KR-20260066572-A - Simulation-based Decision Support Method and System for Data Distribution of Hyperlocal Services in Edge Cloud Environments

KR20260066572AKR 20260066572 AKR20260066572 AKR 20260066572AKR-20260066572-A

Abstract

A simulation-based decision support method and system for data distribution of hyperlocal services in an edge cloud environment are presented. The simulation-based decision support system for data distribution of hyperlocal services in an edge cloud environment proposed in this invention includes a level-based control unit that determines the level of a data distribution strategy for edge storage utilization using level-based control applied globally across all service regions; a strategy customization unit that provides service region-based control on the determined level-based data distribution strategy; a data distribution map providing unit that visualizes a data distribution map to represent the determined level-based data distribution strategy applied to each service region; and a simulation unit that provides simulation results based on the final data distribution strategy determined according to the service region and the level-based data distribution strategy.

Inventors

고인영
임수정

Assignees

한국과학기술원

Dates

Publication Date: 20260512
Application Date: 20241106
Priority Date: 20241104

Claims (15)

A level-based control unit that determines the level of a data distribution strategy for edge storage utilization using level-based control applied globally across all service areas; A strategy customization unit that provides service area-based control on the above-determined level-based data distribution strategy; A data distribution map providing unit that visualizes a data distribution map to represent the above-determined level-based data distribution strategy applied to each service area; and A simulation unit that provides simulation results according to the final data distribution strategy determined according to the above service area and the above level-based data distribution strategy. A simulation-based decision support system for data distribution including
In paragraph 1, The above level-based control unit is, Determining the level of a data distribution strategy among multiple levels based on cloud storage utilization in the existing cloud environment prior to data distribution and edge storage utilization in all service regions. Simulation-based decision support method for data distribution.
In paragraph 1, The above strategy customization department is, To reflect specific preferences and policies regarding data distribution, the entire service region is arbitrarily divided into multiple regions, and the system is customized to switch storage types between the cloud and edge of each divided region. Simulation-based decision support method for data distribution.
In paragraph 1, The above data distribution map providing unit is, Providing a distributed map that displays regional information including segmented service areas, cloud storage utilization, edge storage utilization, region ID, used storage ID, data size of regional data, and population density representing the number of users located in that region. Simulation-based decision support method for data distribution.
In paragraph 1, The above simulation unit is, Providing simulation results representing performance and cost indicators, including average response times classified by storage type, the percentage of messages with response speeds below a predetermined threshold, minimum and maximum response times during all message transmissions across the entire service area, the total number of users benefiting from edge storage, the latency difference between a cloud-only strategy and a selected end-data distribution strategy, the overall performance improvement rate, and the estimated cost of the strategy calculated based on the ratio of edge and cloud storage usage. Simulation-based decision support method for data distribution.
In paragraph 5, The above simulation unit is, To provide simulation results regarding the average response time classified by the above storage type and the message ratio where the response speed is below a predetermined standard, the average response time and the message ratio are provided in three categories according to the storage type: a type calculated using all message transmissions in the entire service area, a type calculated for areas using cloud storage, and a type calculated for areas using edge storage. Simulation-based decision support method for data distribution.
In paragraph 5, The above simulation unit is, To provide simulation results for the estimated cost of a strategy calculated based on the above-mentioned cloud storage usage ratio, the estimated cost is estimated using the total data size of the region using cloud storage, the total data size of the region using edge storage, the cost of using cloud storage within a predetermined period, and the cost of using edge storage per predetermined data capacity. Simulation-based decision support method for data distribution.
A step of determining the level of a data distribution strategy for edge storage utilization using level-based control applied globally across all service areas through a level-based control unit; A step of providing service area-based control on the level-based data distribution strategy determined above through the strategy customization unit; A step of visualizing a data distribution map to represent the determined level-based data distribution strategy applied to each service area through a data distribution map provider; and A step of providing simulation results according to the final data distribution strategy determined by the service area and the level-based data distribution strategy through the simulation unit. A simulation-based decision support method for data distribution including
In paragraph 8, The step of determining the level of a data distribution strategy for edge storage utilization using level-based control applied globally across all service areas through the level-based control unit described above is: Determining the level of a data distribution strategy among multiple levels based on cloud storage utilization in the existing cloud environment prior to data distribution and edge storage utilization in all service regions. Simulation-based decision support method for data distribution.
In paragraph 8, The step of providing service area-based control on the level-based data distribution strategy determined through the strategy customization unit is: To reflect specific preferences and policies regarding data distribution, the entire service region is arbitrarily divided into multiple regions, and the system is customized to switch storage types between the cloud and edge of each divided region. Simulation-based decision support method for data distribution.
In paragraph 8, The step of visualizing a data distribution map to represent the determined level-based data distribution strategy applied to each service area through the data distribution map providing unit is: Providing a distributed map that displays regional information including segmented service areas, cloud storage utilization, edge storage utilization, region ID, used storage ID, data size of regional data, and population density representing the number of users located in that region. Simulation-based decision support method for data distribution.
In paragraph 8, The step of providing simulation results according to the final data distribution strategy determined according to the service area and the level-based data distribution strategy through the simulation unit is: Providing simulation results representing performance and cost indicators, including average response times classified by storage type, the percentage of messages with response speeds below a predetermined threshold, minimum and maximum response times during all message transmissions across the entire service area, the total number of users benefiting from edge storage, the latency difference between a cloud-only strategy and a selected end-data distribution strategy, the overall performance improvement rate, and the estimated cost of the strategy calculated based on the ratio of edge and cloud storage usage. Simulation-based decision support method for data distribution.
In Paragraph 12, The step of providing simulation results according to the final data distribution strategy determined according to the service area and the level-based data distribution strategy through the simulation unit is: To provide simulation results regarding the average response time classified by the above storage type and the message ratio where the response speed is below a predetermined standard, the average response time and the message ratio are provided in three categories according to the storage type: a type calculated using all message transmissions in the entire service area, a type calculated for areas using cloud storage, and a type calculated for areas using edge storage. Simulation-based decision support method for data distribution.
In Paragraph 12, The step of providing simulation results according to the final data distribution strategy determined according to the service area and the level-based data distribution strategy through the simulation unit is: To provide simulation results for the estimated cost of a strategy calculated based on the above-mentioned cloud storage usage ratio, the estimated cost is estimated using the total data size of the region using cloud storage, the total data size of the region using edge storage, the cost of using cloud storage within a predetermined period, and the cost of using edge storage per predetermined data capacity. Simulation-based decision support method for data distribution.
In a program stored on a computer-readable storage medium to execute a simulation-based decision support method for data distribution by a simulation-based decision support system for data distribution, A step of determining the level of a data distribution strategy for edge storage utilization using level-based control applied globally across all service areas through a level-based control unit; A step of providing service area-based control on the level-based data distribution strategy determined above through the strategy customization unit; A step of visualizing a data distribution map to represent the determined level-based data distribution strategy applied to each service area through a data distribution map provider; and A step of providing simulation results according to the final data distribution strategy determined by the service area and the level-based data distribution strategy through the simulation unit. A program stored on a computer-readable storage medium containing

