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An Optimal Algorithm for resource allocation in D2D Communication

Computers, Materials & Continua 2023年第4期75卷 531-546页

作者： Shahad Alyousif Mohammed Dauwed Rafal Nader Mohammed Hasan Ali Mustafa Musa Jabar Ahmed Alkhayyat Research Centre University of MashreqBaghdadIraq College of Engineering Department of Electrical&Electronic EngineeringGulf UniversityAlmasnadKingdom of Bahrain Medical Instrumentation Techniques Engineering Dijlah University CollegeBaghdadIraq Department of Pharmacy Al-Mustaqbal University CollegeHilla51001Iraq Computer Techniques Engineering Department Faculty of Information TechnologyImam Ja’afar Al-Sadiq UniversityNajaf10023Iraq Department of Medical Instruments Engineering Techniques Al-Turath University CollegeBaghdad10021Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi UniversityBaghdad10021Iraq College of Technical Engineering The Islamic UniversityNajafIraq

The number of mobile devices accessing wireless networks isskyrocketing due to the rapid advancement of sensors and wireless communicationtechnology. In the upcoming years, it is anticipated that mobile datatraffic would rise even more. The development of a new cellular networkparadigm is being driven by the Internet of Things, smart homes, and moresophisticated applications with greater data rates and latency *** are being used up quickly due to the steady growth of smartphonedevices andmultimedia apps. Computation offloading to either several distantclouds or close mobile devices has consistently improved the performance ofmobile devices. The computation latency can also be decreased by offloadingcomputing duties to edge servers with a specific level of computing ***-to-device (D2D) collaboration can assist in processing small-scaleactivities that are time-sensitive in order to further reduce task delays. The taskoffloading performance is drastically reduced due to the variation of differentperformance capabilities of edge nodes. Therefore, this paper addressed thisproblem and proposed a new method for D2D communication. In thismethod, the time delay is reduced by enabling the edge nodes to exchangedata samples. Simulation results show that the proposed algorithm has betterperformance than traditional algorithm.

关键词： D2D communication resource allocation latency optimization

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Adaptive resource allocation Algorithm for 5G Vehicular Cloud Communication

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Computers, Materials & Continua 2024年第8期80卷 2199-2219页

作者： Huanhuan Li Hongchang Wei Zheliang Chen Yue Xu School of Mathematics and Computer Sciences Nanchang UniversityNanchang330031China Department of Electrical Engineering Jiangxi Vocational College of Mechanical&Electrical TechnologyNanchang330013China Kehua Data Co. Ltd.Xiamen361006China

The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation *** propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these *** study analyzes the components of the 5G vehicular network architecture to determine the performance of different *** is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band ***,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication *** study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane *** on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s *** determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation *** experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 *** indicates that the proposed method has higher adaptive allocation efficiency.

关键词： 5G vehicular networks mobile cloud communication resource allocation channel capacity network connectivity communication radius objective function

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User Scheduling and Slicing resource allocation in Industrial Internet of Things

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China Communications 2023年第6期20卷 368-381页

作者： Sisi Li Yong Zhang Siyu Yuan Tengteng Ma Beijing University of Posts and Telecommunications Beijing 100876China Beijing Key Laboratory of Work Safety Intelligent Monitoring Beijing University of Posts and TelecommunicationsBeijing 100876China Strategy Development Institute China Telecom Corporation Limited Beijing Research InstituteBeijing 102209China

Heterogeneous base station deployment enables to provide high capacity and wide area *** slicing makes it possible to allocate wireless resource for heterogeneous services on *** two promising technologies contribute to the unprecedented service in *** establish a multiservice heterogeneous network model,which aims to raise the transmission rate under the delay constraints for active control terminals,and optimize the energy efficiency for passive network terminals.A policygradient-based deep reinforcement learning algorithm is proposed to make decisions on user association and power control in the continuous action *** results indicate the good convergence of the algorithm,and higher reward is obtained compared with other baselines.

关键词： wireless communication resource allocation reinforcement learning heterogeneous network network slicing Internet of Things

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Energy Efficient resource allocation Approach for Renewable Energy Powered Heterogeneous Cellular Networks

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Computers, Materials & Continua 2020年第7期64卷 501-514页

作者： Yifei Wei Yu Gong Qiao Li Mei Song Xiaojun Wang Beijing Key Laboratory of Work Safety Intelligent Monitoring Beijing University of Posts and TelecommunicationsBeijing100867China School of Electronic Engineering Dublin City UniversityDublin9Ireland

In this paper,maximizing energy efficiency(EE)through radio resource allocation for renewable energy powered heterogeneous cellular networks(HetNet)with energy sharing,is *** goal is to maximize the network EE,conquer the instability of renewable energy sources and guarantee the fairness of users during allocating *** define the objective function as a sum weighted EE of all links in the *** formulate the resource allocation problem in terms of subcarrier assignment,power allocation and energy sharing,as a mixed combinatorial and non-convex optimization *** propose an energy efficient resource allocation scheme,including a centralized resource allocation algorithm for iterative subcarrier allocation and power allocation in which the power allocation problem is solved by analytically solving the Karush-Kuhn-Tucker(KKT)conditions of the problem and a water-filling problem thereafter and a low-complexity distributed resource allocation algorithm based on reinforcement learning(RL).Our numerical results show that both centralized and distributed algorithms converge with a few times of *** numerical results also show that our proposed centralized and distributed resource allocation algorithms outperform the existing reference algorithms in terms of the network EE.

