• International journal of advanced smart convergence
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• v.10 no.3
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• pp.41-50
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• 2021

The purpose of this study is to analyze various energy platforms using data in the US and to suggest directions and implications. Some of the leading energy platforms are selected and analyzed based on the opening platform model. We focus on the case analysis of the US utility companies. In case of the horizontal open platform, Green Button sponsor's 'Connect My Data (CMD)' driven by the government invites the utility companies to jointly develop the sponsor's data solution. In case of the vertical open platform, the certification program 'Share My Data (SMD)' allows backward compatibility, because the technical improvement is minimal. The utility companies benchmark Amazon's three-sided market mediation and prefer platform and category exclusivity. For the former, they have data analytics companies like Enervee, Opower and for the latter, they have electronics manufactures and energy service providers (ESPs) like Distributed Energy Resources (DERs). Based on this US case study, we suggest the energy platforms to open their platform for renewable energy supply, energy conservation, high-efficiency products, and residential DER dissemination. To successfully implement the government's energy transition policy, the US platforms should be benchmarked as a business model. Especially, it is needed for them to coordinate a platform ecosystem. To ensure trust in the products and services offered on the marketplace platform, platform's certification program is helpful.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.3
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• pp.123-131
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• 2015

With a prospective of rapid deployment of IOT, a systematic approach to derive a business strategy for various possible scenarios of IOT applications is in great demand. In this paper, a conceptual framework that can be utilized for the purpose of assessing the market potential and of setting up an initial business strategy for IOT deployment is suggested. The framework consists of utilization of well-known value curve analysis, ecosystem analysis and house of quality tools. The value curve analysis is utilized to identify value-enhancing components of consumers as well as relative strengths of suppliers. The ecosystem analysis is used to identify relevant players of the supply chain and their mutual relationships. The house of quality is suitable for developing the initial business strategy of the supplier by converting consumer requirements identified by value curve analysis into technical requirements for the supplier. In this paper, we applied our proposed framework to two services that have high potentiality of being benefited by IOT: car-sharing service and telehealth service.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.125-138
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• 2016

Currently, there is increasing demand for weather information, however, providing meteorology and climate information is limited. In order to improve them, supporting the meteorology and climate big data platform use and training the meteorology and climate big data specialist who meet the needs of government, public agencies and corporate, are required. Meteorology and climate big data requires high-value usable service in variety fields, and it should be provided personalized service of industry-specific type for the service extension and new content development. To provide personalized service, it is essential to build the collaboration ecosystem at the national level. Building the collaboration ecosystem environment, convergence of marine policy and climate policy, convergence of oceanography and meteorology and convergence of R&D basic research and applied research are required. Since then, demand analysis, production sharing information, unification are able to build the collaboration ecosystem.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.238-247
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• 2020

This study has a purpose to analyze quantitatively whether ICT industry provides the qualitative indicator of employment to attract excellent human resources. We investigate the relationships of labor market conditions among ICT manufacturing, non-ICT manufacturing, ICT services, non-ICT services. Therefore, the quantitative and qualitative indicators of employment (wages, working hours, admission and turnover, involuntary retirement, and the duration years of job) are analyzed for the ICT industry and IT workers. In order to quantitatively analyze qualitative indicators such as employment status and longevity, we used employment statistics. In order to compensate for the limitations of employment insurance data, the comparison analysis with the survey data of economically active population of the National Statistical Office was conducted. As a result of this research, ICT service industry has to improve the working conditions of employees and establish an ecosystem for a lifelong career base to grow as a specialist, need to pursue an investigation for ICT worker career shift, and promote standard labor contracts. In addition, protection of employees, ICT-related job vision and social respect have to be perused.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.137-147
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• 2020

The Corona 19 pandemic is bringing a big change in the fields of politics, economy, society, culture, environment, ecosystem, science and technology, and business management activities and advertising. Therefore, in this study, after the Corona 19 pandemic, we predicted how the characteristics of future advertising and the types of future advertising will change, and we studied countermeasures. We used, a method of analyzing related literature and the Delphi Survey method predicting the future, as a research method. As expert Panel, the subject of the Delphi technique survey, we recruited 30 experts in the field of advertising and future fields with professional insight. We study to predict how the characteristics of future advertising and the types of future advertising will change according to changes in the advertising environment such as social changes, business changes, and consumer changes after the Corona 19 pandemic. In order to cope with these changes in future advertising, it is necessary to actively prepare the advertising industry and advertising experts. Therefore, we suggested countermeasures so that the advertising industry and advertising experts can understand and respond for future advertising changes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4063-4086
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• 2016

Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.61-70
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• 2020

The 4th Industrial Revolution is a revolutionary change through intelligence, big fusion and personalization, and the importance of sensor technology that is the basis of core technology is emerging. This study empirically analyzes the derivation of national strategy for R&D of sensor technology, and draws out the effect of technology internalization effort through strategic R&D activities on technical performance and further on national economy. The research and development results are calculated for each type of technology internalization, and the results of the research and development are verified to establish a structure that contributes to the national economic performance. As a national technology internalization strategy, considering its own R&D investment and joint research and development, we examine the impact of each factor on patents and GDP, focusing on causality and ripple effects. For causality analysis, Grandeur causality analysis shows that R&D investment and joint research and development in all countries have mutual causal relationship with GDP. The implications are as follows. First, it is necessary to establish the policy of national economic development through the internalization of technology and knowledge. Second, it is necessary to establish policies according to the type of knowledge internalization. Third, it will be necessary to create an ecosystem environment based on a virtuous relationship between knowledge internalization and national technology and economic development.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.75-94
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• 2011

The industrial ecosystem around the Internet services has been evolving since the Internet was first introduced. The Net Neutrality issue best represents the process of the evolution and presents an inevitable challenge that the industry should overcome. This paper deals with this structural change with the Two-Sided Market framework and provides a System Dynamics(SD) model to evaluate the economic implications of the net neutrality policy. In particular, our approach analyzes the policy impacts when two competing platforms (network providers) play a role of the platform in a typical two-sided market, which connects Content Providers(CPs) with users. Previous studies show that the indirect network externality between these two markets makes the entire system tip to one platform. When the multi-homing in the CP market is allowed as in our model, however, their argument may lose its validity. To examine the system behavior, conducted here is SD simulations of our model. The simulation results show that co-existence of the competing platforms persists with the network effects over a certain threshold. The net neutrality policy seems to lower the threshold based on our experimental outcomes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3384-3398
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• 2020

In recent years, as the environment has become an important issue in dealing with food, energy, and urban development, diverse environment-related applications such as environmental monitoring and ecosystem management have emerged. In such applications, automatic classification of animals using video or sound is very useful in terms of cost and convenience. So far, many works have been done for animal sounds classification using artificial intelligence techniques such as a convolutional neural network. However, most of them have dealt only with the sound of a specific class of animals such as bird sounds or insect sounds. Due to this, they are not suitable for classifying various types of animal sounds. In this paper, we propose a sound classification scheme based on a multi-feature network for classifying sounds of multiple species of animals. To do that, we first collected multiple animal sound datasets and grouped them into classes. Then, we extracted their audio features by generating mixed records and used those features for training. To evaluate the effectiveness of our scheme, we constructed an animal sound classification model and performed various experiments. We report some of the results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.8
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• pp.1368-1387
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• 2011

In recent years, ubiquitous and pervasive scenarios have emerged as a complex ecosystem where differentiated software/hardware components interoperate wirelessly and seamlessly. The goal is to enable users to continuously access services and contents, and to always get the best out of their current environment and available resources. In such dynamic and flexible scenarios, the need emerges for flexible and general solutions for continuous runtime self-reconfiguration and self-optimization of ubiquitous support software systems. This paper proposes a fully reconfigurable middleware approach that aims at reconfiguring complex software systems made up of heterogeneous off-the-shelf components from both functional and non-functional perspectives. Our middleware can also extend already existing and non-reconfigurable middleware/applications in an easy and flexible way, with no need to re-design them. The proposed design principles have been practically applied to the implementation of a runtime self-reconfigurable middleware called Off-The-Shelf Ready To Go (OTS-RTG), implemented on top of iPOJO. The reported experimental results both exhibit a limited overhead and show the wide applicability of the proposed solution to many application scenarios, including complex, industrial, Enterprise Service Bus-based ones.