ANN based execution time prediction model and assessment of input parameters through ISM
المؤلفون المشاركون
Shukla, Anju
Singh, Harikesh
Kumar, Shishir
المصدر
The International Arab Journal of Information Technology
العدد
المجلد 17، العدد 5 (30 سبتمبر/أيلول 2020)، ص ص. 683-691، 9ص.
الناشر
جامعة الزرقاء عمادة البحث العلمي
تاريخ النشر
2020-09-30
دولة النشر
الأردن
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Cloud computing is on-demand network access model which provides dynamic resource provisioning, selection and scheduling.
The performance of these techniques extensively depends on the prediction of various factors e.g., task execution time, resource trust value etc., As the accuracy of prediction model absolutely depends on the input data that are fed into the network, Selection of suitable inputs also plays vital role in predicting the appropriate value.
Based on predicted value, Scheduler can choose the suitable resource and perform scheduling for efficient resource utilization and reduced makespan estimates.
However, precise prediction of execution time is difficult in cloud environment due to heterogeneous nature of resources and varying input data.
As each task has different characteristic and execution criteria, the environment must be intelligent enough to select the suitable resource.
To solve these issues, an Artificial Neural Network (ANN) based prediction model is proposed to predict the execution time of tasks.
First, input parameters are identified and selected through Interpretive Structural Modeling (ISM) approach.
Second, a prediction model is proposed for predicting the task execution time for varying number of inputs.
Third, the proposed model is validated and provides 21.72% reduction in mean relative error compared to other state-of-the-art methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Shukla, Anju& Kumar, Shishir& Singh, Harikesh. 2020. ANN based execution time prediction model and assessment of input parameters through ISM. The International Arab Journal of Information Technology،Vol. 17, no. 5, pp.683-691.
https://search.emarefa.net/detail/BIM-1439712
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Shukla, Anju…[et al.]. ANN based execution time prediction model and assessment of input parameters through ISM. The International Arab Journal of Information Technology Vol. 17, no. 5 (Sep. 2020), pp.683-691.
https://search.emarefa.net/detail/BIM-1439712
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Shukla, Anju& Kumar, Shishir& Singh, Harikesh. ANN based execution time prediction model and assessment of input parameters through ISM. The International Arab Journal of Information Technology. 2020. Vol. 17, no. 5, pp.683-691.
https://search.emarefa.net/detail/BIM-1439712
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 690-691
رقم السجل
BIM-1439712
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر