@article{MAKHILLAJIT20141315791,
    title = {Optimal Heterogeneous Network Selection Based on Estimation of Network Quality Factor (NQF)},
    journal = {Asian Journal of Information Technology},
    volume = {13},
    number = {1},
    pages = {1-10},
    year = {2014},
    issn = {1682-3915},
    doi = {ajit.2014.1.10},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2014.1.10},
    author = {Bhuvaneswari and},
    keywords = {QoS,heterogeneous network,network quality factor,user satisfation factor,call blocking probability,recent call history},
    abstract = {The paradigm shift from fixed homogeneous network to mobile 
  heterogeneous network for mobile multimedia applications with QoS (Quality of 
  Service) is growing enormously. The main QoS parameters for mobile multimedia 
  application are high bandwidth and low delay. To achieve satisfactory service 
  delivery for mobile multimedia applications in heterogeneous network, the above 
  mentioned QoS parameter is to be met. Provision of such services in heterogeneous 
  environment invites many research issues. One of the main challenge is the selection 
  of optimal network with QoS since current QoS schemes have two drawbacks such 
  as unawareness of the heterogeneous wireless environment and inefficient utilization 
  of the reserved bandwidth. To solve these problems, we present a novel QoS parameter 
  namely Network Quality Factor (NQF) to estimate the network status. NQF is evaluated 
  by estimating the Call blocking probability (Cbp) of heterogeneous network from 
  its ‘rch’ (recent call history). The estimation of ‘rch’ 
  parameter and Cbp avoids unnecessary hand-off and enhances the effective bandwidth 
  utilization of a cellular network under heavy load condition. The predicted 
  ‘rch’ parameter of a network is then mapped in the proposed QoS mapper 
  sub-module present in QoS broker module to select an optimum network. The network 
  with higher NQF is always termed as optimum network as it has low Cbp and it 
  is always selected. A Bayesian Network Model is assumed for Cbp estimation and 
  simulated using Monte-Carlo Method over various heterogeneous environment conditions. 
  The estimated NQF is then mapped with User Satisfaction Factor (USF) to select 
  the most suitable access network for each session. The modeling and simulation 
  results demonstrate that the NQF based optimum network selection can satisfy 
  user’s QoS requirement and obtain a more efficient use of the scarce wireless 
  bandwidth during heavy traffic load condition.}
    }