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