• ETRI Journal
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• v.27 no.4
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• pp.355-366
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• 2005

Automatic discovery of physical topology plays a crucial role in enhancing the manageability of modern metro Ethernet networks. Despite the importance of the problem, earlier research and commercial network management tools have typically concentrated on either discovering logical topology, or proprietary solutions targeting specific product families. Recent works have demonstrated that network topology can be determined using the standard simple network management protocol (SNMP) management information base (MIB), but these algorithms depend on address forwarding table (AFT) entries and can find only spanning tree paths in an Ethernet mesh network. A previous work by Breibart et al. requires that AFT entries be complete; however, that can be a risky assumption in a realistic Ethernet mesh network. In this paper, we have proposed a new physical topology discovery algorithm which works without complete knowledge of AFT entries. Our algorithm can discover a complete physical topology including inactive interfaces eliminated by the spanning tree protocol in metro Ethernet networks. The effectiveness of the algorithm is demonstrated by implementation.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.448-450
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• 2005

A ubiquitous network allows all users to access and exchange information of any kind freely at any time, from anywhere, and from any appliance through the use of broadband and mobile access. Bluetooth commincation can provide the missing wireless extension to the heterogeneous network, allowing a more ubiquitous access. In this point of view, the BT specifications define ways for which each BT device can set up multiple connections with neighboring devices to communicate in a multi-hop fashion. this paper provides insights on the Bluetooth technology and on some limitations of the scatternet formations. so that, we describe a new multi-hop routing protocol for the establishment of scatternets. this protocol defines rules for forming a multi-hop topology in two phases. the first phase, topology discovery, concerns the discovery of the node's depth from a root node initiating inquiry process. the second phase forms scatternet topology based on the result of topology discovery.

• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.905-916
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• 2004

Self-organizing hierarchical ad hoc network (SOHAN) is a new ad-hoc network architecture designed to improve the scalability properties of conventional 'flat' ad hoc networks. This network architecture consists of three tiers of ad-hoc nodes, i.e.. access points, forwarding nodes and mobile nodes. This paper presents a topology discovery and routing protocol for the self-organization of SOHAN. We propose a cross-layer path metric based on link quality and MAC delay which plays a key role in producing an optimal cluster-based hierarchical topology with high throughput capacity. The topology discovery protocol provides the basis for routing which takes place in layer 2.5 using MAC addresses. The routing protocol is based on AODV with appropriate modifications to take advantage of the hierarchical topology and interact with the discovery protocol. Simulation results are presented which show the improved performance as well as scalability properties of SOHAN in terms of through-put capacity, end-to-end delay, packet delivery ratio and control overhead.

• KNOM Review
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• v.23 no.1
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• pp.1-9
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• 2020

With the rapid development of science and technology in recent years, the network environment are growing, and a huge amount of traffic is generated. In particular, the development of 5G networks and edge computing will accelerate this phenomenon. However, according to these trends, network malicious behaviors and traffic overloads are also frequently occurring. To solve these problems, network administrators need to build a network management system to implement a high-speed network and should know exactly about the connection topology of network devices through the network management system. However, the existing network topology discovery method is inefficient because it is passively managed by an administrator and it is a time consuming task. Therefore, we proposes a method of network topology discovery according to the amount of in and out network traffic. The proposed method is applied to a real network to verify the validity of this paper.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1195-1210
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• 2012

In this paper, we propose a new signaling protocol as an extension of Generalized Multi-Protocol Label Switching (GMPLS) based PCE protocol for control carrier ethernet. The proposed protocol is not only compatible with the GMPLS PCE standard protocol, but also provides the topology discovery and configuration. In order to verify interoperability, we implement the proposed protocol as well as the system integrating functions including commercial system for testbed. In addition, we have simulated topology discovery test for proposed protocol performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.191-210
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• 2011