关键词： Heterogeneous networks energy harvesting energy efficiency resource allocation energy sharing

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Distributed resource allocation in Dispersed Computing Environment Based on UAV Track Inspection in Urban Rail Transit

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Computers, Materials & Continua 2024年第7期80卷 643-660页

作者： Tong Gan Shuo Dong Shiyou Wang Jiaxin Li Division of Consulting Beijing Metro Consultancy Corporation Ltd.Beijing100037China Department of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China

With the rapid development of urban rail transit,the existing track detection has some problems such as low efficiency and insufficient detection coverage,so an intelligent and automatic track detectionmethod based onUAV is urgently needed to avoid major safety *** the same time,the geographical distribution of IoT devices results in the inefficient use of the significant computing potential held by a large number of *** a result,the Dispersed Computing(DCOMP)architecture enables collaborative computing between devices in the Internet of Everything(IoE),promotes low-latency and efficient cross-wide applications,and meets users’growing needs for computing performance and service *** paper focuses on examining the resource allocation challenge within a dispersed computing environment that utilizes UAV inspection ***,the system takes into account both resource constraints and computational constraints and transforms the optimization problem into an energy minimization problem with computational *** Markov Decision Process(MDP)model is employed to capture the connection between the dispersed computing resource allocation strategy and the system ***,a method based on Double Deep Q-Network(DDQN)is introduced to derive the optimal ***,an experience replay mechanism is implemented to tackle the issue of increasing *** experimental simulations validate the efficacy of the method across various scenarios.

关键词： UAV track inspection dispersed computing resource allocation deep reinforcement learning Markov decision process

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Efficient resource allocation Algorithm in Uplink OFDM-Based Cognitive Radio Networks

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Computers, Materials & Continua 2023年第5期75卷 3045-3064页

作者： Omar Abdulghafoor Musbah Shaat Ibraheem Shayea Ahmad Hamood Abdelzahir Abdelmaboud Ashraf Osman Ibrahim Fadhil Mukhlif Herish Badal Norafida Ithnin Ali Khadim Lwas Electronic&Telecommunications Engineering Department The American University of KurdistanDuhokKurdistan RegionIraq CTTC BarcelonaSpain Faculty of Electrical and Electronics Engineering Istanbul Technical UniversityIstanbulTurkey Department of Information Systems King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computing and Informatics University Malaysia SabahKota KinabaluMalaysia Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi MalaysiaJohorMalaysia R&D Ministry of Industry and MineralsBaghdadIraq

The computational complexity of resource allocation processes,in cognitive radio networks(CRNs),is a major issue to be ***,the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users,CRs,and primary users,PUs,exist in the identical geographical ***,this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarioswhile limiting interference to PUs to allowable ***,this paper,compared to other frameworks proposed in the literature,proposes a two-step approach to reduce the complexity of the proposed mathematical *** the first step,the subcarriers are assigned to the users of the CRN,while the cost function includes a pricing scheme to provide better power control algorithm with improved reliability proposed in the second *** main contribution of this paper is to lessen the complexity of the proposed algorithm and to offer flexibility in controlling the interference produced to the users of the primary networks,which has been achieved by including a pricing function in the proposed cost ***,the performance of the proposed power and subcarrier algorithm is confirmed for orthogonal frequency-division multiplexing(OFDM).Simulation results prove that the performance of the proposed algorithm is better than other algorithms,albeit with a lesser complexity of O(NM)+O(Nlog(N)).

关键词： Cognitive radio resource allocation OFDM pricing

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A Novel resource allocation Method in Ultra-Dense Network Based on Noncooperation Game Theory

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China Communications 2016年第10期13卷 169-180页

作者： Zhen Wang Xiaorong Zhu Xu Bao Su Zhao Nanjing University of Posts and Telecommunications Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Department of Telecommunications Engineering Jiangsu University Zhenjiang China

In ultra-dense networks(UDNs), large-scale deployment of femto base stations is an important technique for improving the network throughput and quality of service(QoS). In this paper, a multidimensional resource allocation algorithm based on noncooperation game theory is proposed to manage the resource allocation in UDNs, including transmission point association, user channels, and power. The algorithm derives a multidimensional resource optimization model and converts into a noncooperation game model according to the analysis of transmission point association user channel and power allocation. The algorithm includes two phases: transmission point association, and channel and power allocation. Then, feasible domain and discrete variables relaxation approaches are introduced to derive an approximate optimal multidimensional resource allocation solution with low complexity. Simulation results show that this method has some advantages in suppressing interference and improves the overall system throughput, while ensuring the QoS of femtocell users.

