Abstract: The main objective of this study makes effective slot configuration of distributed computing based on resource utilization as updated with semantic relations in real time applications. Dynamic resource slot configuration is latest component in open source implementation Hadoop based data proceedings as extensible survey onto huge information place in current years. Current Hadoop cluster implementation unique let to slit in layout (fixed number of mapping slots in resource utilization). To increase the cluster lifetime traditionally introduce simple yet effective schema for slot ratio between in map reduce in resource allocation. Furthermore, these systems usually compute multiple concurrent tasks without any training sequences in resource allocation. This state of affairs have move to notice closer to mind-adaptive structures that dynamically reorganize using device wealth to optimize for a specific target. So in this paper we propose to develop efficient and effective framework for dynamic resource utilization in map reducing, i.e., SAVE (Self Adaptive Virtualization Aware High performance/low energy heterogeneous system architecture) for hardware and software for runtime execution of appropriate tasks with of resource utilization. Our experimental results show efficient allocation of processes in cluster map reducing in concurrent processes. Our proposed approach may achieve efficient data utilization in real time cloud computing assessments.
K. Divya Bharathi and P.V.R.D. Prasada Rao, 2016. Dynamic Resource Utilization over Parallel Slot Configuration in Distributed Computing. Asian Journal of Information Technology, 15: 3538-3544.