A User-Oriented Intelligent Access Selection Algorithm in Heterogeneous Wireless Networks

Liang, Gen; Guo, Xiaoxue; Fang, Jingcheng

doi:10.1155/2020/8828355

Cited by 9 publications

(6 citation statements)

References 39 publications

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“…Consumers and network equipment on portable and rural networks consume 57 percent of the energy consumed by the ICT industry [16]. The fast growth of power usage by users and system equipment has generated important difficulties [17] and the researchers are working hard to maintain customer experience, speed, and flexibility [18].…”

Section: Literature Reviewmentioning

confidence: 99%

Efficient Network Selection Using Multi-Depot Routing Problem for Smart Cities

Shanthakumari¹,

Nam²,

Nam³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Smart cities make use of a variety of smart technology to improve societies in better ways. Such intelligent technologies, on the other hand, pose significant concerns in terms of power usage and emission of carbons. The suggested study is focused on technological networks for big data-driven systems. With the support of software-defined technologies, a transportation-aided multicast routing system is suggested. By using public transportation as another communication platform in a smart city, network communication is enhanced. The primary objective is to use as little energy as possible while delivering as much data as possible. The Attribute Decision Making with Capacitated Vehicle (CV) Routing Problem (RP) and Half Open Multi-Depot Heterogeneous Vehicle Routing Problem is used in the proposed research. For the optimum network selection, a Multi-Attribute Decision Making (MADM) method is utilized. For the sake of reducing energy usage, the Capacitated Vehicle Routing Problem (CVRP) is employed. To reduce the transportation cost and risk, Half Open Multi-Depot Heterogeneous Vehicle Routing Problem is used. Moreover, a mixed-integer programming approach is used to deal with the problem. To produce Pareto optimal solutions, an intelligent algorithm based on the epsilon constraint approach and genetic algorithm is created. A scenario of Auckland Transport is being used to validate the concept of offloading the information onto the buses for energy-efficient and delay-tolerant data transfer. Therefore the experiments have demonstrated that the buses may be used effectively to carry out the data by customer requests while using 30% of less energy than the other systems.

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Section: Literature Reviewmentioning

confidence: 99%

Efficient Network Selection Using Multi-Depot Routing Problem for Smart Cities

Shanthakumari¹,

Nam²,

Nam³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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“…Assignment of weights and applications were not taken speci cally in this paper. An access selection algorithm was proposed [21]. In order to maximize the transmission rate of a wireless network, an optimal value of bandwidth should be allocated to users.…”

Section: Background and Related Workmentioning

confidence: 99%

Switching of Interfaces and Self-optimization of weights using Backpropagation ANN in WHN Enviornment

Rani

2023

Preprint

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In today’s scenario, mobile communication is facing a healthy competition due to different networks, interfaces, channels, and many more available in wireless heterogeneous environment. The problem arises when customers/users get the availability of many interfaces at the same time. At that time users need an intelligent or smart mechanism to connect them to the best services according to their requirements/preferences. Interface management manages available interfaces and connects the user with the best. In this paper, Interface management with Artificial Neural Network (ANN) allows the smart use of different radio accesses/interfaces. The selection is made with different parameters of different networks. This paper proposed a backpropagation neural network that is used for the switching in between different networks-3G, WLAN, 4G and 5G. The different parameters of a network are used as the selection parameters with assigning proper weights. Weights are initialized with fuzzy AHP and optimized with Back Propagation Neural Network (BPNN). The target value and the actual value is compared and their difference used as the adjusting value for the weights to get the optimum value. The backpropagation is used to train the network. The comparison among the projected algorithm and the existing algorithm shows the valuablity of the new method and the best connectivity of the network.

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“…To satisfy the served users by a reasonable degree, utility theory represents the values of the attributes. Describing a criterion's effect on a single application type by a suited utility function is presented in many studies [37,38].…”

Section: Scoring Candidate Networkmentioning

confidence: 99%

An adaptive optimized handover decision model for heterogeneous networks

Ezz-Eldien,

Abdel-Atty,

Abdalla

et al. 2023

PLoS ONE

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A heterogeneous network (HetNet), combining different technologies, is considered a promising solution adopted by several upcoming generations of mobile networks to keep up with the rapid development of mobile users’ requirements while improving network performance. In this scenario, a vertical handover (VHO) algorithm is responsible for ensuring the continuity of the ongoing user connection while moving within the coverage of the HetNet. Although various VHO algorithms were proposed, achieving efficient performance from both network and user perspectives remains challenging. This paper proposes an adaptive optimized vertical handover algorithm based on a multi-attribute decision-making (MADM) algorithm integrated with particle swarm optimization and gravitational search algorithm (PSOGSA) as a framework to implement the handover process. The algorithm includes three main ideas. Firstly, a network selection framework is proposed considering the most important criteria, including signal strength and other networks’ attributes, along with users’ characteristics regarding their mobility and service preferences. Secondly, two new parameters are introduced as control handover parameters named load factor (LF) and score priority (SP) to reduce unnecessary handovers and the overall HetNet power consumption while achieving balanced load distribution. Lastly, the desired aims are formulated as an objective function, then the PSOGSA algorithm is used to reach the optimal values of both LF and SP, which will be considered when executing the handover algorithm. The presented algorithm is simulated in a heterogeneous wireless network where the fifth-generation (5G) wireless technology coexists with other radio access networks to improve the evaluation field of the proposed algorithm. Also, the proposed algorithm’s performance is evaluated in the case of using various MADM algorithms. The simulation results show that the proposed adaptive optimized approach attains efficient performance by decreasing unnecessary handovers by more than 40% and achieving much better load distribution by around 20% to 40%, outperforming traditional handover approaches.

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A User-Oriented Intelligent Access Selection Algorithm in Heterogeneous Wireless Networks

Cited by 9 publications

References 39 publications

Efficient Network Selection Using Multi-Depot Routing Problem for Smart Cities

Efficient Network Selection Using Multi-Depot Routing Problem for Smart Cities

Switching of Interfaces and Self-optimization of weights using Backpropagation ANN in WHN Enviornment

An adaptive optimized handover decision model for heterogeneous networks

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