Mohammad Saraireh

ARMA model order and parameter estimation using genetic algorithms

A new method for simultaneously determining the order and the parameters of autoregressive moving average (ARMA) models is presented in this article. Given an ARMA (p, q) model in the absence of any information for the order, the correct order of the model (p, q) as well as the correct parameters will be simultaneously determined using genetic algorithms (GAs). These algorithms simply search the order and the parameter spaces to detect their correct values using the GA operators. The proposed method works on the principle of maximizing the GA fitness value relying on the deviation between the actual plant output, with or without an additive noise, and the estimated plant output. Simulation results show in detail the efficiency of the proposed approach. In addition to that, a practical model identification and parameter estimation is conducted in this article with results obtained as desired. The new method is compared with other well-known methods for ARMA model order and parameter estimation.

A Novel Quality of Service Assessment of Multimedia Traffic over Wireless Ad Hoc Networks

With the extensive growth of the Internet, wireless technology, and multimedia applications, quality of service (QoS) monitoring and measurement of the networks have become important. Network measurements are carried out to obtain information about important QoS parameters such as delay, loss and jitter. Each type of multimedia applications has its own requirements and limits on these parameters. To evaluate the QoS of multimedia applications transmitted over wireless networks, a fuzzy logic assessment system has been developed. The system showed how the end-to-end QoS could be measured without the necessity for complex mathematical models. The measured QoS were classified into three categories Good, Average, and Poor regions. In addition, and based on the proposed system, the distributions and the overall QoS were estimated. The results indicated that the measured QoS was a good indication of the network conditions and resource availability.

Assessment and improvement of quality of service in wireless networks using fuzzy and hybrid genetic-fuzzy approaches

Fuzzy and hybrid genetic-fuzzy approaches were used to assess and improve quality of service (QoS) in simulated wireless networks. Three real-time audio and video applications were transmitted over the networks. The QoS provided by the networks for each application was quantitatively assessed using a fuzzy inference system (FIS). Two methods to improve the networks’ QoS were developed. One method was based on a FIS mechanism and the other used a hybrid genetic-fuzzy system. Both methods determined an optimised value for the minimum contention window (CWmin) in IEEE 802.11 medium access control (MAC) protocol. CWmin affects the time period a wireless station waits before it transmits a packet and thus its value influences QoS. The average QoS for the audio and video applications improved by 42.8% and 14.5% respectively by using the FIS method. The hybrid genetic-fuzzy system improved the average QoS for the audio and video applications by 35.7% and 16.5% respectively. The study indicated that the devised methods were effective in assessing and significantly improving QoS in wireless networks.

A robust and efficient genetic algorithm for solving a chemical reactor problem: theory, application and convergence analysis

Solution of the chemical reactor problem, as an optimal control problem, using continuous genetic algorithms (CGAs) is presented in this paper. The proposed approach overcomes the drawbacks of the traditional approaches in terms of lack of efficiency, lack of accuracy and lack of robustness. The solution is based on the value of the performance index and the final system state constraints. Simulation results show clearly that the new technique outperforms the existing direct and indirect methods. Based on the convergence analysis, the solution of the optimal control problem is achieved without any limitation on the nature of the problem and regardless of the CGA tuning parameters.

A Comparative Study of IEEE 802.11 MAC Access Mechanisms for Different Traffic Types

The fast growth and development of wireless computer networks and multimedia applications make the Quality of Service (QoS) provided to their transmission an important issue. This paper aims to investigate the impact of varying the number of active stations on the network performance. This was carried out using different data rates. The investigations also considered both MAC protocol access mechanisms, i.e. the basic access and the Request To Send / Clear To Send (RTS/CTS). The effect of traffic type i.e. Constant Bit Rate (CBR) and Variable Bit Rate (VBR) traffics was also examined. The findings revealed that in large networks (larger than 15 stations), the RTS/CTS access mechanism outperformed the basic access mechanism since the performance of the latter was more sensitive to the increase and decrease of the number of active stations. Increasing the data rate improved the network performance in term of delay and jitter but it degraded the network performance in term of channel utilisation and packet loss ratio.