Research On Network Selection Algorithm Of Multi-Connection

The advent of the information age has brought disruptive effects to people’s lives,with innovative technologies such as cloud computing,big data and blockchain bring better service experience to users.The proliferation of user data traffic,the widespread popularity of terminal devices and the differentiated QoS needs of users also pose huge challenges to current communication networks,thus requiring the convergence of multiple standard networks to promote an "interoperable" system.In order to achieve seamless roaming among heterogeneous networks,network selection algorithms have become a hot research topic in heterogeneous network convergence.Excellent network selection algorithms can ensure reasonable allocation of wireless resources and effectively improve user satisfaction.This paper discusses the commonly used heterogeneous wireless network selection techniques and analyzes the characteristics and limitations of different network selection algorithms.To address the problems of existing network selection algorithms,two improved network selection algorithms are proposed on the basis of the original algorithms,and the performance of the algorithms is verified by simulation.In order to solve the problem of joint resource scheduling in different network standards,a Step Adaptive Firefly Algorithm Based on Cubic Chaotic Mapping(SACM-FA)is proposed in this paper.The algorithm integrates the firefly algorithm with chaotic optimization theory,uses chaotic sequences to randomly generate the initial positions of fireflies to ensure the randomness of the initial individuals,and introduces adaptive search step factor to enhance the diversity of the population to perform the optimal search operation under the condition of satisfying the user QoS guarantee,and iterates several times to arrive at the best allocation scheme to allocate wireless resources for users.The SACM-FA algorithm optimizes the bandwidth allocation and power control problems in the eLWA uplink environment where multiple service types coexist,and improves user utility and user satisfaction.The final simulation results show that the SACM-FA algorithm can improve the throughput of the wireless system and effectively improve the network performance in the eLWA system with multiple service coexistence.Compared to the traditional network selection algorithm,the improved algorithm can effectively balance the network load and significantly improve the user satisfaction.Meanwhile,for the classical TOPSIS algorithm’s unreasonable closeness calculation and inverse order problem,this paper proposes a network selection access algorithm(AE-GTOPSIS)based on gray correlation degree and joint subject-objective assignment.The algorithm adopts a joint subject-objective weighting method combining the AHP method and the entropy method instead of the traditional single weighting method,and takes into account the complexity of the algorithm and the rationality of the weight assignment.It also introduces the gray correlation degree to improve the traditional TOPSIS algorithm,and uses the gray correlation degree and Euclidean distance to jointly construct a new relative closeness,and uses the relative closeness as a criterion to judge the superiority of the solution and rank the candidate networks.The simulation results show that,compared with the single weighting method,the combined subject-objective weighting method can reasonably assign the attribute weights considering the importance of the attributes.At the same time,compared with the classical selection algorithm,the AE-GTOPSIS algorithm proposed in this paper can effectively reduce the number of network vertical switching,alleviate the negative impact of frequent network switching on user perception,provide stable and reliable network connection while safeguarding user QoS requirements,and improve user satisfaction.