Using Long-Term Prediction for Web Service Network Traffic Loads.

Daniel W. Yoas; Gregory Simco

doi:10.1109/itng.2014.79

Using Long-Term Prediction for Web Service Network Traffic Loads.

Daniel W. Yoas
, Gregory Simco

Research output: Contribution to conference › Presentation

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.

Original language	American English
Pages	21-26
Number of pages	6
DOIs	https://doi.org/10.1109/itng.2014.79
State	Published - Apr 9 2014
Event	ITNG '14 Proceedings of the 2014 11th International Conference on Information Technology New Generations - Duration: Apr 9 2014 → …

Conference

Conference	ITNG '14 Proceedings of the 2014 11th International Conference on Information Technology New Generations
Period	4/9/14 → …

ASJC Scopus Subject Areas

Information Systems

Keywords

Computer Network Reliability
Computer Performance
Error analysis
Forecasting
Telecommunication traffic
Web Services
business data procession
resource allocation
scheduling
Availability

Disciplines

Computer Sciences

Access to Document

10.1109/itng.2014.79

Cite this

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title = "Using Long-Term Prediction for Web Service Network Traffic Loads.",

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.",

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doi = "10.1109/itng.2014.79",

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AU - Simco, Gregory

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N2 - 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.

AB - 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.

KW - Computer Network Reliability

KW - Computer Performance

KW - Error analysis

KW - Forecasting

KW - Telecommunication traffic

KW - Web Services

KW - business data procession

KW - resource allocation

KW - scheduling

KW - Availability

UR - https://nsuworks.nova.edu/gscis_facpres/39

UR - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6822170

U2 - 10.1109/itng.2014.79

DO - 10.1109/itng.2014.79

M3 - Presentation

SP - 21

EP - 26

T2 - ITNG '14 Proceedings of the 2014 11th International Conference on Information Technology New Generations

Y2 - 9 April 2014

ER -

Using Long-Term Prediction for Web Service Network Traffic Loads.

Abstract

Conference

ASJC Scopus Subject Areas

Keywords

Disciplines

Access to Document

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Cite this