Load Balancing in Heterogeneous Network with SDN: A Survey

Li, Jingbo; Ma, Li; Fu, Yingxun; Ma, Di; Xiao, Ailing

doi:10.1007/978-981-16-8174-5_19

Cited by 2 publications

(1 citation statement)

References 20 publications

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“…When the temperature drops, the system gradually tends to balance to find the optimal solution. According to the Metropolis criterion [33] for judging whether the new solution is the optimal solution, the criterion is shown in equation (5).…”

Section: Discussionmentioning

confidence: 99%

Multi-objective optimization of process parameters for ultrasonic rolling extrusion of 42CrMo material

Wang

et al. 2023

Mechanics & Industry

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To choose the most suitable method to solve the process parameter optimization of ultrasonic rolling extrusion, the 42CrMo material was taken as the research object. Based on a four-factor five-level orthogonal experiment, the response surface method was used to establish prediction models of the surface roughness, surface residual stress, and work hardening degree. To obtain better Pareto front, resulting in better distribution and convergence of the solution set, the simulated annealing algorithm, particle swarm optimization, second-generation non-dominated sorting genetic algorithm and multi-island genetic algorithm were used to optimize the parameters of ultrasonic rolling extrusion. Comparing the optimization effect with the calculation efficiency, the simulated annealing algorithm is finally selected as the optimization method of the ultrasonic rolling extrusion process parameters, and the optimization parameter domain of the ultrasonic rolling extrusion process is obtained. The optimization model was tested and verified. The results showed that the best optimization effect was achieved after 3000 iterations, and the maximum relative error of the experimental and calculated values for the surface roughness, work hardening degree and residual stress of the optimized 42CrMo material after ultrasonic rolling was controlled within 5%. The established multi-objective optimization model has high accuracy and application value, can realize the optimization of ultrasonic rolling extrusion process parameters.

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Section: Discussionmentioning

confidence: 99%

Multi-objective optimization of process parameters for ultrasonic rolling extrusion of 42CrMo material

Wang

et al. 2023

Mechanics & Industry

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Machine Learning-Based Load Balancing Algorithms in Future Heterogeneous Networks: A Survey

et al. 2022

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The massive growth of mobile users and the essential need for high communication service quality necessitate the deployment of ultra-dense heterogeneous networks (HetNets) consisting of macro, micro, pico and femto cells. Each cell type provides different cell coverage and distinct system capacity in HetNets. This leads to the pressing need to balance loads between cells, especially with the random distribution of users in numerous mobility directions. This paper provides a survey on the intelligent load balancing models that have been developed in HetNets, including those based on the machine learning (ML) technology. The survey provides a guideline and a roadmap for developing cost-effective, flexible and intelligent load balancing models in future HetNets. An overview of the generic problem of load balancing is also presented. The concept of load balancing is first introduced, and its purpose, functionality and evaluation criteria are then explained. Besides, a basic load balancing model and its operational procedure are described. A comprehensive literature review is then conducted, including techniques and solutions of addressing the load balancing problem. The key performance indicators (KPIs) used in the evaluation of load balancing models in HetNets are presented, along with the concurrent optimisation of coverage (CCO) and mobility robustness optimisation (MRO) relationship of load balancing. A comprehensive literature review of ML-driven load balancing solutions is specifically accomplished to show the historical development of load balancing models. Finally, the current challenges in implementing these models are explained as well as the future operational aspects of load balancing.

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Load Balancing in Heterogeneous Network with SDN: A Survey

Cited by 2 publications

References 20 publications

Multi-objective optimization of process parameters for ultrasonic rolling extrusion of 42CrMo material

Multi-objective optimization of process parameters for ultrasonic rolling extrusion of 42CrMo material

Machine Learning-Based Load Balancing Algorithms in Future Heterogeneous Networks: A Survey

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