A bio inspired Energy-Aware Multi objective Chiropteran Algorithm (EAMOCA) for hybrid cloud computing environment

Resource scheduling is a momentous task of determining and formulating when an activity should start or end depending on the number of tasks, the availability of the resources, time and processor speed. A cloud is an aggregation of resources or services that are provided as service through network. In earlier version of cloud computing (grid computing) it was enough to find the subset of resources for the applications whereas cloud computing goes one step higher allocating resources to Virtual Machines (VM's) as well as scheduling tasks on the VM's. So resource scheduling is indispensable in cloud computing for load balancing and maximizing the utilization while minimizing the execution time and energy. Few approaches relating to energy salvation have certain disadvantages such as, time complexity and slow Convergence. Hence Energy-Aware Multi objective Chiropteran Algorithm (EAMOCA) is developed by bringing together the echo-localization and hibernation properties for scheduling resources as well as conserving energy. Promotion of energy salvation in cloud environment is achieved in a well delineated manner. By using the performance metrics such as total energy consumed by physical resources, SLA violation (CPU performance) and VM migration, we have manipulated our approach through real time implementation by setting up a private cloud employing VMware.