Abstract:
There is provided a method of data replication between management modules in a rugged environment. According to an embodiment of the present disclosure, an edge server management module replication method includes: a step of collecting, by a first management module, environment information of an edge server; a step of managing, by the first management module, the edge server, based on the collected environmental information; a first storage step of storing, by the first management module, management data related to the edge server in a repository of the first management module; and a second storage step of storing, by a second management module, the management data stored at the first storage step in a repository of the second management module. Accordingly, the time required to respond to an error occurring in a severe industrial site can be minimized through data replication processing between replicated edge management modules in a rugged environment, so that a continuous edge service can be provided without interruption.
Abstract:
A module type PDU for different power supply is provided. The PDU includes: a base configured to transmit different kinds of power; and a multi socket module connected with the base to transmit one kind of power to devices plugs of which are connected to the multi socket module. Accordingly, double power supply can be achieved through a single PDU and thus a PDU installing cost can be reduced, and, as the number of PDUs is reduced, electric equipments can be simplified.
Abstract:
A method for generating firmware by allowing a developer to freely select functions to be included in firmware installed on a main board of a server, and by building a firmware image is provided. The method for generating firmware includes: listing functions that are allowed to be included in firmware installed on a main board of a server; receiving selection of at least one of the listed functions from a user; and building a firmware image including the functions selected by the user.Accordingly, since a firmware image is built by a developer freely selecting functions to be included in firmware installed on a main board of a server, firmware optimized for requirements of the developer can be generated.
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.
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.
Abstract:
A cloud management method and a cloud management device are provided. The cloud management method receives a resource allocation request for a specific service, calculates an idle resource current state score regarding each resource of each node of each cluster by monitoring virtual resource usage current states of a plurality of nodes included in a plurality of clusters, and determines a node to allocate resources for executing the requested specific service, based on the calculated idle resource current state score. Accordingly, a score is given to a resource current state of an associated cluster, and a resource candidate group is selected in response to a service scheduling request, based on the score, and an optimal node is selected based on required resources necessary for the service.
Abstract:
There is provided a query execution method in a DB system in which a plurality of CSDs are used as a storage. According to an embodiment, a query execution method includes: generating snippets for offloading a part of query computations for a query received from a client to CSDs; scheduling the generated snippets for the CSDs; collecting results of offloading; and merging the collected results of offloading. Accordingly, by dividing query computations, offloading, and processing in parallel, while processing query computations that are inappropriate for offloading by a DBMS, a query request from a client can be executed effectively and rapidly.
Abstract:
A policy-based orchestration method in an exascale class cloud storage environment, and a storage system using the same are provided. The storage orchestration method includes: allocating a combination of different storages to a user as a storage space; and adjusting the combination according to a user's using pattern. Accordingly, the storage can be operated optimally and autonomically, and thus can be operated efficiently and economically.
Abstract:
There are provided a method and an apparatus for cloud management, which selects optimal resources based on graphic processing unit (GPU) resource analysis in a large-scale container platform environment. According to an embodiment, a GPU bottleneck phenomenon occurring in an application of a large-scale container environment may be reduced by processing partitioned allocation of GPU resources, rather than existing 1:1 allocation, through real-time GPU data analysis (application of a threshold) and synthetic analysis of GPU performance degrading factors.
Abstract:
A cloud management method and a cloud management device are provided. The cloud management method determines whether a plurality of pods are overloaded, identifies resource usage current states of a cluster and a node, and determines a method of scaling resources of a specific pod that is overloaded from among the plurality of pods, according to the resource usage current states of the cluster and the node, and scales the resources of the specific pod according to the determined method. Accordingly, scaling for uniformly extending resources of a node and a pod in a cluster horizontally and vertically can be automatically performed.