• Annual Conference of KIPS
• /
• 2007.11a
• /
• pp.954-957
• /
• 2007

AODV 에서는 RREQ 메시지 전송을 통해 라우팅 경로를 설정한다. Ad-hoc 네트워크에서 노드가 자주 이동하거나 전송 지연 시간이 클 경우 RREQ 메시지 발생이 증가한다. 이러한 네트워크 변동에 따른 RREQ 메시지 발생 증가는 결과적으로 데이터 패킷 수신율을 저하시킬 뿐만 아니라, 노드의 에너지 소모율도 증가시킨다. 본 논문에서는 네트워크 토폴로지 변동 상황을 감지하여 AODV 에서의 RREQ 메시지 발생 빈도를 효과적으로 조절하는 알고리즘을 제안하였다. 제안된 알고리즘을 50개의 노드가 10m/s 이하의 속도로 무작위로 이동하는 Ad-hoc 네트워크에 적용한 결과, 기존 AODV 알고리즘에 비해 RREQ 메시지 발생 빈도가 25% 감소하였다. 뿐만 아니라 RREP 패킷과 RERR 패킷 역시 각각 26% 및 31%씩 감소하였다. 모든 종류의 메시지 발생 빈도 수가 감소함에 따라 데이터 패킷 수신율은 3% 증가했으며, 에너지 소모율 역시 13% 감소하였다.

• The KIPS Transactions:PartC
• /
• v.14C no.3 s.113
• /
• pp.229-238
• /
• 2007

Sensor networks consist of many tiny sensor nodes that collaborate among themselves to collect, process, analyze, and disseminate data. In sensor networks, sensor nodes are typically powered by batteries, and have limited computing resources. Moreover, the redeployment of nodes by energy exhaustion or their movement makes network topology change dynamically. These features incur problems that do not appear in traditional, wired networks. Security in sensor networks is challenging problem due to the nature of wireless communication and the lack of resources. Several efforts are underway to provide security services in sensor networks, but most of them are preventive approaches based on cryptography. However, sensor nodes are extremely vulnerable to capture or key compromise. To ensure the security of the network, it is critical to develop suity mechanisms that can survive malicious attacks from "insiders" who have access to the keying materials or the full control of some nodes. In order to protect against insider attacks, it is necessary to understand how an insider can attack a sensor network. Several attacks have been discussed in the literature. However, insider attacks in general have not been thoroughly studied and verified. In this paper, we study the insider attacks against routing protocols in sensor networks using the Ad-hoc On-Demand Distance Vector (AODV) protocol. We identify the goals of attack, and then study how to achieve these goals by modifying of the routing messages. Finally, with the simulation we study how an attacker affects the sensor networks. After we understand the features of inside attacker, we propose a detect mechanism using hop count information.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.1C
• /
• pp.89-96
• /
• 2012

Since tactical robots are going to be grown and tactical data communications will be more network-centric, the reliability of wireless tactical data networks is going to be very important in the future. However, the connectivity of such wireless tactical data networks can be extremely uncertain in practical circumstances. In this paper, we propose a searching technique to find out the weak boundary area of the network connectivity using a small UAV(unmanned aerial vehicle) which has a simple polling access function to wireless nodes on the ground in wireless tactical data networks. The UA V calculates the network topology of the wireless tactical data networks and coverts it to the Lapalcian matrix. In the proposed algorithm, we iteratively search the eigenvalues and find a minimum cut in the network resulting in finding the weak boundary of the connectivity for the wireless tactical data networks. If a UAV works as a relay nodes for the weak area, we evaluate that the throughput performance of the proposed algorithm outperforms star connection method and MST(minimum Spanning Tree) connection method. The proposed algorithm can be applied for recovering the connectivity of wireless tactical data networks.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.3B
• /
• pp.112-122
• /
• 2008

Basing on Piconet, The Bluetooth System forms network and transmits data. There is one Master and maximum 7 Slave bluetooth devices in one piconet. A job scheduler performed by Master bluetooth device, gives the chance of data transmission to Slave bluetooth devices, which connected to Master, using polling method in piconet. The maximum data rate is 723.2 kb/s when it uses ACL link with DH5 packet type in a piconet which is constructed by two bluetooth devices. However, if there are one master and two slave devices in a piconet, then the maximum data rate is reduced to a half(361.6kb/s), because a master device has to support same data rate for all connected devices. And, there is the defect in scatternet when data transmission rate becomes low(Maximum rate: 302.2kb/s). This paper proposals the new ad-hoc network topology called "DoublePico"for overcome the low data transmission in scatternet which is constructed by piconets. The method of doublepico that represented in this paper makes high data transfer rate(Maximum rate: 457.57kb/s) in bluetooth ad-hoc networks.

• Journal of KIISE:Information Networking
• /
• v.37 no.5
• /
• pp.396-402
• /
• 2010

The tracking of current location of residents is an essential requirement for context-aware service of smart houses. This paper presents a wireless sensor network system which could detect location transition such as entrance and exit to a room and also identify the user who passed the room, without duty of wearing any sort of tag. We designed new sensor node to solve the problem of short operation lifetime of previous work[1] which has two pyroelectric infrared (PIR) sensors and an ultrasonic sensor, as well as a 2.4 GHz radio frequency wireless transceiver. The proposed user identification method is to discriminate a person based on his/her height by using an ultrasonic sensor. The detection idea of entering/exiting behavior is based on order of triggering of two PIR sensors. The topology of the developed wireless sensor network system is simple star structure in which each sensor node is connected to one sink node directly. We evaluated the proposed sensing system with a set of experiments for three subjects in a model house. The experimental result shows that the averaged recognition rate of user identification is 81.3% for three persons. and perfect entering/exiting behavior detection performance.

