Reliable edge-cloud computing service delay optimization method for cyber-physical system
A cyber-physical system and optimization method technology, applied in the field of reliable edge-cloud computing service delay optimization, can solve problems such as reducing the sustainability of CPS applications, and achieve the effect of reducing system service delay and avoiding transmission and execution.
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Embodiment 1
[0120] Such as figure 2 As shown, this embodiment proposes a reliable edge-cloud computing service delay optimization method for cyber-physical systems, and the method includes the following steps:
[0121] Step 1: Model the service delay of the base station based on the calculation offload transmission delay and execution delay, and set the service delay target of the edge cloud computing according to the energy budget and reliability characteristics. The service delay target of the edge cloud computing includes static phase targets and dynamic The goal of the stage, the goal of the static stage is to find the optimal calculation offloading mapping and the number of task backups, and the goal of the dynamic stage is to avoid the transmission and execution of redundant tasks at runtime;
[0122] Step 2: Calculate the system service delay, and convert the service delay target of edge cloud computing into five scheduling constraints. The five scheduling constraints include the ...
Embodiment 2
[0217] This embodiment takes a cyber-physical fusion system as an example to illustrate how to apply a reliable edge-cloud computing service delay optimization method for cyber-physical systems. The cyber-physical fusion system is a typical CPS composed of edge / cloud computing coupling, specifically including multiple A terminal user, multiple base stations, multiple heterogeneous edge servers and a cloud server, multiple heterogeneous edge servers and a cloud server constitute an edge / cloud server, multiple end users are wirelessly connected to adjacent base stations, and the edge / cloud server Wirelessly connect to multiple base stations in its vicinity.
[0218] In this embodiment, the base station is expressed as J is the number of base stations, and the heterogeneous edge server is expressed as κ is the number of heterogeneous edge servers, edge / cloud servers are expressed as In actual application, each heterogeneous edge server has server heterogeneity, which is main...
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