Time-sensitive multi-task edge computing and cache cooperative offload strategy method
An edge computing, multi-tasking technology, applied in the field of edge computing combined with the Internet of Things and drones, can solve the problems affecting the quality of experience and delay of IoT devices, and achieve the effect of meeting the quality of experience requirements and reducing energy consumption.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Publication Date
- 2021-10-12
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Abstract
Description
.Technical field
[0001] The invention belongs to the field of unmanned aerial vehicles, edge computing combined with the Internet of Things, under the background of the 5G Internet of Things, a time-sensitive multi-task edge computing and cache cooperative unloading strategy based on the unmanned aerial vehicle. Background technique
[0002] Usually the deployment of mobile edge computing servers is fixed, which limits its development closer to IoT devices, thereby further reducing the latency or energy consumption of devices. As an aerial mobile edge computing node, drones are widely used in surveillance, data collection, disaster relief, and public safety service coverage due to their excellent flexibility and mobility. Although drone-enabled mobile edge computing provides IoT devices with remote resources, it still faces communication and computing design challenges due to the limited number of embedded batteries in drones and IoT devices. At present, a variety of energy...
Examples
Embodiment Construction
[0116] Time-sensitive multi-task edge computing and cache collaboration unloading strategy method, the method of the present invention includes UAV trajectory optimization sub-strategy, UAV resource allocation optimization sub-strategy, Internet of Things device unloading decision-making sub-strategy; use the block coordinate descent method to combine the above three The sub-strategies are iteratively run, and the final value is obtained after the final strategy converges;
[0117] The UAV trajectory optimization sub-strategy is used to optimize the UAV flight trajectory when the UAV resource allocation optimization sub-strategy and the IoT device unloading decision-making sub-strategy are determined;
[0118] UAV resource allocation optimization sub-strategy, which is used for UAV flight trajectory and IoT device unloading decision-making sub-strategy. Under the fixed situation, use CVX technology to solve the calculation of each time slice of UAV for each IoT device through t...