GreenSched: An intelligent energy aware scheduling for deadline-and-budget constrained cloud tasks

Abstract

The constant growth of the energy crisis within the ICT Sector has persistently gained importance thereby prompting endeavors to curb growing energy demands and associated expenditures. This paper attempts to propose an intelligent energy aware task allocation and resource provisioning technique running in GreenSched model. The GreenSched model tends to exploit the heterogeneity of tasks and multi-core capacity of the varied nodes in the cloud environment and attempts to proactively schedule the deadline-and budget- constrained tasks on identified less energy consuming or energy aware nodes. It implements a Forward-only Counter Propagation Network (CPN) based intelligent scheduler unit that runs a scheduling technique to identify the best nodes for the task allocation process, one with least energy consumption and deadline- and budget -fulfilling capability. The nodes are clustered and classified by comparing their energy consumption values. The proposed algorithm has been implemented using the CloudSim toolkit and Kohonen and CP-ANN Toolbox with the help of MatlabTM platform. The experimental results exhibit that the proposed technique offers reduced energy consumption along with an overall improvement in the performance by meeting the deadline-and-budget constraints imposed by the users.