Emerging Internet of vehicles systems brings interesting new applications, such as VR entertainment systems in a car. These applications frequently generate data processing requirements and require a rapid response to ensure user experience. The combination of edge computing mode and ultra-low-latency communications (URLLC) traffic can better meet the requirements of the above scenarios. All requests for signal transmission and data processing can be considered a latency-limited task. We study scheduling strategies of these tasks intending to maximize overall utility for all users. We show that finding an optimal schedule for at least N tasks is NP-hard in the utility-maximizing issue. We propose a heuristic algorithm to maximize the overall utility of all users from the perspective of residual utility. To simulate the tolerance of delay for different tasks, we designed three utility curves: exponential, linear, and step. Simulation results show that the proposed algorithm outperforms the benchmark.
Maximize Potential Reserved Task Scheduling for URLLC Transmission and Edge Computing
01.11.2020
743111 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Europäisches Patentamt | 2020
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