Wireless LAN Service Quality Optimization in Academic Environments

Abstract

This paper targets optimized service quality (SQ) -a metric that compares the perceived performance by users with the expected performance -sufficient to satisfy users' quality of experience (QoE). The perceived performance was obtained in a field survey from an academic environment, and using Interval Type-2 Fuzzy Logic (IT2FL), uncertainties inherent in the field data were efficiently modeled for accurate estimation of the SQ. To obtain the expected performance, two unsupervised tools: the Principal Component Analysis (PCA) and Self-organizing Map (SOM) were exploited to abstract the most relevant features, and observe similarity patterns between the abstract features. An Adaptive Neuro-Fuzzy Inference System (ANFIS) was then used to optimize the system performance. Results obtained showed that ANFIS sufficiently optimized and modeled the SQ -as the root mean square error (RMSE) values of the train and test data were approximately the same -for all the study sites considered. However, combining the three campuses produced the least mean absolute error (MAE) of 0.0979 for train data, and the highest MAE of 0.7345 for test data. Further, the least MAE of 0.4707 for test data was obtained from town campus Annex. The wide variation in MAE observed in the train and test data might not be unconnected with the high degree of uncertainties associated with interference, site topology and terrain issues -exhibited by the system under study, as well as the quality of data collected. The proposed system framework has the potentials to develop into a complete location-based system.

Optimization of Intelligent Tuning System for Stringed Instruments Based on Wireless Sensor Network

“…The main purpose of network layer protocol in wireless sensor network system is path design and maintenance. Network layer protocol is one of the important factors restricting the performance of wireless sensor network [14]. The performance of a wireless sensor network is closely related to the network layer protocol of the wireless sensor network, and the stability, robustness, redundancy, and power consumption of the whole system are closely related to the network layer protocol.…”