Title :
Using Long-Term Prediction for Web Service Network Traffic Loads
Author :
Yoas, Daniel W. ; Simco, Greg
Author_Institution :
Ind., Comput., & Eng. Technol., Pennsylvania Coll. of Technol., Williamsport, PA, USA
Abstract :
Businesses have used forecasting to address inventory levels and staffing needs. By understanding long-term utilization of resources, businesses have been able to optimize the costs associated with those resources. To date, computing has used forecasting to address short-term needs for services like scheduling and load balancing. This paper presents a portion of a larger study that was conducted to determine if long-term prediction of a server´s resources is possible. The result of that larger study indicates that server resources exhibit long-term predictability, opening the possibility for future research to improve business use of servers.
Keywords :
Web services; business data processing; resource allocation; scheduling; Web service network; business use; load balancing service; long-term predictability; long-term resource utilization; network traffic load; scheduling service; server resources; Availability; Error analysis; Resource management; Telecommunication traffic; Web servers; Availability; Computer Network Reliability; Computer Performance; Forecasting; Web Services;
Conference_Titel :
Information Technology: New Generations (ITNG), 2014 11th International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4799-3187-3
DOI :
10.1109/ITNG.2014.79