• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.915-922
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• 2003

The Grid is an infrastructure to connect heterogeneous resources that are scattered over areas with high-speed network and to cooperate with each other. To support Grid applications, network resources should be managed, since the network has to be safe and reliable. The Grid Monitoring Architecture Working Group (GMAWG) of the Global Grid Forum (GGF) proposed an effective architecture to be scalable across wide-area networks and encompass a large number of heterogeneous resources. In this paper, we describe the design and implementation of Grid network monitoring system based on the GMA for practical network management. By this system, network operations center can form a management system flexibly and scalably for Grid network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• Journal of Computing Science and Engineering
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• v.7 no.1
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• pp.44-52
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• 2013

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.1-9
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• 2006

As an effective solution to resolve complex computing problems and to handle geographically dispersed data sets, grid computing has been noticed. Grid computing separates an application to several parts and executes on heterogeneous computing platforms simultaneously. The most important problem in grid computing environments is to manage grid resources and to schedule grid resources. This paper proposes a grid transaction network model that is applicable for resource management and scheduling in grid computing environment and presents a grid resource bidding algorithm for grid users and grid resource providers. Using DEVSJAVA modeling and simulation, this paper evaluates usefulness and efficiency of the proposed model.

• Convergence Security Journal
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• v.2 no.2
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• pp.179-187
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• 2002

Grid is a infrastructure to connect heterogeneous resources that are scattered over areas with high-speed network and to cooperate with each other. To carry out Grid application, first, network resources should be managed, since the network has to be safe and reliable. GMA suggests an effective architecture for monitoring of resources that are scattered over a wide area. In this paper, basing on GMA, Grid network management system based on web for practical and general network management is designed. Grid network management system has to operate and connect various distributed management system. Using LDAP authentication, as one access system, Grid network management system maintain stability.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.639-645
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• 2005

GRID environments have been developed in distributed heterogeneous computing infrastructure for advanced science and engineering Therefore efficient scheduling algorithms for allocating user job to resources in the GRID environment are required. Many scheduling algorithms have been proposed, but these algorithms are not suitable for the GRID environment. That is the previous scheduling algorithm does not consider network bandwidth between multiple resources. In this paper, we propose a new scheduling algorithm for Global GRID environment and show that our algorithm has better performance than other scheduling algorithms through extensive simulation.

• 한국전산유체공학회:학술대회논문집
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• 2003.08a
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• pp.63-68
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• 2003

The Grid[1] is a communication service that collaborates dispersed high performance computers so that those can be shared and worked together. So, the Grid enables a researcher to analyze a huge-sized problem which was impossible by using local resources. However, diverse communication speeds among computing resources and heterogeneity of computing resources can reduce parallel efficiency in the Grid, The present paper focuses on the development of an efficient load balancing algorithm suitable for the Grid. Proposed algorithm classifies the whole processors into several groups with relatively faster communication speeds. Computational domain is firstly partitioned to each group and then to the processor level considering the performance of each processor. Developed algorithm is validated in the homogeneous system by comparing the present result with the result of equally partitioned meshes and then applied to the heterogeneous system. Additionally, the present algorithm is expanded to be able to solve the decomposed domains and applied to some problems.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.1
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• pp.111-119
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• 2022

This paper is about power transfer between heterogeneous systems in zero-energy buildings. Currently, electricity used in buildings, from renewable energy generation power in buildings, consists of alternating current networks. In order to use electricity, alternating current must be converted to direct current, which typically results in a loss of 10%. In order to solve this problem, research is needed to reduce power loss as much as possible by implementing both a DC network and an AC network in a zero-energy building. Therefore, in this paper, an inter-link converter capable of bidirectional power transfer between DC and AC networks applied to zero-energy buildings is developed. The structure of the inter-link converter to be developed was proposed and its feasibility was verified through simulations and experiments.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.608-611
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• 2004

Grid computing environment can be used to interconnect a wide variety of geographically distributed heterogeneous computing resources based on high-speed network. To make business service, it is necessary for Grid accounting system to measure the computational cost by consuming computer resources. To collect resource consumption data, and to keep track of process without needing to recompile kernel source, we use system call wrapping. By making use of this technique, we modifies system call table and replace existing system call to new system call that can monitor processes running in CPU kernel currently. Therefore we can measure user process resource usage for Grid accounting system.

• International Journal of Contents
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• v.6 no.4
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• pp.30-34
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• 2010

Effective job scheduling scheme is a crucial part of complex heterogeneous distributed systems. Gang scheduling is a scheduling algorithm for grid systems that schedules related grid jobs to run simultaneously on servers in different local sites. In this paper, we address grid jobs (gangs) schedule modeling using Stochastic reward nets (SRNs), which is concerned for static and dynamic scheduling policies. SRN is an extension of Stochastic Petri Net (SPN) and provides compact modeling facilities for system analysis. Threshold queue is adopted to smooth the variations of performance measures. System throughput and response time are compared and analyzed by giving reward measures in SRNs.