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701
Service chain deployment algorithms for deterministic end-to-end delay upper bound
Published 2021-11-01“…To solve the problem that the current service chain deployment algorithms cannot guarantee the delay of each packet passing through the service chain (SC), a SC deployment algorithm for deterministic end-to-end delay upper bound was proposed.First, the end-to-end delay bound of the SC was derived based on network calculus.Then, the deterministic end-to-end delay bound of the SC was achieved by collaboratively optimizing the routing of SC and the resource allocation of the virtual network function nodes in the SC.The experimental results show that the proposed algorithm can effectively improve the volume of accepted SC while guaranteeing that the end-to-end delay of each packet satisfies the delay requirements.…”
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702
Fair and efficient opportunistic interference alignment algorithm based on round-robin scheduling
Published 2017-10-01“…Opportunistic interference alignment (OIA) algorithm was proposed for the practical implementation of interference alignment (IA).A fair and efficient OIA algorithm was presented for the unfairness in resource allocation and high dependence of tremendous users in the existing OIA algorithms.Firstly,the users with the best channel was selected in the primary cell based on round-robin scheduling after the coordinate cluster was determined.Then,the interference from the primary users was eliminated by skillfully designing the useful signal spaces in the subordinate cells.Furthermore,the users with the minimum interference leakage was selected in the subordinate cells.Finally,the fairness performance was theoretically analyzed.Simulation results show that both the sum-rate and fairness of the proposed algorithm are significantly higher than that of the conventional algorithm with less interference leakage.Besides,the users can achieve a quick access.…”
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703
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704
Joint beam hopping and coverage control optimization algorithm for multibeam satellite system
Published 2023-04-01“…To improve the performance of multibeam satellite (MBS) systems, a deep reinforcement learning-based algorithm to jointly optimize the beam hopping and coverage control (BHCC) algorithm for MBS was proposed.Firstly, the resource allocation problem in MBS was transformed to a multi-objective optimization problem with the objective maximizing the system throughput and minimizing the packet loss rate of the MBS.Secondly, the MBS environment was characterized as a multi-dimensional matrix, and the objective problem was modelled as a Markov decision process considering stochastic communication requirements.Finally, the objective problem was solved by combining the powerful feature extraction and learning capabilities of deep reinforcement learning.In addition, a single-intelligence polling multiplexing mechanism was proposed to reduce the search space and convergence difficulty and accelerate the training of BHCC.Compared with the genetic algorithm, the simulation results show that BHCC improves the throughput of MBS and reduces the packet loss rate of the system, greedy algorithm, and random algorithm.Besides, BHCC performs better in different communication scenarios compared with a deep reinforcement learning algorithm, which do not consider the adaptive beam coverage.…”
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705
Comparative Performance Evaluation of Scheduling Algorithms using 5G‑Air‑Simulator
Published 2025-05-01“…With the spread of new applications, efficient scheduling algorithms are mandatory to handle the allocation of the limited spectrum resources to various types of traffic and to guarantee the requirements of the quality of service and the quality of experience informed by users. …”
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706
A New Multiobjective A∗ Algorithm With Time Window Applied to Large Airports
Published 2024-01-01“…This study proposes a multiobjective A∗ algorithm with time windows which takes into account the allocation of resources on airport taxiways and introduces factors such as turning angles, dynamic turning speeds, and dynamic characteristics of the ground operations. …”
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707
The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm
Published 2021-01-01“…The decision tree mining algorithm can classify the data, grasp the teaching process of the teacher, and analyze the overall performance of the students, so as to realize the dynamic management of the educational administration and help the educational administration personnel to make the right decision, with more reasonable allocation of resources. …”
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708
Parallel CUDA-Based Optimization of the Intersection Calculation Process in the Greiner–Hormann Algorithm
Published 2025-03-01Get full text
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709
New Courteous Algorithm for Uplink Scheduling in LTE-Advanced and 5G Networks
Published 2020-01-01Get full text
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710
Clustering of High School Students Academic Scores Using K-Means Algorithm