Topology management, which includes neighbor discovery, tracking and updating, is a key area that need to be dealt with appropriately to increase network performance. The use of directional antenna in Wireless Mesh Networks is beneficial in constructing backbone networks viewing the properties of directional antenna. The backbone links must be robust to obtain better network performance. In this paper, a simple yet effective topology protocol is presented that performs well compared to its predecessors. Our protocol constructs the topology with the constraints in the number of links per node. The full topology is constructed in two phases. The resultant topology is termed as Web-topology. The topology formed is robust, efficient, and scalable.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.4 s.334
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• pp.7-14
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• 2005

Earlier researches have typically concentrated on discovering IP network topology, which implies that the connectivity of all Ethernet devices is ignored. But automatic discovery of Physical topology Plays a crucial role in enhancing the manageability of modem Metro Ethernet mesh networks due to the benefits of Ethernet services, including: Ease of use, Cost Effectiveness and flexibility. Because of proprietary solutions targeting specific product families and related algorithm which depends on Layer 2 forwarding table information it is impossible to discover physical topology in the Ethernet mesh networks. To cope with these shortcomings, in this paper we propose a novel and practical algorithmic solution that can discover accurate physical topology in the Ethernet mesh networks. Our algorithm divides the Ethernet mesh networks into bridged networks and host networks and those bridges located in boundary are named edge bridges. Our algorithm uses the standard spanning tree protocol MIB information for the bridged networks and uses the standard Layer 2 forwarding table MIB information for the host networks. As using the standard MIB information to discover physical topology we can offer interoperability guarantee in the Ethernet mesh networks composed of the various vendors' products.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.1102-1109
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• 2017

In Train Control Network(TCN), to support advanced services beyond control applications, it was revised to support high speed ethernet as IEC 61375-2-5(ETB) and IEC 61375-3-4(ECN). And Train Topology Discovery Protocol(TTDP) was included by which train-consist can be automatically configured. Meanwhile, to adopt wireless LAN as an next onboard network, TTDP need to be modified to reflect the characteristics of WLAN. This paper proposed a TTDP for WLAN using transmission power control and the number of HELLO-ACK handshake. And it determined whether the TTDP executed using the two WLAN interfaces having different bandwidths is correct or not. The proposed TTDP can allow to reduce interference from other nodes. For evaluation of performance of TTDP, NS-2 was used. The evaluation result shows the high reliability of the TTDP in wireless environment.

• KNOM Review
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• v.24 no.2
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• pp.48-55
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• 2021

Ethereum is an open software platform based on blockchain technology that enables the construction and distribution of distributed applications. Ethereum uses a fully distributed connection method in which all participating nodes participate in the network with equal authority and rights. Ethereum networks use Kademlia-based node discovery protocols to retrieve and store node information. Ethereum is striving to stabilize the entire network topology by implementing node discovery protocols, but systems for monitoring are insufficient. This paper develops a WireShark dissector that can receive packet information in the Ethereum node discovery process and provides network packet measurement results. It can be used as basic data for the research on network performance improvement and vulnerability by analyzing the Ethereum node discovery process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.9
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• pp.561-569
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• 2014

In wireless ad hoc networks, neighbor discovery is essential in the network initialization and the design of routing, topology control, and medium access control algorithms. Therefore, efficient neighbor discovery algorithms should be devised for self-organization in wireless ad hoc networks. In this paper, we propose a probabilistic neighbor discovery (PND) algorithm, which aims at reducing the neighbor discovery time by adjusting the transmission probability of advertisement messages through the multiplicative-increase/multiplicative-decrease (MIMD) policy. To further improve PND, we consider the collision detection (CD) capability in which a device can distinguish between successful reception and collision of advertisement messages. Simulation results show that the transmission probabilities of PND and PND with CD converge on the optimal value quickly although the number of devices is unknown. As a result, PND and PND with CD can reduce the neighbor discovery time by 15.6% to 57.0% compared with the ALOHA-like neighbor discovery algorithm.