Efficient Forecasting of HTTP workload using Seasonal ARIMA Model in IaaS

Provided by: Creative Commons
Topic: Enterprise Software
Format: PDF
In this paper, the authors aim at improving Quality-of-Service (QoS) in Infrastructure-as-a-Service (IaaS) model in cloud computing by forecasting resource provisioning on demand basis. QoS in IaaS model can be improved by provisioning of resources in such a way that it not only complies with Service Level Agreement (SLA) but also allocates resources in right amount so that efficient utilization of resources occurs leading to low cost. In a dynamic workload environment like web server, the QoS parameters viz. response time, throughput, etc. can be achieved only by elastic provisioning of resources.

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