• The KIPS Transactions:PartC
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• v.15C no.2
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• pp.93-102
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• 2008

The network weather map and bandwidth time-series graph are popularly used to understand the current and past traffic condition of NSP, ISP, and enterprise networks. These systems collect traffic performance data from a SNMP agent running on the network devices such as routers and switches, store the gathered information into a DB, and display the network performance status in the form of a time-series graph or a network weather map using Web user interface. Most of current enterprise networks are constructed in the form of a hierarchical tree-like structure with multi-Gbps Ethernet links, which is quietly different from the national or world-wide backbone network structure. This paper focuses on the network weather map for current enterprise network. We start with the considering points in developing a network weather map system suitable for enterprise network. Based on these considerings, this paper proposes the best way of using SNMP in constructing a network weather map system. To prove our idea, we designed and developed a network weather map system for our campus network, which is also described in detail.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.391-399
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• 2005

In this paper we present an algorithm based on network flow techniques which provides a solution for a combinatorial problem. Then, in order to provide all the solutions of this problem, we make use of an algorithm that given the bipartite graph $G=(V_1 {\cup}{V_2},\;E,\;{\omega})$ outputs the enumeration of all bipartite matchings of given cardinality v and cost c.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.561-575
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• 2023

Brain network analysis has attracted the interest of neuroscience researchers in studying brain diseases. Magnetoencephalography (MEG) is especially proper for analyzing functional connectivity due to high temporal and spatial resolution. The application of graph theory for functional connectivity analysis has been studied widely, but research on network modeling for MEG still needs more. Temporal exponential random graph model (TERGM) considers temporal dependencies of networks. We performed the brain network analysis, including static/temporal network statistics, on two groups of epilepsy patients who removed the left (LT) or right (RT) part of the brain and healthy controls. We investigate network differences using Multiset canonical correlation analysis (MCCA) and TERGM between epilepsy patients and healthy controls (HC). The brain network of healthy controls had fewer temporal changes than patient groups. As a result of TERGM, on the simulation networks, LT and RT had less stable state than HC in the network connectivity structure. HC had a stable state of the brain network.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.321-328
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• 2013

In this paper, we present a technique for obtaining conflict-free schedules for real-time automation protocol for industrial Ethernet (RAPIEnet) switches. Mathematical model of the switch is obtained using graph theory. Initially network traffic entry and exit parts in a single RAPIEnet switch are identified, so that a bipartite conflict graph can be constructed. The obtained conflict graph is transformed to three kinds of matrices to be used as inputs for our simulation model, and selection of any of the matrix forms is application-specific. A greedy edge-coloring algorithm is used to schedule the network traffic and to solve the minimum coloring problem. After scheduling, empty slots are identified for forwarding the non real-time traffic of asynchronous devices. Finally, an algorithm for synchronizing the schedules of adjacent switches is proposed using edge-contraction and minors. All simulations were carried out using Matlab.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.31-34
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• 2022

The concept of locating chromatic number of graph is a development of the concept of vertex coloring and partition dimension of graph. The locating-chromatic number of G, denoted by χ_L(G) is the smallest number such that G has a locating k-coloring. In this paper we will discussed about the procedure for determine the locating chromatic number of Origami graph using Python Programming.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.3
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• pp.3-14
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• 1994

In this study, two reliability computational algorithms which respectively utilize a factoring method are proposed for a system represented by reliability block diagram. First, vertex factoring algorithm is proposed. In this algorithm, a reliability block diagram is considered as a network graph with vertex reliabilities. Second algorithm is mainly concerned with conversion of a reliabilities block diagram into a network graph with edge reliabilities. In this algorithm, the independence of edges is preserved by eliminating replicated edges, and in computing the reliability of a converted network graph, existing edge factoring algorithm is applied. The efficiency of two algorithms are compared for example systems with respect to computing times. The results shows that the second algorithm is shown to be more efficient than the first algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.306-311
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• 2007

본 논문에서는 Wireless Sensor Network상에서 전체 노드들의 lifetime을 증대시키기 위하여 "random한" 방식으로 cluster-head를 선출하는 LEACH 알고리즘이 가지고 있는 cluster-head 선출 과정에서 선출되는 수와 선출되는 노드들의 위치가 적절히 분산되지 않는 문제를 해결하기 위해 변형된 Graph Coloring 문제를 기반으로 노드의 위치 정보를 사용하지 않고 cluster-head를 적절히 분산하여 선출함으로써 효율적인 clustering을 하는 중앙처리 방식의 새로운 알고리즘 "GCCA : Graph Coloring based Clustering Algorithm for Wireless Sensor Networks" 을 제안한다. GCCA는 cluster-head가 선출되는 수를 일정하게 유지하고 선출되는 노드의 위치가 전체 network area에 적절히 분산되는 효과를 가져 옴으로 LEACH 알고리즘보다 에너지 효율이 증대됨을 실험을 통하여 보인다.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1188-1195
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• 2014

This paper presents an analytical technique for reliability evaluation of electrical distribution network (EDN) containing distributed generation (DG). Based on hierarchical levels of circuit breaker controlling zones and feeder sections, a directed-relation-graph (DRG) for an END is formed to describe the hierarchical structure of the EDN. The reliability indices of EDN and load points can be evaluated directly using the formed DRG, and the reliability evaluation of an EDN containing DGs can also be done without re-forming the DRG. The proposed technique incorporates multi-state models of photovoltaic and diesel generations, as well as weather factors. The IEEE-RBTS Bus 6 EDN is used to validate the proposed technique; and a practical campus EDN containing DG was also analyzed using the proposed technique.

• Industrial Engineering and Management Systems
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• v.10 no.4
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• pp.238-246
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• 2011

Given a directed graph, we can determine how the user's preference moves from one product item to another. In this graph called "preference transition network", each node represents the product item while its edge pointing to the other nodes represents the transition of user's preference. However, with the large number of items make the network become more complex, unclear and difficult to be interpreted. In order to address this problem, this paper proposes a visualization technique in preference transition analysis based on recency and frequency. By adapting these two elements, the semantic meaning of each item and its transition can be clearly identified by its different types of node size, color and edge style. The experiment in a sales data has shown the results of the proposed approach.

• Journal of Korea Multimedia Society
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• v.23 no.1
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• pp.24-30
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• 2020

As the number of internet-connected appliances and the variety of IoT services are rapidly increasing, it is hard to protect IT assets with traditional network security techniques. Most traditional network log analysis systems use rule based mechanisms to reduce the raw logs. But using predefined rules can't detect new attack patterns. So, there is a need for a mechanism to reduce congested raw logs and detect new attack patterns. This paper suggests enterprise security management for IoT services using graph and network measures. We model an event network based on a graph of interconnected logs between network devices and IoT gateways. And we suggest a network clustering algorithm that estimates the attack probability of log clusters and detects new attack patterns.