Cloud computing is a shared pool of compute, storage and network resources that are elastic in nature and can dynamically scale to meet changing demands of an IT organization. Every IT organization has to invest in hardware, software resources to make the business run effectively. Cloud offers guaranteed and reliable access to these resources on pay-as-you-use manner. Increasing demand of cloud services leads to certain challenges. One of the major issue in cloud computing is related to task scheduling in which the goal of service provider is to use the available resources in an efficient manner. A number of meta-heuristic algorithms have been proposed to solve this problem. In this paper, cloud task scheduling policy based on Ant colony Optimization (ACO) and Honey Bee Optimization (HBO) algorithms are combined to improve resource utilization. Minimizing Makespan, Flowtime and reducing cost is the major goal of proposed algorithm.

ACO, HBO, Hybridisation, Makespan, Flowtime, Task scheduling

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