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  • Open Access

    ARTICLE

    Deep Q-Learning Based Computation Offloading Strategy for Mobile Edge Computing

    Yifei Wei1,*, Zhaoying Wang1, Da Guo1, F. Richard Yu2

    CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 89-104, 2019, DOI:10.32604/cmc.2019.04836

    Abstract To reduce the transmission latency and mitigate the backhaul burden of the centralized cloud-based network services, the mobile edge computing (MEC) has been drawing increased attention from both industry and academia recently. This paper focuses on mobile users’ computation offloading problem in wireless cellular networks with mobile edge computing for the purpose of optimizing the computation offloading decision making policy. Since wireless network states and computing requests have stochastic properties and the environment’s dynamics are unknown, we use the model-free reinforcement learning (RL) framework to formulate and tackle the computation offloading problem. Each mobile user… More >

  • Open Access

    ARTICLE

    Context-Based Intelligent Scheduling and Knowledge Push Algorithms for AR-Assist Communication Network Maintenance

    Lanlan Rui1, Yabin Qin1,*, Biyao Li1, Zhipeng Gao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 291-315, 2019, DOI:10.31614/cmes.2018.04240

    Abstract Maintenance is an important aspect in the lifecycle of communication network devices. Prevalent problems in the maintenance of communication networks include inconvenient data carrying and sub-optimal scheduling of work orders, which significantly restrict the efficiency of maintenance work. Moreover, most maintenance systems are still based on cloud architectures that slow down data transfer. With a focus on the completion time, quality, and load balancing of maintenance work, we propose in this paper a learning-based virus evolutionary genetic algorithm with multiple quality-of-service (QoS) constraints to implement intelligent scheduling in an edge network. The algorithm maintains the More >

  • Open Access

    ARTICLE

    A Heterogeneous Virtual Machines Resource Allocation Scheme in Slices Architecture of 5G Edge Datacenter

    Changming Zhao1,2,*, Tiejun Wang2, Alan Yang3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 423-437, 2019, DOI:10.32604/cmc.2019.07501

    Abstract In the paper, we investigate the heterogeneous resource allocation scheme for virtual machines with slicing technology in the 5G/B5G edge computing environment. In general, the different slices for different task scenarios exist in the same edge layer synchronously. A lot of researches reveal that the virtual machines of different slices indicate strong heterogeneity with different reserved resource granularity. In the condition, the allocation process is a NP hard problem and difficult for the actual demand of the tasks in the strongly heterogeneous environment. Based on the slicing and container concept, we propose the resource allocation… More >

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