Load Pattern Identifier (LOPI) for Scaling Size and Pattern of the Workload for Setting Threshold Values Dynamically in Cloud Environment
Author(s):
Pooja Kumari Jha, Dr Deepika Pathak
Keywords:
Cloud, Threshold, Auto-scaling, Load, Rate.
Abstract
As internet applications such as social networks, streaming networking, diverse online groups and smartphone apps are continuously increasing, website consumer traffic is extremely complex, and sometimes unpredictable. Accessible in both regions, with Pay-as-you-go frameworks, cloud storage platforms as self-service on request. The auto-scaling method must be used by service providers to maximize scalability, usage of resources and the providers to scale the resources according to the consumers. Dynamic threshold technology aims to optimize the activity and expense of physical servers. Efficient allocation of capital will further reduce the cost of operation. In addition to the physical server, threshold values may be set on a virtual machine. It cannot be always the same load or workload. The Load Pattern Identifier (LoPI) is used for finding the load pattern. In contrast with interpolation, extrapolation, and correlation examination, the demand for real time and the expected workload. The control motor is used for LoPI analysis and rule generation. Finally, the complex threshold for cloud services is set to auto-scale.
Article Details
Unique Paper ID: 150814

Publication Volume & Issue: Volume 7, Issue 10

Page(s): 71 - 78
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