公开(公告)号：US20230153317A1

公开(公告)日：2023-05-18

申请号：US17985994

申请日：2022-11-14

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Young Hwan KIM

IPC: G06F16/25 ,  G06F16/2453

CPC classification number: G06F16/252 ,  G06F16/24542

Abstract: There is provided a method for scheduling offloading snippets based on a large amount of DBMS task computation. A DB scheduling method according to an embodiment of the disclosure includes determining, by a DBMS, whether to offload a part of query computations upon receiving a query execution request from a client, generating, by the DBMS, an offloading code which is a code for offloading a part of the query computations, based on the received query, when offloading is determined, selecting one of the plurality of storages in which a DB is established, and delivering the offloading code. Accordingly, snippets which will be generated simultaneously are scheduled for CSDs, so that resources are equally utilized, a query execution time is reduced, and reliability on data processing is enhanced.

公开(公告)号：US20220078231A1

公开(公告)日：2022-03-10

申请号：US17467804

申请日：2021-09-07

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Young Hwan KIM

IPC: H04L29/08 ,  G06F9/50

Abstract: There is provided a cloud management method and apparatus for performing load balancing so as to make a service in a cluster that is geographically close in an associative container environment and has a good resource current status. The cloud management method according to an embodiment includes: monitoring, by a cloud management apparatus, available resource current statuses of a plurality of clusters, and selecting a cluster that owns a first service supported by a first cluster an available resource rate of which is less than a threshold value; calculating, by the cloud management apparatus, scores regarding an available resource current status and geographical proximity of each cluster; and performing, by the cloud management apparatus, load balancing of the first service, based on a result of calculating the scores. Accordingly, a delay in a response speed of a service that is required in a distributed environment can be minimized, and a service can be supported to be processed in a geographically close cluster through analysis of geographical closeness (proximity) between an access location where there is a user request and a cluster in which services are distributed.

公开(公告)号：US20240160612A1

公开(公告)日：2024-05-16

申请号：US18387626

申请日：2023-11-07

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Young Hwan KIM ,  Ri A CHOI

IPC: G06F16/21 ,  G06F9/48

CPC classification number: G06F16/217 ,  G06F9/4881

Abstract: There is provided a method for dividing query computations and scheduling for CSDs in a DB system in which a plurality of CSDs are used as a storage. A scheduling method according to an embodiment includes: selecting one of a plurality of scheduling polices; selecting a CSD to which snippets included in a group are delivered according to the selected scheduling policy; and delivering the snippets to the selected CSD, and the scheduling polices are polices for selecting CSDs to which snippets are delivered, based on different criteria. Accordingly, CSDs may be randomly selected according to user setting or a query execution environment, or an optimal CSD may be selected according to a CSD status or a content of an offload snippet, so that a query execution speed can be enhanced.

公开(公告)号：US20240160487A1

公开(公告)日：2024-05-16

申请号：US18388799

申请日：2023-11-10

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Young Hwan KIM ,  Ju Hyun KIL

IPC: G06F9/50

CPC classification number: G06F9/5038 ,  G06F9/5011 ,  G06F9/5072

Abstract: There is provided a cloud management method and apparatus for available GPU resource scheduling in a large-scale container platform environment. Accordingly, a list of available GPUs may be reflected through a GPU resource metric collected in a large-scale container driving (operating) environment, and an allocable GPU may be selected from the GPU list according to a request, so that GPU resources can be allocated flexibly in response to a GPU resource request of a user (resource allocation reflecting requested resources rather than 1:1 allocation).

公开(公告)号：US20240155815A1

公开(公告)日：2024-05-09

申请号：US18387222

申请日：2023-11-06

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Young Hwan KIM ,  Ki Cheol PARK

IPC: H05K7/20

CPC classification number: H05K7/20836 ,  H05K7/20727

Abstract: There is a method for applying a BMC analytical local fan control model in a rugged environment. A server chassis cooling fan control method according to an embodiment controls rotation speeds of cooling fans on a zone basis while identifying/managing a temperature distribution of an edge server chassis on a zone basis through BMC data analysis. Accordingly, a damage that may be caused by increased temperature of an edge server in a rugged environment may be minimized, and also, power consumption for cooling an edge server may be reduced.

