• Annual Conference of KIPS
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• 2016.10a
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• pp.114-116
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• 2016

Recently, SDN and NFV technology have been developed actively and provide enormous flexibility of network provisioning. The future network services would generally involve many different types of services such as hologram games, social network live streaming videos and cloud-computing services, which have dynamic service requirements. To provision networks for future services dynamically and efficiently, SDN/NFV orchestrators must clearly understand the service requirements. Currently, network provisioning relies heavily on QoS parameters such as bandwidth, delay, jitter and throughput, and those parameters are necessary to describe the network requirements of a service. However it is often difficult for users to understand and use them proficiently. Therefore, in order to maintain interoperability and homogeneity, it is required to have a service abstraction layer between users and orchestrators. The service abstraction layer analyzes ambiguous user's requirements for the desired services, and this layer generates corresponding refined services requirements. In this paper, we present our initial effort to design a Smart Service Abstraction Layer (SmSAL) for future network architecture, which takes advantage of machine learning method to analyze ambiguous and abstracted user-friendly input parameters and generate corresponding network parameters of the desired service for better network provisioning. As an initial proof-of-concept implementation for providing viability of the proposed idea, we implemented SmSAL with a decision tree model created by learning process with previous service requests in order to generate network parameters related to various audio and video services, and showed that the parameters are generated successfully.

• Journal of Information Technology Services
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• v.16 no.2
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• pp.111-127
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• 2017

Computing Performance, sensor, storage, memory, and network costs have been steadily declining, and IoT services have recently become more active. The Internet of Things is linked with Big Data to create new business, and public institutions and corporations are hurry to import Internet of things. As the importance of the Internet of things has increased, the number of devices supporting the IoT has rapidly increased. With the development of the Internet of Things, various types of Internet services are being developed. For this reason, there is an increasing demand for IoT service designers and developers for IoT service case automatic search technology. IoT service designers can avoid duplication with existing services through service case retrieval and developers can save cost and time by combining existing reusable service equipment. This paper proposes IoT-Lite ontology for IoT and Semantic Web service to solve the above-mentioned problems. The existing ontologies for IoT, despite its many advantages, are not widely used by developers because it has not overcome the relatively slow drawbacks of increasing complexity and searching for development. To complement this, this study uses the IoT-Lite ontology introduced by W3C as a model and a semantic web service for automatic system retrieval. 3D camera, GPS, and 9-axis sensor, and IoT-Lite designed by IoT-Lite technique are integrated with the semantic technique and implemented directly.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.1-14
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• 2005

It is difficult to identify reusable and independent components in component-based development(CBD) process. Therefore existing methodologies have dealt the problem of component identification based on only developer's intuition and heuristics. As a result, it is difficult to identify the business components by common developers. Therefore, in this paper, we propose a new baseline and technique to identify the business components based on domain model such as use case diagrams, class diagrams, and sequence diagrams. proposed method identifies components through two phases; system component identification and business component identification. Especially, we consider structural characteristics as well as dependency characteristics according to methods call types and directions in identifying components. We also present a case study and comparative analysis and assessment to prove the practical use of our technique.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.234-243
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• 2000

We design a modified network architecture with condsidering current Internet network model and traffic characteristics, and propose EDCBT(Enhanced Dispersed Core-based Tree) multicast routing protocol, which enhances scalabity, reliability, end-to-end delay and resource utilization EDBCT adopts bidirectional dispersed shared trees and manages both of intradomain and interdomain multicast trees for a multicast group. Each regional multicast tree is estabilshed from its core router and they are interconnected by the operation between border routers on edges of each regional network. As a result, interdomain multicast tree can be easily established. We introduce a new concept named RBTS(Region-based Tree Switching), which dramatically enhances QoS and network utilization. Finally, protocol performance and the effect of core router location are evaluated with MIL3 OPNet network simulator, in terms of end-to-end delay, packet loss and throughput.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.414-423
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• 2009

Folksonomy, which is collaborative classification created by freely selected keywords, is one of the driving factors of the web 2.0. Folksonomy has advantage of being built at low cost while its weakness is lack of hierarchical or systematic structure in comparison with taxonomy. If we can build classifier that is able to classify web resources from collective intelligence in taxonomy, we can build taxonomy at low cost. In this paper, targeting folksonomy in Slashdot.org, we define a general model and show that collective intelligence, which can build classifier, really exists in folksonomy using a stability value. We suggest method that builds SVM classifier using stability that is result from this collective intelligence. The experiment shows that our proposed method managed to build taxonomy from folksonomy with high accuracy.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.586-597
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• 2014

