Comparison of Statistical Calculations for Software Model Analysis
0 likes97 views
The document discusses the use of cloud computing for resource allocation in software model analysis, highlighting the challenges of scheduling tasks dynamically due to uncertain arrivals. It proposes a genetic algorithm as a heuristic method to efficiently allocate resources based on computation and memory usage, aiming for global optimization. By employing parallel processing, the approach reduces execution time while storing scheduled data in the cloud.
1 of 1
Download to read offline
More Related Content
Viewers also liked (9)
Ad
Similar to Comparison of Statistical Calculations for Software Model Analysis (20)
Ad
More from ijcoa (20)
Comparison of Statistical Calculations for Software Model Analysis
- 1. International Journal of Computing Algorithm, Vol 2(1), June 2013 ISSN(Print):2278-2397 Website: www.ijcoa.com Comparison of Statistical Calculations for Software Model Analysis N.Sasikala1 , G.Rasitha Banu2 , K.Rangarajan3 1 2 Research Scholar, Mother Theresa Women’s University 3 Hod, MCA Department, Bharath University Abstract Cloud Computing is the utilization of pool of resources for remote users through internet that can be easily accessible, scalable and utilization of resources. To attain maximum utilization of resources the tasks need to be scheduled. The problem in scheduling is allocating the correct resources to the arrived tasks. Dynamic scheduling is that the task arrival is uncertain at run time and allocating resources are tedious as several tasks arrive at the same time. To avoid this scheduling problem, Genetic Algorithm is used. Genetic algorithm is a heuristic method that deals with the natural selection of solution from all possible solutions. Using genetic algorithm the tasks are scheduled according to the computation and memory usage. The tasks are scheduled dynamically. The execution time is reduced by parallel processing. The scheduled data is stored in cloud. By using GA to obtain global optimization.