1. Deep reinforcement learning-based resource reservation algorithm for emergency Internet-of-things slice
- Author
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Guolin SUN, Ruijie OU, and Guisong LIU
- Subjects
emergency IoT ,deep reinforcement learning ,resource reservation ,ultra-low latency communication ,Telecommunication ,TK5101-6720 - Abstract
Based on the requirements of ultra-low latency services for emergency Internet-of-things (EIoT) applications,a multi-slice network architecture for ultra-low latency emergency IoT was designed,and a general methodology framework based on resource reservation,sharing and isolation for multiple slices was proposed.In the proposed framework,real-time and automatic inter-slice resource demand prediction and allocation were realized based on deep reinforcement learning (DRL),while intra-slice user resource allocation was modeled as a shape-based 2-dimension packing problem and solved with a heuristic numerical algorithm,so that intra-slice resource customization was achieved.Simulation results show that the resource reservation-based method enable EIoT slices to explicitly reserve resources,provide a better security isolation level,and DRL could guarantee accuracy and real-time updates of resource reservations.Compared with four existing algorithms,dueling deep Q-network (DQN) performes better than the benchmarks.
- Published
- 2020
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