Performance analysis of multi-threading on mobile game contents in Smart virtual machine
- Authors
- Son, Yunsik; Song, Hajoo; Lee, Yangsun
- Issue Date
- Jul-2015
- Publisher
- ASIA LIFE SCIENCES
- Keywords
- multi-threading; Smart Virtual Machine (SVM); Smart cross platform; cloud computing; mobile computing; IoT computing; program concurrency
- Citation
- ASIA LIFE SCIENCES, pp 335 - 345
- Pages
- 11
- Indexed
- SCIE
- Journal Title
- ASIA LIFE SCIENCES
- Start Page
- 335
- End Page
- 345
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/17393
- ISSN
- 0117-3375
- Abstract
- As a virtual machine is a software emulation to provide a logical environment without hardware dependency, it is a key technology for cloud, mobile and IoT computing and one of major technologies to offer better IT service in the information and knowledge-based society. Smart Virtual Machine (SVM) is a core module of a smart cross platform that provides users with language-platform independent functions for a higher level of contents reusability. This is a software processor executable with the medium code named SIL as the stack basis. This study introduces a way of multi-thread embodiment in which SVM can execute multiple tasks. The multi thread for SVM was designed based on a thread model of C++ and Java Language. Since it supports C/C++ and Java programming environments, SVM processes various tasks simultaneously with a higher level of program concurrency. This study focuses on a thread for Smart Virtual Machine. As a virtual machine-based compiler generates a program created by means of C/C++ or Java and the semantically equivalent intermediate code, SVM receives and executes them. The thread for SVM was designed based on a thread model of C++/Java, thread scheduling is possible for multithreading in programming. A programmer may use the thread regardless of the developing language, and it is executable with no limitation due to certain hardware types. Besides, the thread enhances program concurrency.
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- Appears in
Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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