Abstract: Now a days cloud computing provides utility of services to users in IT oriented services. There are more number of technologies were presented in cloud computing, MapReduce programming model is one of the critical technology in cloud. There is a novel scheduling algorithm Adaptive Task Allocation Scheduler (ATAS) for allocating non-identical tasks in MapReduce programming model in heterogeneous cloud. The ATAS adopts more accurate in to determine response time and backup tasks in heterogeneous cloud environment. However, most existing efforts in improving the energy efficiency of a cloud system focus on workload based allocation at the system. This study tries to address the energy efficiency with a new technique HTS (Hash based Task Scheduling) in a heterogeneous cloud system at the task scheduling level. It schedules tasks based on the index that is calculated while execution. So in this study we propose to develop an algorithm Task Scheduling with Hash based Sorting, it is a positional index based task scheduling algorithm in processing of different jobs in heterogeneous cloud environment with all proceedings of each process in parallel speculative execution in real time cloud environment. The experimental results show efficient task scheduling with positional sorted index in real time heterogeneous with CPU performance when compared to ATAS schema in real time cloud environment.