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Joint Optimization of Task Caching,Computation Offloading and resource allocation for Mobile Edge Computing

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China Communications 2022年第12期19卷 142-159页

作者： Zhixiong Chen Zhengchuan Chen Zhi Ren Liang Liang Wanli Wen Yunjian Jia School of Microelectronics and Communication Engineering Chongqing UniversityChongqing400044 China Chongqing Key Laboratory of Space Information Network and Intelligent Information Fusion Chongqing400044 China National Mobile Communications Research Laboratory Southeast UniversityNanjing210096 China School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400065 China

Applications with sensitive delay and sizeable data volumes,such as interactive gaming and augmented reality,have become popular in recent *** applications pose a huge challenge for mobile users with limited *** offloading is a mainstream technique to reduce execution delay and save energy for mobile ***,computation offloading requires communication between mobile users and mobile edge computing(MEC) *** a mechanism would difficultly meet users’ demand in some data-hungry and computation-intensive applications because the energy consumption and delay caused by transmissions are considerable expenses for *** task data can effectively reduce the data transmissions when users offload their tasks to the MEC *** limited caching space at the MEC server calls for judiciously decide which tasks should be *** by this,we consider the joint optimization of computation offloading and task caching in a cellular *** particular,it allows users to proactively cache or offload their tasks at the MEC *** objective of this paper is to minimize the system cost,which is defined as the weighted sum of task execution delay and energy consumption for all *** at establishing optimal performance bound for the system design,we formulate an optimization problem by jointly optimizing the task caching,computation offloading,and resource *** problem is a challenging mixed-integer non-linear programming problem and is NP-hard in *** solve it efficiently,by using convex optimization,Karmarkar ’s algorithm and the proposed fast search algorithm,we obtain an optimal solution of the formulated problem with manageable computational *** simulation results show that in comparison to some representative benchmark methods,the proposed solution can effectively reduce the system cost.

关键词： mobile edge computing computation offloading caching resource allocation

Integrated Route Planning and resource allocation for Connected Vehicles

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China Communications 2021年第3期18卷 226-239页

作者： Quan Yuan Bo Chen Guiyang Luo Jinglin Li Fangchun Yang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of High-end Server and Storage Technology Jinan 250101ShandongChina

Intelligent and connected vehicles have leveraged edge computing paradigm to enhance their environment comprehension and behavior planning *** the quantity of intelligent vehicles and the demand for edge computing are increasing rapidly,it becomes critical to efficiently orchestrate the communication and computation resources on edge *** methods usually perform resource allocation in a fairly effective but still reactive manner,which is subject to the capacity of nearby edge *** deal with the contradiction between the spatiotemporally varying demands for edge computing and the fixed edge cloud capacity,we proactively balance the edge computing demands across edge clouds by appropriate route *** this paper,route planning and resource allocation are jointly optimized to enhance intelligent *** propose a multi-scale decentralized optimization method to deal with the curse of *** large-scale optimization,backpressure algorithm is used to conduct route planning and load balancing across edge *** small-scale optimization,game-theoretic multi-agent learning is exploited to perform regional resource *** experimental results show that the proposed algorithm outperforms the baseline algorithms which optimize route planning and resource allocation separately.

关键词： connected vehicles edge computing resource allocation route planning

A Novel resource allocation Algorithm based on Downlink and Uplink Decouple Access Scheme in Heterogeneous Networks

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China Communications 2016年第6期13卷 22-31页

作者： Laiwei Jiang Xuejun Sha Xuanli Wu Naitong Zhang Communication Research Center Harbin Institute of Technology

Traditional cellular network requires that a user equipment(UE) should associate to the same base station(BS) in both the downlink(DL) and the uplink(UL). Based on dual connectivity(DC) introduced in LTE-Advanced R12, DL/UL decouple access scheme has been proposed, which is especially suitable for heterogeneous networks(Het Nets). This paper is the pioneer to take the DL/UL decouple access scheme into consideration and develop a novel resource allocation algorithm in a two-tier Het Net to improve the total system throughput in the UL and ease the load imbalance between macro base stations(MBSs) and pico base stations(PBSs). A model is formulated as a nonlinear integer programming, and the proposed algorithm is a sub-optimal algorithm based on the graph theory. First, an undirected and weighted interference graph is obtained. Next, the users are grouped to let users with large mutual interferences to be assigned to different clusters. Then, the users in different clusters are allocated to different resource blocks(RBs) by using the Hungarian algorithm. Simulation results show that the proposed algorithm can provide great promotions for both the total system throughput and the average cell edge user throughput and successfully ease the load imbalance between MBSs and PBSs.

