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 >
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