关键词： resource allocation noncooperation game theory variables relaxation

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Joint resource allocation Using Evolutionary Algorithms in Heterogeneous Mobile Cloud Computing Networks

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China Communications 2018年第8期15卷 189-204页

作者： Weiwei Xia Lianfeng Shen National Mobile Communications Research Lab Southeast University

The problem of joint radio and cloud resources allocation is studied for heterogeneous mobile cloud computing networks. The objective of the proposed joint resource allocation schemes is to maximize the total utility of users as well as satisfy the required quality of service(QoS) such as the end-to-end response latency experienced by each user. We formulate the problem of joint resource allocation as a combinatorial optimization problem. Three evolutionary approaches are considered to solve the problem: genetic algorithm(GA), ant colony optimization with genetic algorithm(ACO-GA), and quantum genetic algorithm(QGA). To decrease the time complexity, we propose a mapping process between the resource allocation matrix and the chromosome of GA, ACO-GA, and QGA, search the available radio and cloud resource pairs based on the resource availability matrixes for ACOGA, and encode the difference value between the allocated resources and the minimum resource requirement for QGA. Extensive simulation results show that our proposed methods greatly outperform the existing algorithms in terms of running time, the accuracy of final results, the total utility, resource utilization and the end-to-end response latency guaranteeing.

关键词： heterogeneous mobile cloud computing networks resource allocation genetic algorithm ant colony optimization quantum genetic algorithm

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A Trusted Edge resource allocation Framework for Internet of Vehicles

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Computers, Materials & Continua 2023年第11期77卷 2629-2644页

作者： Yuxuan Zhong Siya Xu Boxian Liao Jizhao Lu Huiping Meng Zhili Wang Xingyu Chen Qinghan Li State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China State Grid Henan Information&Telecommunication Company Zhengzhou450018China School of Information Studies Syracuse UniversitySyracuse13244USA

With the continuous progress of information technique,assisted driving technology has become an effective technique to avoid traffic *** to the complex road conditions and the threat of vehicle information being attacked and tampered with,it is difficult to ensure information *** paper uses blockchain to ensure the safety of driving information and introduces mobile edge computing technology to monitor vehicle information and road condition information in real time,calculate the appropriate speed,and plan a reasonable driving route for the *** solve these problems,this paper proposes a trusted edge resource allocation framework for assisted driving service,which includes two stages:the blockchain generation stage(the first stage)and assisted driving service stage(the second stage).Furthermore,in the first stage,a delay-and-throughput-oriented block generation model for the mobile terminal is *** the second stage,a balanced offloading algorithm for assisted driving service based on edge collaboration is proposed to solve the problems of unbalanced load of cluster mobile edge computing(MEC)servers and low resource utilization of the *** this paper optimizes the throughput of blockchain and delay of the transportation network through deep reinforcement learning(DRL)***,compared with joint computation and communication resources’allocation(JCCR)and resource allocation method based on binary offloading(RAB),our proposed scheme can optimize the delay by 7.4%and 26.7%,and support various application services of the vehicular networks more effectively.

关键词： Blockchain load balancing vehicular networks resource allocation

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Hybrid Multiple Access and Service-Oriented resource allocation for Heterogeneous QoS Provisioning in Machine Type Communications

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Journal of Communications and Information Networks 2020年第2期5卷 225-236页

作者： Yanan Liu Xianbin Wang Jie Mei Electrical and Computer Engineering Western UniversityLondonON N6A 3K7Canada

Non-orthogonal multiple access(NOMA)has emerged as one important enabling technology for future wireless communications and services,including machine type communication(MTC).Unfortunately,supporting diverse MTC services and massive connectivity is still challenging due to the very different service requirements,scarce radio resources,limited battery capacity of MTC devices,as well as rapidly changing network *** this paper,a hybrid-multipleaccess(HMA)scheme for service-oriented resource allocation scheme is proposed in supporting diverse MTC services for resource constrained devices and *** the proposed scheme,HMA allows MTC devices to choose a suitable type of multiple access technique according to their channel conditions,power constraints,and quality of service(QoS)*** support service-oriented resource allocation,the physical network is firstly sliced into several virtualized networks based on QoS requirements and hardware conditions of MTC devices.A novel utility function integrating network performance and the power consumption in MTC devices is ***,the resource allocation problem is formulated as an optimization problem to maximize the different utility functions under constraints of user QoS requirements and maximum transmitted *** improve computational capacity as well as reduce the operational latency,a cloud-edge collaborative scheme is further designed to share the computation loads between the cloud and *** results demonstrate the proposed service-oriented resource allocation scheme is effective and illustrate that the proposed hybrid multiple access method provides better performance than NOMA in terms of effective energy efficiency.

关键词： machine type communication network virtualization cloud-edge computing resource allocation hybrid multiple access

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