Fairness-Aware Task Allocation for Heterogeneous Multi-Cloud Systems
Sanjaya Kumar Panda, Roshni Pradhan, Benazir Neha, Sujaya Kumar Sathua · Advances in systems analysis, software engineering, and high performance computing book series · 2015
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 effort (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 allocation (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.