Scheduling Algorithms for Allocation of Resources in Cloud Computing Environment

Cloud computing technology facilitates computing intensive applications by providing virtualized resources which can be dynamically provisioned. Virtualization plays a significant role for managing and coordinating the access from the resource pool to multiple virtual machines on which multiple heterogeneous applications are running. The use of virtualization techniques allows exible assignment of resources to virtual machines enabling elastic, on demand resource provisioning. Various dynamic scheduling algorithms are used for allocation of virtualized resources. In this paper, compare three different scheduling algorithms such as converging algorithm, skewness algorithm and synthetic heuristic algorithm. The converging algorithm converges resource into private cloud resource pools and global resource pools and enables real time maintenance for the dynamic variation of resource to ensure continuity and reliability. Skewness algorithm is used to allocate data center resources dynamically based on application demands and optimizing the number of servers in use. The synthetic heuristic algorithm is based on genetic algorithm, for independent task scheduling in cloud computing systems