关键词： LTE-Advanced downlink and up-link decouple access scheme heterogeneous networks resource allocation graph theory

Task Offloading and resource allocation for Edge-Enabled Mobile Learning

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China Communications 2023年第4期20卷 326-339页

作者： Ziyan Yang Shaochun Zhong School of Information Science and Technology Northeast Normal UniversityChangchun 130117China Engineering Research Center of E-Learning Supporting Technology Ministry of EducationChangchun 130117China

Mobile learning has evolved into a new format of education based on communication and computer technology that is favored by an increasing number of learning users thanks to the development of wireless communication networks,mobile edge computing,artificial intelligence,and mobile ***,due to the constrained data processing capacity of mobile devices,efficient and effective interactive mobile learning is a ***,for mobile learning,we propose a"Cloud,Edge and End"fusion system *** task offloading and resource allocation for edge-enabled mobile learning to reduce the time and energy consumption of user ***,we present the proposed solutions that uses the minimum cost maximum flow(MCMF)algorithm to deal with the offloading problem and the deep Q network(DQN)algorithm to deal with the resource allocation problem ***,the performance evaluation shows that the proposed offloading and resource allocation scheme can improve system performance,save energy,and satisfy the needs of learning users.

关键词： mobile learning mobile edge computing(MEC) system construction offloading resource allocation

Metaheuristic resource allocation Strategy for Cluster Based 6G Industrial Applications

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Computers, Materials & Continua 2022年第4期71卷 667-681页

作者： Anwer Mustafa Hilal Lamia Osman Widaa Fahd N.Al-Wesabi Mohammad Medani Manar Ahmed Hamza Mesfer Al Duhayyim Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

The emergence of Beyond 5G(B5G)and 6G networks translated personal and industrial operations highly effective,reliable,and gainful by speeding up the growth of next generation Internet of Things(IoT).Industrial equipment in 6G encompasses a huge number of wireless sensors,responsible for collecting massive quantities of *** the same time,6G network can take real-world intelligent decisions and implement automated equipment *** the inclusion of different technologies into the system increased its energy consumption for which appropriate measures need to be *** has become mandatory for optimal resource allocation in 6G-enabled industrial *** this scenario,the current research paper introduces a new metaheuristic resource allocation strategy for clusterbased 6G industrial applications,named MRAS-CBIA *** technique aims at accomplishing energy efficiency and optimal resource allocation in 6G-enabled industrial *** proposed MRAS-CBIR technique involves three major ***,Weighted Clustering Technique(WCT)is employed to elect the optimal Cluster Heads(CHs)or coordinating agents with the help of three parameters namely,residual energy,distance,and node ***,Decision Tree-based Location Prediction(DTLP)mechanism is applied to determine the exact location of Management Agent(MA).Finally,Fuzzy C-means with Tunicate Swarm Algorithm(FCMTSA)is used for optimal resource allocation in 6G industrial *** performance of the proposed MRAS-CBIA technique was validated and the results were examined under different *** resultant experimental values highlighted the superior performance of MRAS-CBIR technique over existing state-of-the-art methods.

关键词： 6G industrial internet of things energy efficiency resource allocation metaheuristics

Dynamic resource allocation in TDD-Based Heterogeneous Cloud Radio Access Networks

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China Communications 2016年第6期13卷 1-11页

作者： Zhi Yu Ke Wang Hong Ji Xi Li Heli Zhang The Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications

To fulfill the explosive growth of network capacity, fifth generation(5G) standard has captured the attention and imagination of researchers and engineers around the world. In particular, heterogeneous cloud radio access network(H-CRAN), as a promising network paradigm in 5G system, is a hot research topic in recent years. However, the densely deployment of RRHs in H-CRAN leads to downlink/uplink traffic asymmetry and severe inter-cell interference which could seriously impair the network throughput and resource utilization. To simultaneously solve these two problems, we proposed a dynamic resource allocation(DRA) scheme for H-CRAN in TDD mode. Firstly, we design a clustering algorithm to group the RRHs into different sets. Secondly, we adopt coordinated multipoint technology to eliminate the interference in each set. Finally, we formulate the joint frame structure, power and subcarrier selection problem as a mixed strategy noncooperative game. The simulation results are presented to validate the effectiveness of our proposed algorithm by compared with the existing work.