公开(公告)号：US20170337253A1

公开(公告)日：2017-11-23

申请号：US15464798

申请日：2017-03-21

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Jae Gi SON ,  Chang Won PARK

IPC: G06F17/30

CPC classification number: G06F16/27

Abstract: Provided herein is an In-Memory DB connection support type scheduling method and system for real-time big data analysis in distributed computing environment. The data processing method according to an embodiment of the present disclosure analyzes data based on a distributed computing environment using a distributed system and dynamically alters a structure of a distributed DB constituting the distributed system based on the distributed computing environment. By this method, it is possible to secure concurrency adaptively to the distributed computing environment by dynamically managing the number of shards, and secure real-timeliness through TMO-based scheduling, thereby ultimately improving the speed/efficiency of big data analysis.

公开(公告)号：US20250155960A1

公开(公告)日：2025-05-15

申请号：US18897221

申请日：2024-09-26

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Young Hwan KIM

IPC: G06F1/3296

Abstract: There is provided a method for applying a learning model-based power saving model in an intelligent BMC. According to an embodiment, a BMC includes: a prediction module configured to predict future computing resource usage and a future CPU temperature from monitoring data on computing resources; a power capping module configured to control power capping based on the predicted future computing resource usage; a fan control module configured to control a cooling fan based on the predicted future CPU temperature. Accordingly, the BMC effectively/efficiently controls power capping and cooling fans based on prediction by interworking with the on-device AI, thereby reducing power consumption of a data center infrastructure effectively/efficiently.

公开(公告)号：US20240160963A1

公开(公告)日：2024-05-16

申请号：US18387230

申请日：2023-11-06

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Young Hwan KIM ,  Han Gyeol KIM

IPC: G06N5/04

CPC classification number: G06N5/04

Abstract: There is provided an intelligent BMC for predicting a fault by interworking on-device AI. A fault prediction method of a BMC according to an embodiment includes: collecting monitoring information regarding computing modules installed on a main board; calculating a FOFL from the collected monitoring data; and constructing an AI model related to the calculated FOFL and predicting a FOFL from the monitoring data. Accordingly, a fault occurring in various patterns may be predicted based on monitoring data by interworking with on-device AI.

公开(公告)号：US20220150110A1

公开(公告)日：2022-05-12

申请号：US17497098

申请日：2021-10-08

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Young Hwan KIM

IPC: H04L12/24 ,  H04L29/08

Abstract: There is provided an edge server system management and control method in a rugged environment. An edge server management apparatus according to an embodiment of the present disclosure includes: a communication unit configured to communicate with an edge server; and a processor configured to collect environmental information of the edge server through the communication unit, and to control an external environment of the edge server and to control resource configuration for an edge service, based on the collected environmental information. Accordingly, it is possible to manage/control an edge server system-based configuration module (a fan, a heater) even, and to operate an edge service by reconfiguring resources of the edge server in a severe industrial site.

公开(公告)号：US20220075665A1

公开(公告)日：2022-03-10

申请号：US17467963

申请日：2021-09-07

Applicant: Korea Electronics Technology Institute

Inventor： Jae Hoon AN ,  Young Hwan KIM

IPC: G06F9/50 ,  G06F9/38

Abstract: There are provided a cloud management method and a cloud management apparatus for rapidly scheduling arrangements of service resources by considering equal distribution of resources in a large-scale container environment of a distributed collaboration type. The cloud management method according to an embodiment includes: receiving, by a cloud management apparatus, a resource allocation request for a specific service; monitoring, by the cloud management apparatus, available resource current statuses of a plurality of clusters, and selecting a cluster that is able to be allocated a requested resource; calculating, by the cloud management apparatus, a suitable score with respect to each of the selected clusters; and selecting, by the cloud management apparatus, a cluster that is most suitable to the requested resource for executing a requested service from among the selected clusters, based on the respective suitable scores. Accordingly, for the method for determining equal resource arrangements between associative clusters according to characteristics of a required resource, a model for selecting a candidate group and finally selecting a cluster that is suitable to a required resource can be supported.