Multi-dimension resource allocation algorithm based on QoS guarantee in dense WLAN by Qi ZHANG, Lin-jing ZHAO, Jian-dong LI

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Virtual Network Resource Allocation Algorithm Based on Load Balance in Carrier-SDN by Li Wang, Jihong Zhao, Hua Qu, Ya Guo

“…Resource allocation algorithm for virtual networks in carrier-SDN based on load balance was proposed.Firstly,multiple-layered model of carrier-SDN was constructed.Secondly,the binaryzation of particle swarm optimization algorithm with the characteristic of virtual network embedding（VNE）algorithm was realized.Finally,load balance was set as optimization object,then the solution of VNE problem was got.The simulation results demonstrate that the proposed algorithm has superior performance in terms of load balance,acceptance ratio and average compared with existing methods.…”
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Energy-efficient resource allocation algorithm for massive MIMO OFDMA downlink system by Ying HU, Bao-feng JI, Yong-ming HUANG, Fei YU, Lv-xi YANG

“…An algorithm is proposed for energy-efficient resource allocation scheme in massive MIMO OFDMA downlink mobile communication system.A mathematical formulation of optimization issue is provided with the objective of maximizing system energy efficiency lower bound under the minimum data rate requirement of user,meanwhile the BS uses a zero-forcing(ZF) precoding.And then for optimizing energy efficiency function,the bandwidth allocation,power allocation and the number of antenna arrays at the BS are adjusted synchronously.First,an iterative algorithm derived from optimality condition for bandwidth assignment is proposed.Second,the properties of fractional programming and convex optimization are used to maximize the energy efficiency.Specifically,both the number of antenna arrays at the BS and the transmit data rate at the user are adjusted.Simulation results show that the proposed schemes not only have less iteration number but also have good perform for system energy efficiency and throughput.…”
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Wide area cooperative resource allocation algorithm for shortwave communication access network by Guojun LI, Xu HOU, Changrong YE, Yiping LUO

“…Aiming at the problem that short-wave point-to-point communication was not reliable enough to meet the actual needs, a wide area cooperative resource allocation algorithm based on shortwave communication access network was proposed.The reliability of the shortwave communication was improved by invoking multiple stations to coordinately guarantee users from different channels.The resource allocation problem was decomposed into two sub-problems of channel and station matching and station allocation.Firstly, the maximum expected success rate matching model was established to match the channel and the station, and the stations allocated to the channel were combined into different guarantee schemes.Then, the fuzzy analytic hierarchy process and the entropy weight method were used to obtain the subjective and objective scores of the scheme, and the optimal scheme was selected through fusion of evidence reasoning.The results show that the proposed algorithm can effectively improve the success rate of shortwave communication and has good adaptability.…”
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Resource allocation algorithm based on the multi-relay decoding-and-forwarding in OFDM system by Tao GUO, Youming LI, Ting LI, Yuzhi YAN

“…For the rate maximization problem in OFDM decode-and-forward relay system，a resource allocation algorithm based on the multi-relay forwarding was proposed. …”
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Research on IoV resource allocation algorithm assisted by reconfigurable intelligent surface by Fatang CHEN, Ruofan ZHANG

“…In order to meet the higher requirements of vehicle communication quality and spectral efficiency, a IoV resource allocation algorithm assisted by reconfigurable intelligent surface (RIS) was proposed.The RIS reflection coefficient matrix, power allocation, and spectrum sharing schemes were combined to solve the problem of maximizing the total capacity of V2I link under the condition of ensuring the reliability of V2V link.As this problem was a non-convex optimization problem with highly coupled variables, it was difficult to solve it directly.Therefore, after introducing an analytic expression to approximate the interrupt probability of V2V link, the problem was decomposed into three sub-problems by using the block coordinate descent (BCD) method, and the sub-problems were solved by introducing auxiliary variables, successive convex approximation (SCA), Hungarian algorithm, etc., and then the approximate suboptimal solution of the problem was obtained.Simulation results show that the proposed algorithm has good convergence performance and can effectively improve the total capacity of V2I link.…”
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Research on heterogeneous radio access and resource allocation algorithm in vehicular fog computing by Kai XIONG, Supeng LENG, Ke ZHANG, Hao LIU

Subjects: “…Internet of vehicles (IoV);vehicular fog;vehicular delay tolerant network (VDTN);Q-learning algorithm;resource allocation…”
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Research on resource allocation algorithm of centralized and distributed Q-learning in machine communication by Yunhe YU, Jun SUN

“…Under the premise of ensuring partial machine type communication device (MTCD)’s quality of service (QoS) requirements, the resource allocation problem was studied with the goal of maximizing system throughput in the massive machine type communication (mMTC) scenario.Two resource allocation algorithms based on Q-learning were proposed: centralized Q-learning algorithm (team-Q) and distributed Q-learning algorithm (dis-Q).Firstly, taking into account MTCD’s geographic location and multi-level QoS requirements, a clustering algorithm based on cosine similarity (CS) was designed.In the clustering algorithm, multi-dimensional vectors that represent MTCD and data aggregator (DA) were constructed, and MTCDs can be grouped according to the CS value between multi-dimensional vectors.Then in the MTC network, the team-Q learning algorithm and dis-Q learning algorithm were used to allocate resource blocks and power for the MTCD.In terms of throughput performance, team-Q and dis-Q algorithms have an average increase of 16% and 23% compared to the dynamic resource allocation algorithm and the greedy algorithm, respectively.In terms of complexity performance, the dis-Q algorithm is only 25% of team-Q algorithm and even below, the convergence speed is increased by nearly 40%.…”
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Predictive Algorithms and Perceptions of Fairness: Parent Attitudes Toward Algorithmic Resource Allocation in K-12 Education by Rebecca A. Johnson, Simone Zhang

