-demand services over the Internet. The customers can
use these services by placing the requirements in the form of leases. In IaaS cloud, the customer submits
the leases in one of the form, namely advance reservation (AR) and best efort (BE). The AR lease has
higher priority over the BE lease. Hence, it can preempt the BE lease. It results in starvation among the
BE leases and is unfair to the BE leases. In this chapter, the authors present fairness-aware task alloca-
tion (FATA) algorithm for heterogeneous multi-cloud systems, which aims to provide fairness among
AR and BE leases. We have performed rigorous experiments on some benchmark and synthetic datasets.
The performance is measured in terms of two metrics, namely makespan and average cloud utilization.
The experimental result shows the superiority of the proposed algorithm over the existing algorithm.
INTRODUCTION
The popularity of Cloud Computing is rapidly growing because of its advancement in virtualization
technology (Buyya, Yeo, Venugopal, Broberg, & Brandic, 2009; Li et al., 2012; Huang et al., 2013).
This technology facilitates the cloud service providers (CSPs) to create the virtual machines (VMs)
instantly (Desmarais, 2013, pp. 18-24). Moreover, the VMs are deployed in a data center to access a
service (Sotomayor, Montero, Llorente, & Foster, 2008). Thus, the CSP provides on-demand service
over the internet. These services are delivered to customers on pay-per-use basis. But these services are
Fairness-Aware Task
Allocation for Heterogeneous
Multi-Cloud Systems
Sanjaya Kumar Panda
Indian School of Mines Dhanbad, India & VSS
University of Technology Burla, India
Roshni Pradhan
VSS University of Technology Burla, India
Benazir Neha
VSS University of Technology Burla, India
Sujaya Kumar Sathua
VSS University of Technology Burla, India