• Title of article

    Environment Specific TCP Upstream Throughput Models in IEEE802.11b WLAN.

  • Author/Authors

    oghogho, i delta state university - department of electrical/electronic engineering, Abraka, Nigeria

  • From page
    739
  • To page
    746
  • Abstract
    This paper presents our study on environment based dependence of TCP Upstream Throughput (TCP_upT) on signal to noise ratio (SNR) for a single user in an IEEE 802.11b Wireless Local Area Network (WLAN). Small offices, open corridors and free space environments were studied using an infrastructure based network for different quality of service (QoS) traffic. Environment based Models that predict TCP_upT directly from SNR for different signal categories were statistically generated, validated and compared with similar models that were earlier developed without considering specific environments. The first type of models developed in this work were developed from all data specifically collected from each environment while the second type of models were developed by first categorizing the data in each specific environment into different signal categories and then models were statistically generated for each signal category before combining them into one model equation. At the stated levels of significance and the different degrees of freedom, the developed models were accepted at 1% (for F test) and 0.5% (for T test). From the RMS errors computed, the specific environment based models developed in this work were more accurate (as they showed lower RMS errors compared with earlier similar models) in predicting TCP_upT in IEEE 802.11b WLAN for a single user on the network. It was also observed that the second type of models were found to be more accurate having shown lower RMS errors.
  • Keywords
    TCP Upstream throughput , Signal to noise ratio , environment based empirical model , IEEE802.11b , WLANs
  • Journal title
    Journal of Applied Sciences and Environmental Management
  • Journal title
    Journal of Applied Sciences and Environmental Management
  • Record number

    2728545