Published 2025-03-01“…Additionally, clustering outcomes provide valuable insights for refining teaching strategies, allocating resources more effectively, and personalizing learning approaches to suit each student's needs. …”
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711
Routing algorithm for heterogeneous computing force requests based on computing first network
Published 2025-02-01“…Due to the particularity and uniqueness of computing force requests, how to find an effective path set with non-intersecting transmission links for a group of heterogeneous computing force requests, so that the group of requests can reach their respective destination computing force nodes, and thus allocate computing force resources for the group of requests, is a key issue facing current computing first networks. …”
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712
Algorithms to Identify Copied and Manipulated Spectrum Occupancy Data in Cognitive Radio Networks
Published 2025-01-01“…Spectrum Access Systems (SASs) and similar systems coordinate access to shared radio frequency bands to efficiently allocate the use of spectrum between users in a locality. …”
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713
Economic operation analysis of the power grid combining communication network and distributed optimization algorithm
Published 2025-05-01“…It is necessary to strengthen communication and resource allocation in practical applications.…”
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714
Network media streaming offloading algorithm based on QoE in mobile edge network
Published 2024-02-01“…Aiming at the problems of high-latency, high energy consumption, high bandwidth, and poor quality of experience (QoE) caused by emerging network media streaming business in mobile edge computing, a computing offloading algorithm based on QoE feedback configuration was proposed.Firstly, both preprocessing and priority were comprehensively considered to maximize network resource utilization.Meanwhile, different weights were assigned to the computation tasks for establishing a resource allocation relationship.Secondly, after comprehensively taking into account deadline, computing resource, power and bandwidth constraint, an QoE model was established where the optimization objective was the weighted sum of task delay, energy consumption and precision, and the method of Lagrange multipliers was utilized to solve the established model.Simulation results indicate that, compared with the deep reinforcement learning-based online offloading algorithm, the proposed algorithm can effectively optimize the resource allocation and better improve the QoE.…”
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715
An Integrated Implementation Framework for Warehouse 4.0 Based on Inbound and Outbound Operations
Published 2025-07-01“…First, for inbound processes, an algorithm-driven storage allocation model is proposed to solve stacker crane scheduling problems. …”
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716
Network media streaming offloading algorithm based on QoE in mobile edge network
Published 2024-02-01“…Aiming at the problems of high-latency, high energy consumption, high bandwidth, and poor quality of experience (QoE) caused by emerging network media streaming business in mobile edge computing, a computing offloading algorithm based on QoE feedback configuration was proposed.Firstly, both preprocessing and priority were comprehensively considered to maximize network resource utilization.Meanwhile, different weights were assigned to the computation tasks for establishing a resource allocation relationship.Secondly, after comprehensively taking into account deadline, computing resource, power and bandwidth constraint, an QoE model was established where the optimization objective was the weighted sum of task delay, energy consumption and precision, and the method of Lagrange multipliers was utilized to solve the established model.Simulation results indicate that, compared with the deep reinforcement learning-based online offloading algorithm, the proposed algorithm can effectively optimize the resource allocation and better improve the QoE.…”
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717
Research on E-Commerce Inventory Sales Forecasting Model Based on ARIMA and LSTM Algorithm
Published 2025-05-01Get full text
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718
Efficiency management of engineering projects based on particle swarm multi objective optimization algorithm
Published 2025-12-01“…In addition, in medical resource allocation, multi-objective particle swarm optimization algorithm can optimize the resource allocation plan, balancing fairness and efficiency. …”
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719
A Constrained Multi-Objective Optimization Algorithm with a Population State Discrimination Model
Published 2025-02-01“…A simple yet effective resource allocation model is incorporated to address the potential computational resource waste associated with dual populations, enhancing the resource utilization. …”
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720
Gradual Optimization of University Course Scheduling Problem Using Genetic Algorithm and Dynamic Programming
Published 2025-03-01“…Additionally, by incorporating a greedy algorithm for classroom allocation, the utilization of classroom resources was further enhanced. …”
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