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A distributed algorithm for solving large-scale p-median problems using expectation maximization by Harsha Gwalani, Joseph Helsing, Sultanah M. Alshammari, Chetan Tiwari, Armin R. Mikler

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User allocation technology for multi-dimensional resource optimization of LEO satellite by ZHOU Jiaen, ZHAO Yafei, PENG Mugen

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Optimization of Combat Resource Allocation Based on Restricted Tournament Selection Social Genetic Algorithm by Shandong Yuan, Yun Ren, Han Zhou, Yongjing Cheng, Kai Yan

Subjects: “…Combat resource allocation problem…”
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Network slicing resource allocation algorithm based on bipartite graph matching in smart grids by Weiwei XIA, Yifei XIN, Dong LIANG, Jun WU, Xin WANG, Feng YAN, Lianfeng SHEN

“…To solve the problem of simultaneously satisfying the quality of service requirements of multiple types of services in smart grids and considering the economic utility of power terminals and network side, a network slicing resource allocation algorithm based on bipartite graph matching was proposed.For the control and collection services in smart grids, the corresponding bidding information was formulated for the power terminals, and the payment price and utility matrix were calculated accordingly.The resource allocation between the network slices and the power terminals was modeled as a bipartite graph matching problem.Different slicing resources were allocated to the terminals according to the latency, transmission rate, or energy consumption requirements of different services to maximize the system utility.Simulation results show that the proposed algorithm is able to improve the system utility by 10%～20% compared to the existing double auction algorithm and greedy algorithm.…”
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Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation by WANG Chaowei, PANG Mingliang, WANG Su, ZHAO Lingli, GAO Feifei, CUI Gaofeng, WANG Weidong

“…To address challenges such as co-frequency interference, spectrum scarcity, and uneven traffic distribution in multi-beam LEO satellites, a resource allocation algorithm based on decision performance evaluation was proposed. …”
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Research on resource allocation algorithm in D2D networks based on alliance game by Chen Yujie, Ma Caihong

“…Aiming at the communication resource allocation problem in the SCMA system in the single-cell scenario, this paper aims to maximize the system throughput and ensure the minimum threshold rate of all users, and model it as an alliance game to solve it. …”
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A distributed CRN resource allocation algorithm based on CBR and cooperative Q-learning by Lin XU, Zhijin ZHAO

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Cellular-free RAN slicing resource allocation algorithm based on multi-timescale collaboration by XIA Weiwei, WANG Boye, XIA Yaxing, MIAO Weiwei, WANG Dayang, JING Dongsheng, YAN Feng, SHEN Lianfeng

“…To address the issue of ensuring user quality of service in resource allocation for 6G cell-free radio access network slicing under dynamic service variations, a resource allocation algorithm based on multi-timescale collaborative optimization was proposed. …”
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Joint optimization algorithm for task offloading resource allocation based on edge-end collaboration by Liuqing WU, Xiaorong ZHU

“…In order to solve the problem of limited mobile terminal resources and improve task processing efficiency,a task offloading resource allocation algorithm based on edge-end collaboration was proposed.With the goal of maximizing the total benefit of tasks,the optimal task offloading resource allocation problem based on Lyapunov theory was formed by the constraint of service QoS guarantee and resource limitation.Since the problem is NP-hard,it was decoupled into a channel resource allocation problem solved by KKT condition and a 0-1 integer programming problem about task assignment.Compared with the traditional algorithm,the complexity of the proposed algorithm was O(mn),the efficiency was improved by about 20%,and the delay was reduced more than 15%.…”
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Research on cloud computing resource allocation strategy based on improved ant colony algorithm by Liu Dengming, Jing Junfeng, Liu Kai, Fang Zhiqi

“…In actual projects, it is found that if the ant colony algorithm is directly applied to cloud computing resource allocation, there will often be load imbalances, resulting in low resource utilization. …”
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Joint user association and dynamic resource allocation algorithm for LEO-RAN slicing scenarios by Geng CHEN, Zhiwei XING, Fei SHEN, Qingtian ZENG

“…A joint user association and dynamic resource allocation algorithm was proposed for the slicing scenario of ultra dense low earth orbit-radio access network (LEO-RAN) in order to address the efficient utilization of resources of the integrated terrestrial-satellite network for 6G .Considering the constraints of the minimum rate, maximum delay and resource proportion of different slices, a joint optimization problem of user association and resource allocation was established to maximize the weighted sum of the SE and the differentiated SLA of different slices as the optimization objective.A network slicing algorithm based on multi-agent deep deterministic policy gradient (MADDPG) was proposed to determine the proportion of slicing resources, a Lagrange dual based user association algorithm was proposed to determine the optimal user association policy and the resources were allocated to users by using the round-robin scheduling mechanism.The simulation results show that the proposed algorithm can effectively improve SE while satisfying the differentiated SLA of different slices.Compared with MADDPG-RA, MATD3-LG, MATD3-RA, MASAC-LG and MASAC-RA algorithms, the system utility of the proposed algorithm is improved by 2.0%, 2.3%, 5.7%, 8.7% and 9.4%, respectively.…”
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