Resource-constrained edge cloud-oriented internet of things application optimal deployment method

Abstract

The invention provides a resource-constrained edge cloud-oriented internet-of-things application optimal deployment method, which comprises the following steps of: firstly, respectively constructing aresource waste model, a resource load imbalance model, an energy consumption model and a bandwidth resource consumption model for a constructed smart city mobile edge computing system model; performing weighting to construct a joint optimization objective function; secondly, improving a DE algorithm and control parameters through a chromosome coding scheme, and obtaining an effective improved DEalgorithm; and finally, carrying out optimization solution on the joint optimization objective function by utilizing an improved DE algorithm, and outputting idle resources, resource load imbalance levels, energy consumption power and bandwidth resource consumption corresponding to the minimum value of the joint optimization objective function. According to the approximately optimal deployment scheme provided by the invention, the system utility and the bandwidth resource utilization rate can be improved at the same time under specified resource and execution delay constraint conditions, and the diversity and convergence rate of the algorithm are improved by adopting multiple optimization strategies.

Description

technical field [0001] The present invention relates to the technical field of Internet of Things application deployment of mobile edge computing, in particular to a resource-constrained edge cloud-oriented optimized deployment method for Internet of Things applications. Background technique [0002] In recent years, many scholars have conducted research on the deployment of Internet of Things applications for mobile edge computing, and have achieved a lot of research results. For example, Tong L. et al. designed the edge cloud as a tree hierarchy of regionally distributed edge servers to improve cloud resource utilization efficiency, and further proposed a workload distribution algorithm to decide which edge servers to place mobile applications on, and How much computing power is available to execute each mobile application. Lau F. et al. proposed a general model for how to distribute and schedule jobs to minimize the weighted response time of all jobs, and then proposed a...

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Problems solved by technology

[0004] Aiming at the deficiencies in the above-mentioned background technologies, the present invention proposes a resource-constrained edge cloud-oriented IoT application optimization deployment method, which solves the problem of energy consumption in the edge cloud during the smart city IoT application process in the resource-constrained edge cloud. , Processor resources and bandwidth resource consumption are too large technical problems

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