• Madhuri H. Patil

In cloud computing, resource requirement for tasks is vast and it may have ambiguous factors and changes dynamically over time. These factors causes load imbalances. A scheduling technique known as interlacing peak is developed during which first, the resource requirement of task is obtained using information such as CPU, I/O and memory information is gathered continuously after certain time period then all task are classified into three queues i.e CPU intensive, I/O intensive and memory intensive, then after that resources are being sorted in ascending order into again three queues CPU intensive, I/O intensive and memory intensive which is performed by global resource manager. After all this the task is being scheduled for its execution according to its intensity for CPU, I/O and memory usge. Intensity is determined on the basis of CPU capacity, I/O operations and memory usage. In another words, low CPU intensity tasks are scheduled with resources with low CPU utilization then it matched with resources of CPU intensive queue, low I/O intensity tasks are scheduled with resources with shorter I/O wait times are matched with resources with I/O intensive queue and low memory intensity tasks are scheduled with resources that have low memory usage are matched up with resources of memory intensive queue. The proposed system can balance loads especially true when resources are less often and many tasks will demand for the same resource.

Cloud computing, load balancing, multiqueue, task classification

"TASK CLASSIFICATION USING MULTIQUEUE INTERLACING PEAK SCHEDULING METHOD IN CLOUD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.80-85, June 2019, Available :http://www.jetir.org/papers/JETIR1906I41.pdf

"TASK CLASSIFICATION USING MULTIQUEUE INTERLACING PEAK SCHEDULING METHOD IN CLOUD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp80-85, June 2019, Available at : http://www.jetir.org/papers/JETIR1906I41.pdf