• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.60-68
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• 2012

In recent years, the requirements on the high quality environment monitoring by using the sensor nodes which can handle the multimedia data in WSN have been increased. However, because the volume of multimedia data is tremendous, the limited bandwidth of a wireless channel may incur the bottleneck of a system. To solve such a problem, most of the existing distributed multi-path routing protocols based on multimedia data just focused on overcoming the limited bandwidth in order to enhance the energy efficiency and the transmission rate. However, because the existing methods can not apply a key-based technique to encrypt the multimedia data, they are very weak for the security. In this paper, we propose a secure disjointed multipath routing scheme for multimedia data transmission. Since our proposed scheme divides multimedia data(eg. image) into pixels and sends them through disjointed multipath routing, it can provide security to the whole network without using the key-based method. Our experimental results show that our proposed scheme reduces about 10% the amount of the energy consumption and about 65% the amount of the missed data packets caused by malicious nodes over the existing methods on average.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.15-21
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• 2011

In the range-based localization, the localization accuracy will be high dependent on the accuracy of distance measurement between two nodes. The received signal strength(RSS) is one of the simplest methods of distance measurement, and can be easily implemented in a ranging-based method. However, a RSS-based localization scheme has few problems. One problem is that the signal in the communication channel is affected by many factors such as fading, shadowing, obstacle, and etc, which makes the error of distance measurement occur and the localization accuracy of sensor node be low. The other problem is that the sensor node estimates its location for itself in most cases of the RSS-based localization schemes, which makes the sensor network life time be reduced due to the battery limit of sensor nodes. Since beacon nodes usually have more resources than sensor nodes in terms of computation ability and battery, the beacon node based localization scheme can expand the life time of the sensor network. In this paper, therefore we propose a beacon node based localization algorithm using received signal strength(RSS) and path loss calibration in order to overcome the aforementioned problems. Through simulations, we prove the efficiency of the proposed scheme.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1427-1438
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• 2013

We have developed a 128-bit stream cipher algorithm composed of the 5-stage pipeline, capable of real-time processing, confidentiality and integrity. The developed stream cipher is a stream cipher algorithm that makes the final 128-bit ciphers through a whitening process after making the ASR 277 bit and SHACAL-2 and applying them to the CFB mode. We have verified the hardware performance of the proposed stream cipher algorithm with Modelsim 6.5d and Quartus II 12.0, and the result shows that the hardware runs at 33.34Mhz(4.27Gbps) at worst case. According to the result, the new cipher algorithm has fully satisfied the speed requirement of wireless Internet and sensor networks, and DRM environment. Therefore, the proposed algorithm with satisfaction of both confidentiality and integrity provides a very useful ideas.

• Smart Media Journal
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• v.8 no.3
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• pp.88-94
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• 2019

Livestock disease is a very important issue in the livestock industry because if livestock disease is not responded quickly enough, its damage can be devastating. To solve the issues involving the occurrence of livestock disease, it is necessary to diagnose in advance the status of livestock disease and develop systematic and scientific livestock feeding technologies. However, there is a lack of domestic studies on such technologies in Korea. This paper, therefore, proposes Livestock Disease Forecasting and Livestock Farm Integrated Control System using Cloud Computing to quickly manage livestock disease. The proposed system collects a variety of livestock data from wireless sensor networks and application. Moreover, it saves and manages the data with the use of the column-oriented database Hadoop HBase, a column-oriented database management system. This provides livestock disease forecasting and livestock farm integrated controlling service through MapReduce Model-based parallel data processing. Lastly, it also provides REST-based web service so that users can receive the service on various platforms, such as PCs or mobile devices.

• Journal of KIISE
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• v.44 no.2
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• pp.213-222
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• 2017

The Internet of Things (IoT) technology is rapidly developing in recent years, and is applicable to various fields. A smart factory is one wherein all the components are organically connected to each other via a WSN, using an intelligent operating system and the IoT. A smart factory technology is used for flexible process automation and custom manufacturing, and hence needs adaptive network management for frequent network fluctuations. Moreover, ensuring the timeliness of the data collected through sensor nodes is crucial. In order to ensure network timeliness, the power consumption for information exchange increases. In this paper, we propose an IEEE 802.15.4e DSME-based distributed scheduling algorithm for mobility support, and we evaluate various performance metrics. The proposed algorithm adaptively assigns communication slots by analyzing the network traffic of each node, and improves the network reliability and timeliness. The experimental results indicate that the throughput of the DSME MAC protocol is better than the IEEE 802.15.4e TSCH and the legacy slotted CSMA/CA in large networks with more than 30 nodes. Also, the proposed algorithm improves the throughput by 15%, higher than other MACs including the original DSME. Experimentally, we confirm that the algorithm reduces power consumption by improving the availability of communication slots. The proposed algorithm improves the power consumption by 40%, higher than other MACs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.175-186
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• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.