Paper Title
Review and Characteristic Study of Selective Bioinspired Approaches for Task Scheduling in Cloud Environment

Abstract
In recent years, Cloud computing resources are delivered by Virtual Machines. Challenges available in cloud computing, like resource provisioning, load imbalance and performance improvement can be solved using bio-inspired algorithms. Bioinspired, name itself revels biological inspiration from natural world to adapt environmental changes through self-management, self-organization, and self-learning. Bio-inspired algorithms can solve various kinds of problems naturally by providing optimized solutions. To get better performance at the cloud service providers end, the challenge is to schedule tasks given by the cloud users in such a way that it should meet the prerequisites of the user at one end and at the other minimizes costs of the infrastructure. This paper presents a study of Task scheduling algorithms using Nature inspired approaches focusing on Ant colony optimization and Particle swarm optimization. And a brief analysis of ideas used for task scheduling using bio-inspired algorithms. Keywords - Particle Swarm Optimization, Task Scheduling, Bio-inspired, Ant Colony Optimization.