Network Selection in Heterogeneous Wireless Systems using GRA Method
Unknown authors
Abstract
In heterogeneous wireless networks, connection choosing relates to the method for automatically determining the most suitable one among a variety of readily accessible alternatives according to features including quality of signal, connectivity, and preferences of users. The network choice with heterogeneous wireless systems includes the procedure for choosing a suitable system from an array of available alternatives, taking into consideration variables that include signal quality, bandwidth, and customer preferences, in order to guarantee ideal interaction as well as efficiency for wireless gadgets in a variety of environments. This is a dynamic choice that seeks to maximize the user experience by replying to shifting network situations and demands. Network selection study for heterogeneous wireless systems is crucial since it boosts wireless transmission by means of sophisticated algorithms, enhancing effectiveness, dependability, and overall performance while tackling obstacles from diverse technologies alongside rising connectivity demands, thus improving consumers along with allowing innovations in the Internet of Things and 5G wireless networks. The GRA (Grey Relational Analysis) is a decision-making tool which assesses the value of many variables in a grey structure, helping in the selection of the most appropriate alternative. In accordance with grey system theory, method examines reference and comparison sequences employing grey relational parameters, permitting impartial rankings especially supporting difficult decisions in the fields of engineering, leadership, and economics. The Evaluation parameters are Bandwidth, Jitter, Delay and Cost. Alternate parameter is Wi-Fi. For the analysis, the final rank is where “Wi-Fi 1” is in the 1st rank, “Wi-Fi 3”is in the 2nd rank, “Wi-Fi 4” is in the 3rd rank, “Wi-Fi 2” is in the 4th rank, and “Wi-Fi 5” is in the 5th rank. The best one is “Wi-Fi 1” which holds up the 1st rank.