One of the latest apt platform in today's trending technological scenario for imparting application based utilities and services rendered by various distributed resources situated remotely is the Cloud Computing paradigm. The routine task operations and services involve efficient energy utilization with minimum dissipation via load balancing and process allocation. A heuristics defined approach has been implemented in this research work for execution of task scheduling activities with optimal resource sharing. Here a robust scheduling technique is used by the scheduler in the heterogeneous cloud network for mapping the available resources to execute scalable tasks optimally. The research area takes into consideration various performance based parameters like Make-Span, Throughput, Average Response Time (ART) etc. for analysis and comparison with the standard scheduling procedures. There was a large energy loss using the previous scheduling and load balancing standard algorithms in reference to the above mentioned parameters. Hence a algorithm named Energy Efficient Multi layered Scheduling (EEMLS) is proposed that outperforms the earlier algorithms in common practice; viz. Max-Min, Round Robin, Opportunistic Load Balancing (OLB), Artificial Bee Colony (ABC) and Minimum Completion Time (MCT) by containing the energy loss considerably during the process work flow of task execution. The entire scenario is best implemented in cloud environment using the Cloudsim simulator for obtaining the results to show better performance with energy saving.