Memory Estimation of Internet Server Using Queuing Theory: Comparative Study between M/G/1, G/M/1 and G/G/1 Queuing Model
How to effectively allocate system resource to process
the Client request by Gateway servers is a challenging problem. In
this paper, we propose an improved scheme for autonomous
performance of Gateway servers under highly dynamic traffic loads.
We devise a methodology to calculate Queue Length and Waiting
Time utilizing Gateway Server information to reduce response time
variance in presence of bursty traffic. The most widespread
contemplation is performance, because Gateway Servers must offer
cost-effective and high-availability services in the elongated period,
thus they have to be scaled to meet the expected load. Performance
measurements can be the base for performance modeling and
prediction. With the help of performance models, the performance
metrics (like buffer estimation, waiting time) can be determined at
the development process. This paper describes the possible queue
models those can be applied in the estimation of queue length to
estimate the final value of the memory size. Both simulation and
experimental studies using synthesized workloads and analysis of
real-world Gateway Servers demonstrate the effectiveness of the
proposed system.
[1] UDDI (2004), "Universal description, discovery, and integration of
business for the web,".
[2] Zari ,Mazen, et. al(2001), "Understanding and Reducing Web delays",
pp. 30-37, IEEE Journal for Electronics and Computer Science, Vol. 34,
No.12.
[3] Mogul ,J. C. (1995), "Operating systems support for busy internet
servers," in Fifth Workshop on
[4] Low , Steven H., Srikant , R. (2002), "A Mathematical Framework for
Designing a Low-Loss, Low-Delay Internet", IEEE Transactions on
Communications.
[5] Chen ,Xiangping, Mohapatra , Prasant (2002), "Performance Evaluation
of Service Differentiating Internet Servers", pp. 1368-1375, Vol. 51, No.
11.
[6] Ying , Lei et. al. (2003), "Global Stability of Internet Congestion
Controllers with Heterogeneous Delays", IEEE Transactions on
Communications.
[7] Barford , P., Crovella ,M. (1998), "Generating representative web
workloads for network and server performance evaluation," in
Measurement and Modeling of Computer Systems, pp. 151-160.
[8] Dr. L.K. Singh, Riktesh Srivastava, "Estimation of Buffer Size of
Internet Gateway Server via G/M/1 Queuing Model" International
Journal of Applied Science, Engineering and Technology, Volume 4
Number 1, pp. 474-482, January 2007.
[9] Hot Topics in Operating Systems(HotOS-V), Orcas Island, WA.
[10] Kleinrock , L. (1976), Queueing Systems, Vol. 2, Applications. John
Wiley Publications, NY.
[11] Menasce , D., Almeida , V. (2001), Capacity Planning for Web Services:
Metrics, Models, and Methods. Prentice Hall PTR.
[12] Lazowska , E. D. et. al(1984), Quantitative system performance:
computer system analysis using queueing network models. Prentice-
Hall, Inc.
[13] Anderson , Darrell et. al.( 1999), "A Case for Buffer Servers", p. 82,
IEEE Seventh Workshop on Hot Topics in Operating Systems.
[14] Roberts , Jim W. (2001), "Traffic Theory and the Internet", IEEE
Transactions on Communications.
[1] UDDI (2004), "Universal description, discovery, and integration of
business for the web,".
[2] Zari ,Mazen, et. al(2001), "Understanding and Reducing Web delays",
pp. 30-37, IEEE Journal for Electronics and Computer Science, Vol. 34,
No.12.
[3] Mogul ,J. C. (1995), "Operating systems support for busy internet
servers," in Fifth Workshop on
[4] Low , Steven H., Srikant , R. (2002), "A Mathematical Framework for
Designing a Low-Loss, Low-Delay Internet", IEEE Transactions on
Communications.
[5] Chen ,Xiangping, Mohapatra , Prasant (2002), "Performance Evaluation
of Service Differentiating Internet Servers", pp. 1368-1375, Vol. 51, No.
11.
[6] Ying , Lei et. al. (2003), "Global Stability of Internet Congestion
Controllers with Heterogeneous Delays", IEEE Transactions on
Communications.
[7] Barford , P., Crovella ,M. (1998), "Generating representative web
workloads for network and server performance evaluation," in
Measurement and Modeling of Computer Systems, pp. 151-160.
[8] Dr. L.K. Singh, Riktesh Srivastava, "Estimation of Buffer Size of
Internet Gateway Server via G/M/1 Queuing Model" International
Journal of Applied Science, Engineering and Technology, Volume 4
Number 1, pp. 474-482, January 2007.
[9] Hot Topics in Operating Systems(HotOS-V), Orcas Island, WA.
[10] Kleinrock , L. (1976), Queueing Systems, Vol. 2, Applications. John
Wiley Publications, NY.
[11] Menasce , D., Almeida , V. (2001), Capacity Planning for Web Services:
Metrics, Models, and Methods. Prentice Hall PTR.
[12] Lazowska , E. D. et. al(1984), Quantitative system performance:
computer system analysis using queueing network models. Prentice-
Hall, Inc.
[13] Anderson , Darrell et. al.( 1999), "A Case for Buffer Servers", p. 82,
IEEE Seventh Workshop on Hot Topics in Operating Systems.
[14] Roberts , Jim W. (2001), "Traffic Theory and the Internet", IEEE
Transactions on Communications.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:50012", author = "L. K. Singh and Riktesh Srivastava", title = "Memory Estimation of Internet Server Using Queuing Theory: Comparative Study between M/G/1, G/M/1 and G/G/1 Queuing Model", abstract = "How to effectively allocate system resource to process
the Client request by Gateway servers is a challenging problem. In
this paper, we propose an improved scheme for autonomous
performance of Gateway servers under highly dynamic traffic loads.
We devise a methodology to calculate Queue Length and Waiting
Time utilizing Gateway Server information to reduce response time
variance in presence of bursty traffic. The most widespread
contemplation is performance, because Gateway Servers must offer
cost-effective and high-availability services in the elongated period,
thus they have to be scaled to meet the expected load. Performance
measurements can be the base for performance modeling and
prediction. With the help of performance models, the performance
metrics (like buffer estimation, waiting time) can be determined at
the development process. This paper describes the possible queue
models those can be applied in the estimation of queue length to
estimate the final value of the memory size. Both simulation and
experimental studies using synthesized workloads and analysis of
real-world Gateway Servers demonstrate the effectiveness of the
proposed system.", keywords = "M/M/1, M/G/1, G/M/1, G/G/1, Gateway Servers,
Buffer Estimation, Waiting Time, Queuing Process.", volume = "1", number = "9", pages = "406-5", }