Description

Simulation-based Decision Support Method and System for Data Distribution of Hyperlocal Services in Edge Cloud Environments The present invention relates to a simulation-based decision support method and system for data distribution of hyperlocal services in an edge cloud environment. Edge cloud environments emerged to address issues caused by the centralized resources of the cloud. In particular, for services with strong data locality, such as hyperlocal services, to effectively utilize edge cloud resources, data distribution between the cloud and the edge must be strategically determined. Existing research on data distribution methods has proposed optimization techniques that make decisions automatically. However, a survey of the development of prior art indicates that it is essential to reflect service-specific considerations in data distribution decisions. This highlights that existing automated optimization is insufficient for actual data distribution and that developer intervention is required. Furthermore, the development survey in this study indicates that developers struggle to specify performance and cost requirements for data distribution. FIG. 1 is a diagram showing the configuration of a simulation-based decision support system for data distribution of a hyperlocal service in an edge cloud environment according to an embodiment of the present invention. FIG. 2 is a flowchart illustrating a simulation-based decision support method for data distribution of a hyperlocal service in an edge cloud environment according to an embodiment of the present invention. FIG. 3 is a drawing showing a user interface of WYSIMWYG according to one embodiment of the present invention. FIG. 4 is a diagram illustrating the implementation process of WYSIMWYG according to one embodiment of the present invention. FIG. 5 is a diagram illustrating a user research process according to an embodiment of the present invention. FIG. 6 is a diagram showing a virtual service environment for user research according to an embodiment of the present invention. FIG. 7 is a drawing illustrating a user interface of a baseline access method according to an embodiment of the present invention. In order to solve problems discovered through formative surveys, the present invention proposes WYSIMWYG, a simulation-based decision support tool that enables developers to easily determine appropriate data distribution strategies for hyperlocal services in an edge cloud environment. Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings. FIG. 1 is a diagram showing the configuration of a simulation-based decision support system for data distribution of a hyperlocal service in an edge cloud environment according to an embodiment of the present invention. A decision support system (100) according to the present embodiment may include a processor (110), a bus (120), a network interface (130), a memory (140), and a database (150). The memory (140) may include an operating system (141) and a simulation-based decision support routine (142) for data distribution of hyperlocal services in an edge cloud environment. The processor (110) may include a level-based control unit (111), a strategy customization unit (112), a data distribution map provision unit (113), and a simulation unit (114). In other embodiments, the decision support system (100) may include more components than those of FIG. 1. However, it is not necessary to clearly illustrate most of the prior art components. For example, the decision support system (100) may include other components such as a display or a transceiver. Memory (140) is a computer-readable recording medium and may include a non-perishable permanent mass storage device such as RAM (random access memory), ROM (read only memory), and a disk drive. Additionally, program code for an operating system (141) and a simulation-based decision support routine (142) for data distribution of hyperlocal services in an edge cloud environment may be stored in memory (140). These software components may be loaded from a computer-readable recording medium separate from memory (140) using a drive mechanism (not shown). This separate computer-readable recording medium may include computer-readable recording media (not shown), such as a floppy drive, disk, tape, DVD/CD-ROM drive, or memory card. In another embodiment, software components may be loaded into memory (140) via a network interface (130) rather than a computer-readable recording medium. The bus (120) can enable communication and data transmission between components of the decision support system (100). The bus (120) can be configured using a high-speed serial bus, a parallel bus, a Storage Area Network (SAN), and/or other suitable communication technology. The network interface (130) may be a computer hardware component for connecting the decision support system (100) to a computer network. The network interface (130) ma