The next generation mobile computing technology is recently attracting attention that smartphone and wearable device imbedded with various sensors are being deployed in the world. Existing activity and posture recognition research can be divided into two different ways considering feature of one's movement. While activity recognition focuses on catching distinct pattern according to continuous movement, posture recognition focuses on sudden change of posture and body orientation. There is a lack of research constructing a system mixing two separate patterns which could be applied in real world. In this paper, we propose a method to use both smartphone and wearable device to recognize activity and posture in the same time. To use smartphone and wearable sensor data together, we designed a pre-processing method and constructed recognition model mixing signal vector magnitude and orientation pattern features of vertical and horizontal. We considered cycling, fast/slow walking and running activities, and postures such as standing, sitting, and laying down. We confirmed the performance and validity by experiment, and proved the feasibility in real world.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.1-9
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• 2009

In heterogeneous and distributed computing environments, with an increasing number of Web services providing similar functionalities, the reliability of Web services is a critical decision factor. To fulfill the open business model such as cooperation among enterprises, several Web services can be composed into the upper level business transaction. In Web services composition, the reliability of services is more and more critical. Though each unit Web service can be reliable, the reliability of the composed service is not guaranteed. Thus a way to efficiently assess and select composed Web services is needed. In this paper, we define new metrics for measuring the trust value of Web services, and propose an evaluation method to predict the trustworthy degree of the composed services based on the metrics. We also define a conceptual framework to support optimal Web services selection based on the proposed trust evaluation method. By selecting using the quantitative measurement rather than intuitive selection of the service user, it allows the service users to select the high reliable service meeting their quality requirements well.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.4
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• pp.401-411
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• 2008

Folksonomy, which is created through the collaborative tagging from many users, is one of the driving factors of Web 2.0. Tags are said to be the web metadata describing a web document. If we are able to find the semantic subsumption relationships between tags created through the collaborative tagging, it can help users understand the metadata more intuitively. In this paper, targeting del.icio.us tag data, we propose a method named FolksoViz for deriving subsumption relationships between tags by using Wikipedia texts. For this purpose, we propose a statistical model for deriving subsumption relationships based on the frequency of each tag on the Wikipedia texts, and TSD(Tag Sense Disambiguation) method for mapping each tag to a corresponding Wikipedia text. The derived subsumption pairs are visualized effectively on the screen. The experiment shows that our proposed algorithm managed to find the correct subsumption pairs with high accuracy.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.301-305
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• 2008

Races must be detected for debugging OpenMP programs with directives, because they may cause unintended nondeterministic results of programs. Intel Thread Checker, an existing tool that can detects races, can not verify the existence of races and is often time-consuming and tends to require large space. To solve these problems, we developed a tool that verifies the existence of races using user requirements and analyzed model of programs. However, the tool does not have optimal performance in programs which have no synchronization for interthread coordination. This paper presents an optimal tool that applies the optimum labeling and protocol for program models without interthread coordination. For synthetic programs without interthread synchronization, the tool verifies races over 250 times faster than the previous tool on the average, even if the maximum parallelism increases in every case of which the number of total accesses are identical.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.106-114
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• 2010

Mesh parameterization is the process of finding one-to-one mapping between an input mesh and a parametric domain. It has been considered as a fundamental tool for digital geometric processing which is required to develop several applications of digital geometries. In this paper, we propose a novel 3D volume parameterization by means that a harmonic mapping is established between a 3D volume mesh and a unit solid cube. To do that, we firstly partition the boundary of the given 3D volume mesh into the six different rectangular patches whose adjacencies are topologically identical to those of a surface cube. Based on the partitioning result, we compute the boundary condition as a precondition for computing a volume mesh parameterization. Finally, the volume mesh parameterization with a low-distortion can be accomplished by performing a harmonic mapping, which minimizes the harmonic energy, with satisfying the boundary condition. Experimental results show that our method is efficient enough to compute 3D volume mesh parameterization for several models, each of whose topology is identical to a solid sphere.