KEYWORDS: Switching, Received signal strength, Matrices, Switches, Signal intensity, Telecommunication networks, Detection and tracking algorithms, Signal attenuation, Decision making, Chromium
The research on network switching technology is of great significance for seamless roaming of various terminals in heterogeneous wireless networks (HWNs). A personalized vertical handover decision algorithm considering terminal preferences in high-density access environments is proposed to address the dynamic characteristics of the network and the diverse needs of users. Based on the characteristics of the network, the algorithm maximizes the advantages of each network during high-density access, connecting more terminals to available networks with large connections as much as possible. In addition, criteria such as energy consumption and cost are selected to ensure terminal preferences, and a multi criteria decision making (MCDM) problem is constructed. The Analytic Hierarchy Process (AHP) is used to establish a judgment matrix, Determine the weights of each judgment criterion and ultimately select the network through utility function decision-making. The test results show that compared with the AHP based vertical switching algorithm, this algorithm eliminates the burden of networks and comprehensively considers terminal usage preferences during the pre screening stage. It can more accurately, fairly, and stably select the target switching network, reduce blocking rates and switching times, and more effectively improve the quality of user experience.
With the rapid and in-depth integration of various emerging wireless technologies into all walks of life, the massive terminals in the "Internet of Everything" carry diversified business and bring higher requirements for users' network service experience. How to provide users with personalized services and improve users' experience and satisfaction in the dynamic network environment formed by terminal mobility and network state variability is the key to network switching research.For dense terminal scenarios, in order to avoid frequent network selection caused by network congestion and network load jitter caused by blind switching of dense terminals, a load prediction vertical switching algorithm based on GA optimization is proposed. Firstly, the probability of load state space is predicted by the Markov chain, and the predicted probability is mapped to the network load trend value by the load trend function. Then, the load trend value and important network parameters are used as the decision criterion, and the cost function is established to make a comprehensive decision so as to complete the network switching reasonably and accurately. A genetic Algorithm (GA) was introduced to optimize the weights of the decision criteria, and the optimal weight combination was obtained to minimize the switching times. Simulation results show that the proposed algorithm can effectively balance the load between networks, meet the needs of users with less switching, improve the ping-pong effect, reduce the blocking rate, and finally, effectively improve the quality of user experience.
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