• Journal of Communications and Networks
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• v.18 no.3
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• pp.446-459
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• 2016

In this paper, we propose virtual direction multicast (VDM) for video multicast applications on peer-to-peer overlay networks. It locates the end hosts relative to each other based on a virtualized orientation scheme using real-time measurements. It builds multicast tree by connecting the nodes, which are estimated to be in the same virtual direction. By using the concept of directionality, we target to use minimal resources in the underlying network while satisfying users' quality expectations. We compare VDM against host multicast tree protocol.We simulated the protocol in a network simulator and implemented in PlanetLab. Results both from simulation and PlanetLab implementation show that our proposed technique exhibits good performance in terms of defined metrics.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1037-1052
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• 2019

We had developed in preceding study a classification model for the Korean pine and Larch with an accuracy of 98 percent using Hyperion and Sentinel-2 satellite images, texture information, and geometric information as the first step for tree species mapping in the inaccessible North Korea. Considering a share of major tree species in North Korea, the classification model needs to be expanded as it has a large share of Oak(29.5%), Pine (12.7%), Fir (8.2%), and as well as Larch (17.5%) and Korean pine (5.8%). In order to classify 5 major tree species, national forest type map of South Korea was used to build 11,039 training and 2,330 validation data. Sentinel-2 data was used to derive spectral information, and PlanetScope data was used to generate texture information. Geometric information was built from SRTM DEM data. As a machine learning algorithm, Random forest was used. As a result, the overall accuracy of classification was 80% with 0.80 kappa statistics. Based on the training data and the classification model constructed through this study, we will extend the application to Mt. Baekdu and North and South Goseong areas to confirm the applicability of tree species classification on the Korean Peninsula.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.324-330
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• 2021

Agriculture is one of the essential needs of human life on planet Earth. It is the source of food and earnings for many individuals around the world. The economy of many countries is associated with the agriculture sector. Lots of diseases exist that attack various fruits and crops. Apple Tree Leaves also suffer different types of pathological conditions that affect their production. These pathological conditions include apple scab, cedar apple rust, or multiple diseases, etc. In this paper, an automatic detection framework based on deep learning is investigated for apple leaves disease classification. Different pre-trained models, VGG16, ResNetV2, InceptionV3, and MobileNetV2, are considered for transfer learning. A combination of parameters like learning rate, batch size, and optimizer is analyzed, and the best combination of ResNetV2 with Adam optimizer provided the best classification accuracy of 94%.

• Information Systems Review
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• v.17 no.3
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• pp.135-157
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• 2015

Mobile giving platform is a new type of giving platform which offers donation service through mobile application. Mobile giving platform has developed differently from offline giving platform in the way that induces continuous donation. The purpose of this study is to investigate why mobile giving platform has adopted different strategy, and how it leads to continuous contribution. We conducted a case study with two successful mobile giving platforms; Bigwalk and Tree Planet. The analysis of the strategy is based on the construal level theory which explains the relationship between psychological distance and construal level. The result shows that the users' psychological distance toward giving platform has decreased with the environmental change, offline to mobile. Consequently the mobile giving platform offers services which form low level of construal for encouraging continuous participation. This finding suggests the importance of offering suitable construal level in services, and design guideline for mobile giving platforms.

• ETRI Journal
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• v.28 no.6
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• pp.709-720
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• 2006

In this paper, we suggest a simple and efficient multiple-forwarder-based file distribution method which can work with a tree-based application layer multicast. Existing multiple-forwarder approaches require high control overhead. The proposed method exploits the assumption that receivers join a session at different times. In tree-based application layer multicast, a set of data packets is delivered from its parent after a receiver has joined but before the next receiver joins without overlapping that of other receivers. The proposed method selects forwarders from among the preceding receivers and the forwarder forwards data packets from the non-overlapping data packet set. Three variations of forwarder selection algorithms are proposed. The impact of the proposed algorithms is evaluated using numerical analysis. A performance evaluation using PlanetLab, a global area overlay testbed, shows that the proposed method enhances throughput while maintaining the data packet duplication ratio and control overhead significantly lower than the existing method, Bullet.

• Journal of KIISE:Information Networking
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• v.33 no.4
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• pp.289-298
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• 2006

Algorithms for application-level multicast often use trees to deliver data from the source to the multiple receivers. With the tree structure, the throughput experienced by the descendant nodes will be determined by the performance of the slowest ancestor node. Furthermore, the failure of an ancestor node results in the suspension of the session of all the descendant nodes. This paper focuses on the transmission of data using multiple virtual forwarders, and suggests a scheme to overcome the drawbacks of the plain tree-based application layer multicast schemes. The proposed scheme elects multiple forwarders other than the parent node of the delivery tree. A receiver receives data from the multiple forwarders as well as the parent node and it can increase the amount of receiving data per time unit. The multiple forwarder helps a receiver to reduce the impact of the failure of an ancestor node. The proposed scheme suggests the forwarder selection algorithm to avoid the receipt of duplicate packets. We implemented the proposed scheme using MACEDON which provides a development environment for application layer multicast. We compared the proposed scheme with Bullet by applying the implementation in PlanetLab which is a global overlay network. The evaluation results show that the proposed scheme enhanced the throughput by 20 % and reduced the control overhead over 90 % compared with Bullet.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.22-37
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• 2013

Content distribution to a large number of concurrent clients stresses both server and network. While the server limitation can be circumvented by deploying server clusters, the network limitation is far less easy to cope with, due to the difficulty in measuring and balancing network load. In this paper, we use two useful network load metrics, the worst link stress (WLS) and the degree of interference (DOI), and formulate the problem as partitioning the clients into disjoint subsets subject to the server capacity constraint so that the WLS and the DOI are reduced for each session and also well balanced across the sessions. We present a network load-aware partition algorithm, which is practicable and effective in achieving the design goals. Through experiments on PlanetLab, we show that the proposed scheme has the remarkable advantages over existing schemes in reducing and balancing the network load. We expect the algorithm and performance metrics can be easily applied to various Internet applications, such as media streaming, multicast group member selection.