• KIPS Transactions on Computer and Communication Systems
• /
• v.7 no.1
• /
• pp.9-18
• /
• 2018

Enhancing performance of big data analytics in distributed environment has been issued because most of the big data related applications such as machine learning techniques and streaming services generally utilize distributed computing frameworks. Thus, optimizing performance of those applications at Spark has been actively researched. Since optimizing performance of the applications at distributed environment is challenging because it not only needs optimizing the applications themselves but also requires tuning of the distributed system configuration parameters. Although prior researches made a huge effort to improve execution performance, most of them only focused on one of three performance optimization aspect: application design, system tuning, hardware utilization. Thus, they couldn't handle an orchestration of those aspects. In this paper, we deeply analyze and model the application processing procedure of the Spark. Through the analyzed results, we propose performance optimization schemes for each step of the procedure: inner stage and outer stage. We also propose appropriate partitioning mechanism by analyzing relationship between partitioning parallelism and performance of the applications. We applied those three performance optimization schemes to WordCount, Pagerank, and Kmeans which are basic big data analytics and found nearly 50% performance improvement when all of those schemes are applied.

• Journal of The Korean Association For Science Education
• /
• v.41 no.3
• /
• pp.267-281
• /
• 2021

The shift in the perspective on learning as participation draws attention to learners' identity work. This manuscript foregrounds the ongoing and fluid processes of identity, and focuses on the structure surrounding learners where identity work occurs and the expression of individual agency. From the perspective of learning as participation, we introduce Holland et al. (1998) identity-in-practice theory, as the theoretical lens that dialectically describes structure, agency and identity. The concepts representing this theory are 'figured world', 'positionality' and 'authoring self'. The figured world is a web of meaning encompassing the continuous construct/reconstruct through human actions and also exerts as the social force that shapes human actions. 'Positionality' on the other hand, means an understanding of one's social position in the world. The notion of 'authoring self', is a dimension that synthesizes the above two concepts, which describes the improvisation of one's self through the orchestration and collaboration of various social voices. Next, we analyzed and described various cases of this theory that we found within the scope of science education. However, due to the nature of this theory, which takes a sociocultural approach, international research studies cannot be simply applied to the Korean context. Therefore, we sought to expand the applicability of this theory as a methodological tool, by discussing the directions in which this theory can be used in a domestic context. It is intended that the introduction of this theory, which emphasizes multi-layered, continuous and cumulative identity work, will be used as a resource to further expand the horizon of science education reform that is required for the times.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.6
• /
• pp.719-729
• /
• 2017

Recently, the field of agriculture has been gaining a new leap with the integration of ICT technology in agriculture. In particular, smart farms, which incorporate the Internet of Things (IoT) technology in agriculture, are in the spotlight. Smart farm technology collects and analyzes information such as temperature and humidity of the environment where crops are cultivated in real time using sensors to automatically control the devices necessary for harvesting crops in the control device, Environment. Although smart farm technology is paying attention as if it can solve everything, most of the research focuses only on increasing crop yields. This paper focuses on the development of a system architecture that can harvest high quality crops at the optimum stage rather than increase crop yields. In this paper, we have developed an architecture using apple trees as a sample and used the color information and weight information to predict the harvest time of apple trees. The simple board that collects color information and weight information and transmits it to the server side uses Arduino and adopts model-driven development (MDD) as development methodology. We have developed an architecture to provide services to PC users in the form of Web and to provide Smart Phone users with services in the form of hybrid apps. We also developed an architecture that uses beacon technology to provide orchestration information to users in real time.