TY - GEN
T1 - A client-based QoS approach using generalized extreme value theorem in multi-hop network environments
AU - Kamel, Ammar
AU - Al-Fuqaha, Ala
AU - Benhaddou, Driss
PY - 2012
Y1 - 2012
N2 - Client-side QoS monitoring allows mobile clients to participate in the service evaluation process. Through this approach, mobile clients play proactive role to collect and measure network parameters (e.g., delay, bandwidth) and report any potential service degradation back to the service providers. Adopting this model provides a major enhancement to the service evaluation process by allowing service providers to tune their network resources for a better service performance. In this paper, we present a novel approach that evaluates service performance through collecting service measurements from mobile clients (MCs) in a multi-hop network environment. The proposed approach utilizes a System of Linear Equations (SLE) and Generalized Extreme Value Theorem (GEV) techniques to predict network link performance degradation by estimating the delay extremes on each hop of a given network topology. Consequently, service performance can be evaluated and improved through a continuous assessment process of the network's links behavior over time. Our experimental analysis indicates that our proposed approach provides better prediction of the link delays.
AB - Client-side QoS monitoring allows mobile clients to participate in the service evaluation process. Through this approach, mobile clients play proactive role to collect and measure network parameters (e.g., delay, bandwidth) and report any potential service degradation back to the service providers. Adopting this model provides a major enhancement to the service evaluation process by allowing service providers to tune their network resources for a better service performance. In this paper, we present a novel approach that evaluates service performance through collecting service measurements from mobile clients (MCs) in a multi-hop network environment. The proposed approach utilizes a System of Linear Equations (SLE) and Generalized Extreme Value Theorem (GEV) techniques to predict network link performance degradation by estimating the delay extremes on each hop of a given network topology. Consequently, service performance can be evaluated and improved through a continuous assessment process of the network's links behavior over time. Our experimental analysis indicates that our proposed approach provides better prediction of the link delays.
KW - Client-Based Quality of Service
KW - Extreme Values
KW - Generalized Extreme Value
UR - http://www.scopus.com/inward/record.url?scp=84867386091&partnerID=8YFLogxK
U2 - 10.1109/ICCITechnol.2012.6285813
DO - 10.1109/ICCITechnol.2012.6285813
M3 - Conference contribution
AN - SCOPUS:84867386091
SN - 9781467319508
T3 - International Conference on Communications and Information Technology - Proceedings
SP - 302
EP - 307
BT - 2012 International Conference on Communications and Information Technology, ICCIT 2012
T2 - 2012 International Conference on Communications and Information Technology, ICCIT 2012
Y2 - 26 June 2012 through 28 June 2012
ER -