关键词： heterogeneous cloud radio accessnetworks dynamic time division duplex resource allocation coordinated multipoint

Coordinated resource allocation for Satellite-Terrestrial Coexistence Based on Radio Maps

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China Communications 2018年第3期15卷 149-156页

作者： Yanmin Wang Zhou Lu China Academy of Electronics and Information Technology Beijing 100041 China

Coexistence of satellite and terrestrial wireless communication systems in the same frequency band is quite promising for addressing the challenge of spectrum scarcity. To cope with the inevitable inter-system interference, radio resource allocation at both sides should be carefully re-optimized. In this paper, we focus on a scenario where a satellite communication system and a terrestrial distributed antenna system(DAS) coexist via spectrum sharing. We particularly utilize the radio map(RM) to reduce the system overhead for channel acquisition. Based on the large-scale channel state information at the transmitter(CSIT), which is derived from the RM, we propose an optimized power allocation scheme to improve the achievable sum rate of the terrestrial system. For the satellite side, an opportunistic user scheduling scheme is presented, to reduce the harmful leakage interference to the terrestrial mobile users. Simulation results demonstrate that the proposed RM-based coordination scheme can significantly promote the performance of satellite terrestrial coexistence, although the small-scale channel fading has been ignored in the formulated optimization.

关键词： satellite terrestrial coexistence distributed antenna system (DAS) radio map(RM) resource allocation

Low complexity resource allocation and scheduling algorithms for downlink SDMA systems

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The Journal of China Universities of Posts and Telecommunications 2009年第5期16卷 33-40页

作者： SUN Kai WANG Ying ZHANG Ping College of Electronic Information Engineering Inner Mongolia University Hohhot 010021 China Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing 100876 China

The downlink zero-forcing beamforming strategy in the case of random packet arrivals is investigated. Under this setting, the relevant fairness criterion is the stabilization of all buffer queues which guarantees a bounded average delay for all users. It has been shown that allocating resources to maximize a queue-length-weighted sum of the rates is a stabilizing policy. However, the high complexity of user selection and the feasible rates determination for optimal scheme may prevent the real-time scheduling operation. Two low complexity algorithms are provided taking the channel state, queue state and orthogonality into account. In particular, the authors pick the first user with the largest product between channel gain and queuing length, and select the remaining users to construct candidate user set based on the greedy user selection method or channel orthogonal user selection method. Then, the power and rate allocation for the selected users are implemented based on the modified water-filling method. The complexity of the proposed algorithms is analyzed. The average delay and average throughput are studied in homogeneous scenarios and heterogeneous scenarios, respectively. Simulation results show that the proposed algorithms can take full advantage of the multi-user diversity gain and provide average delay （or throughput） and fairness improvement compared with channel-aware-only schemes.

关键词： space-division multiple access (SDMA) resource allocation scheduling algorithm zero-forcing

End-to-end utility-based resource allocation for multi-RAT nodes in heterogeneous cognitive wireless networks

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The Journal of China Universities of Posts and Telecommunications 2013年第2期20卷 19-24页

作者： CHEN Feng XU Wen-jun LIN Jia-ru NIU kai MA Hong-yu Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications

This paper studies the problem of effective resource allocation for multi-radio access technologies （Multi-RAT） nodes in heterogeneous cognitive wireless networks （HCWNs）. End-to-end utility, which is defined as the delay of end-to-end communication, is taken into account in this paper. In the scenario of HCWNs, it is assumed that the cognitive radio nodes have the ability of Multi-RAT and can communicate with each other through different paths simultaneously by splitting the arrival packets. In this paper, the problem is formulated as the optimization of split ratio and power allocation of the source cognitive radio node to minimize the delay of end-to-end communication, and a low complexity step-by-step iterative algorithm is proposed. Numerical results show good performance of the proposed algorithm over two other conventional algorithms.

关键词： resource allocation heterogeneous cognitive wireless networks end-to-end utility Multi-RAT