• The Journal of Engineering Geology
• /
• v.31 no.1
• /
• pp.1-17
• /
• 2021

It is important to evaluate the fracture network in a rock volume because fractures control the ground conditions and fluid flow characteristics. Therefore, various attempts have been made to quantify fracture networks to better understand ground and flow conditions. The use of fracture density alone (a quantitative parameter based on geometric analysis) does not fully explain the evolution of fracture networks, or quantify the spatial relationship (e.g. connectivity) of fractures in a rock mass. Therefore, the need for fracture network characterization based on topological analysis has recently emerged. In Korea however, the topological analysis of fracture networks within a rock mass has rarely been studied. As such, the definition of the topological analysis of fracture networks and the graph theory related to the topological analysis are briefly summarized in this study. We also introduce an application method for these analyses to fracture characterization. If the topological method is used for the analysis of fracture networks, it can also be adopted to analyze fluid flow characteristics of groundwater, characterize petroleum reservoirs, and analyze the evolution of a fracture network. In addition, topological analysis can be useful for site selection of major facilities such as nuclear waste disposal sites because it can be used to evaluate the stability of the potential sites.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.3
• /
• pp.227-237
• /
• 2022

The most critical factors for detecting changes in very high-resolution satellite images are building positional inconsistencies and relief displacements caused by satellite side-view. To resolve the above problems, additional processing using a digital elevation model and deep learning approach have been proposed. Unfortunately, these approaches are not sufficiently effective in solving these problems. This study proposed a change detection method that considers both positional and topology information of buildings. Mask R-CNN (Region-based Convolutional Neural Network) was trained on a SpaceNet building detection v2 dataset, and the central points of each building were extracted as building nodes. Then, triangulated irregular network graphs were created on building nodes from temporal images. To extract the area, where there is a structural difference between two graphs, a change index reflecting the similarity of the graphs and differences in the location of building nodes was proposed. Finally, newly changed or deleted buildings were detected by comparing the two graphs. Three pairs of test sites were selected to evaluate the proposed method's effectiveness, and the results showed that changed buildings were detected in the case of side-view satellite images with building positional inconsistencies.

• Journal of Korea Water Resources Association
• /
• v.55 no.11
• /
• pp.855-863
• /
• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

• Monthly Notices of the Royal Astronomical Society
• /
• v.483 no.3
• /
• pp.3950-3970
• /
• 2019

We investigate the spatial distribution of Ly α-emitting galaxies (LAEs) at z ≈ 2.67, selected from the NOAO Deep Wide-Field Survey, using two-point statistics and topological diagnostics adopted from network science. We measure the clustering length, r₀ ≈ 4 h^-1 Mpc, and the bias, b_LAE = 2.2^+0.2_-0.1. Fitting the clustering with halo occupation distribution (HOD) models results in two disparate possibilities: (1) where the fraction of central galaxies is <1 per cent in haloes of mass >10¹² M_⊙ and (2) where the fraction is ≈20 per cent. We refer to these two scenarios as the 'Dusty Core Scenario' for Model#1, since most of the central galaxies in massive haloes are dead in Ly α emission, and the 'Pristine Core Scenario' for Model#2, since the central galaxies are bright in Ly α emission. Traditional two-point statistics cannot distinguish between these disparate models given the current data sets. To overcome this degeneracy, we generate mock catalogues for each HOD model using a high-resolution N-body simulation and adopt a network statistics approach, which provides excellent topological diagnostics for galaxy point distributions. We find three topological anomalies from the spatial distribution of observed LAEs, which are not reproduced by the HOD mocks. We find that Model#2 matches better all network statistics than Model#1, suggesting that the central galaxies in >10¹² h^-1 M_⊙ haloes at z ≈ 2.67 need to be less dusty to be bright as LAEs, potentially implying some replenishing channels of pristine gas such as the cold mode accretion.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.16 no.2
• /
• pp.251-258
• /
• 1998

The purpose of this study is to develop the District-level Planning Support System (DPSS) by using GIS. The district-level planning which is related for district-level control of city, needs the various parcel-level information which is composing the urban physical environment. The information has to be stored and analyzed for recognizing the study area, then the district-level planning will be efficiently managed. The use of GIS in the process of district-level planning is restricted for the creation of thematic map. GIS is not used for the analysis of spatial patterns and planning process. This study evaluates the characteristics of current district-level planning and the basic components of urban physical environment. And the database model is built. The topology among components is defined by using the spatial relationship. Then the spatial query machine for district-level planing is developed by using ArcView 3.1, Avenue and Dialog Extension. This spatial query machine is applied for case study. This study shows 1) the possibility of the district-level planning support system for analyzing spatial relationship, 2) the needs of the up-to-date topographic map showing current building's footlines and the complete integration with cadastral maps, it will reduce the uncertainty in the spatial decision making process, 3) the methodology for the construction of spatial decision making rules, 4) the further study for the using of raster, network, image and three dimension data.