• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1117-1127
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• 2017

With the advent of Internet of Things (IoT), the number of devices connected to Internet has rapidly increased, but the security for IoT is still vulnerable. It is difficult to integrate existing security technologies due to generating a large amount of traffic by using different protocols to use various IoT devices according to purposes and to operate in a low power environment. Therefore, in this paper, we propose a normal network behavior profiling method based on big data analysis techniques. The proposed method utilizes a Hadoop/Hive for Big Data analytics and an R for statistical computing. Also we verify the effectiveness of the proposed method through a simulation.

• Journal of KIISE
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• v.42 no.4
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• pp.541-549
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• 2015

A large volume of continuously growing BGP data files can raise two technical challenges regarding scalability and manageability. Due to the recent development of the open-source distributed computing infrastructure, Hadoop, it becomes feasible to handle a large amount of data in a scalable manner. In this paper, we present a new Hadoop-based BGP tool (BGPdoop) that provides the scale-out performance as well as the extensible and agile analysis capability. In particular, BGPdoop realizes a query-based BGP record exploration function using Hive on the partitioned BGP data structure, which enables flexible and versatile analytics of BGP archive files. From the experiments for the scalability with a Hadoop cluster of 20 nodes, we demonstrate that BGPdoop achieves 5 times higher performance and the user-defined analysis capability by expressing diverse BGP routing analytics in Hive queries.

• Smart Media Journal
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• v.9 no.3
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• pp.52-58
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• 2020

The growing global energy demand has been the motivation for innovations for improved approaches on energy trade. The involvement of new energy market players known as prosumers have also enabled Peer-to-Peer (P2P) energy trade in microgrid communities. In this paper, a novel approach to energy trading based on Hive Strategy is proposed. The strategy aims to encourage prosumers to become workers that will meet the energy demands of consumers referred to as hives. The workers are selected based on their Prosumer Ratings (PR) and are ranked from the ones with the highest PR to the lowest. Using the PR, prosumers with the best energy consumption and generation behaviors are prioritized for energy trade. To test the proposed strategy, a simulation has conducted and the results show how the energy demand of the hive is met by the workers. Furthermore, an improvement in the pay-offs and PR of the workers are observed.

• Journal of agricultural medicine and community health
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• v.44 no.3
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• pp.138-143
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• 2019

Objectives: The purpose of this study was to assess the ergonomic risk factors in beekeeping, and to evaluate the effectiveness of assistive device hive lift. Methods: This study included 30 subjects of beekeeper in Pocheon, Korea. We assessed the ergonomic risk of main task in beekeeping with NLE, OWAS and evaluate the effectiveness of hive lift. We also surveyed prevalence of musculoskeletal symptoms among the subjects based on the Korea Working Condition Survey. Results: Moving to different floral origin, internal inspection of beehives, feeding syrup is the most burdensome to musculoskeletal system (NLE LI value=2~3. OWAS action category=4). The prevalence of musculoskeletal symptoms (lower and upper extremities) among the subjects was over 80 %. The introduction of assistive devices in the three hazardous tasks has dramatically reduced the risk by removing manual lifting hives (OWAS action category<1). Conclusions: Beekeeping is a heavy workload on the musculoskeletal system because it has a lot of manual lifting task. As a result of applying the hive lift, the burden could be reduced.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.511-517
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• 2022

Recently, due to rapid climate change, the population of honey bees has decreased, posing a great threat to the existence of the Earth's ecosystem. In particular, the colony collapse phenomenon in which bees disappeared nationwide in early 2022 had devastating consequences for beekeepers. In order to solve the problems of beekeeping due to climate change, it is urgent to develop a system that can monitor the situation inside the hive through various IoT sensors. This paper develops a system that can measure the activity of bees inside the hive and uses it to measure the number of times of entry and exit of the hive. The data measured by the developed system can be monitored in real time on a smartphone through the cloud server. The system developed in this paper can monitor the ecology of bees according to climate change and measure internal and external bee activities. Using this method, it is possible to check in advance for the colony collapse phenomenon in which bees disappeared in early 2022. This is very meaningful in that it presents an alternative that can identify the cause of the problem through early detection.

• Journal of Apiculture
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• v.32 no.3
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• pp.163-170
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• 2017

Small hive beetle (SHB, Aethina tumida Murray (Coleoptera: Nitidulidae) is a honeybee pest infesting combs and stores inside the hive. Contamination of the SHB on Apis mellifera colonies were firstly noticed on September 23, 2016, in Miryang City, Gyeongnam Province in Korea. After that, on October 5, 2016, we investigated the spatial distribution of SHB inside the hive and outside soil within the apiary. Total of 169 beehives were observed. We found all stages of SHB inside or outside of hives. 61% of hives infested with the adult SHB still had live honeybees whereas hives containing larval SHB did not have bees, implying colony destruction In hives with live bees, infestation density was higher as bee population became higher. Coefficient of dispersions (CD) showed significant clumped distribution of infestation among hives. CDs were much higher inside hive than outside soil. Our results indicates SHB could result in honeybee colony collapse it not managed properly. Also even during October, there are new infestation into honeybee colonies and every stage of SHB could still be able to develop. Further detailed analysis of this insect' adaptation in Koran environment could help guide the management strategies of the invaded new pest of honeybee.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.857-862
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• 2021

Recently, rapid climate change has had a significant impact on the bee ecosystem. The decrease in the number of bees and the change in the flowering period have a huge impact on the harvesting of beekeepers. Accordingly, attention is focused on smart beekeeping, which introduces IoT technology to beekeeping. According to the characteristics of beekeeping, it is impossible to continuously observe the beehive in the hive with the naked eye, and the condition of the hive is mostly dependent on knowledge from experience. Although a system that can measure partly through sensors such as temperature/humidity change inside the hive and measurement of the amount of CO2 is applied, there is no research on measuring the movement path and amount of movement of bees inside the beehive. Part of the migration of honeybees inside the hive can provide basic information to predict the most important cleavage time in beekeeping. In this study, we propose a device that detects the movement path of bees and measures and records data entering and exiting the hive in real time. The device proposed in this study was developed according to the honeycomb standard of the existing beehive so that beekeeping farms could use it. The development method used a photodetector that can detect the movement of bees to configure 16 movement paths and to detect the movement of bees in real time. If the measured honeybee movement status is utilized, the problem of directly observing the colony with the naked eye in order not to miss the swarming time can be solved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.699-700
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• 2013

This paper proposes a new visualization method based on cloud technique which uses internal relationship of user correlation and external relation of social network to visualize user relationship hierarchy. The proposed method use hadoop and hive for distribution storing and parallel processing which the result of calculation visualizes hierarchy graph using D3.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1102-1105
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• 2015

인터넷 발전이 가속화되고 SNS가 보급된 이후 과거와는 비교할 수 없을 정도로 큰 데이터 트래픽이 발생하고 있다. 기존의 DBMS는 이를 효과적으로 처리할 수 없었기 때문에 Hadoop과 같은 NoSQL이 탄생하였고, 최근 NoSQL 및 기존 SQL DBMS의 협업을 통해 유연하고 강력한 데이터 관리를 수행하는 연구가 진행되었다. 효율적인 질의 처리를 위한 대표적인 연구로 SQL 기반 분산 병렬 질의 처리 기법과 Hive등이 존재한다. 그러나 기존의 기법은 분산 병렬 환경을 고려하지 않아 SQL DBMS의 질의 결과를 효율적으로 Hive에 전송하지 못한다. 본 논문에서는 SQL DBMS에서 Hive로의 효율적인 SQL 데이터 이동을 위해 네트워크 비용을 최소화하는 기법을 제안하고, 제안하는 기법의 우수성을 제시한다.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.77-83
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• 2015

The storage and retrieval of multimedia data is becoming increasingly important in many application areas including record management, video(CCTV) management and Internet of Things (IoT). In these applications, the files containing multimedia that need to be stored and managed is tremendous and constantly scaling. In this paper, we propose a technique to retrieve a very large number of files, in multimedia format, using the Hadoop Framework. Our strategy is based on the management of metadata that describes the characteristic of files that are stored in Hadoop Distributed File System (HDFS). The metadata schema is represented in Hbase and looked up using SQL On Hadoop (Hive, Tajo). Both the Hbase, Hive and Tajo are part of the Hadoop Ecosystem. Preliminary experiment on multimedia data files stored in HDFS shows the viability of the proposed strategy.