International Conference on Future Web (ICFW) 2014, pp.1-8
Language
English
Type
Conference Paper
Abstract
Recently, as the interest in large-scale data analysis increases, researches and developments relating to the technology for high-speed storing and processing large amounts of data become more active. Accordingly, the user demands for large main memory and the memory cloud service increase more and more. In this paper we design and implement a distributed memory integration system which integrates memory of nodes in a large-scale distributed system. Our system integrates a plurality of memory granting nodes and maintains and manages the distributed memory pool. Our system can provide applications with a huge virtual physical memory which may exceeds the size of the local memory. Thus it can improve the performance of the big data processing applications and furthermore it is possible to realize the memory cloud service. We implemented the prototype of the distributed memory integration system on the Linux Operating System.
KSP Keywords
Cloud service, Distributed System(DS), High Performance Data, High Speed, Integration System, LINUX operating system, Local Memory, Physical Memory, Researches and developments, big data processing, distributed memory
Copyright Policy
ETRI KSP Copyright Policy
The materials provided on this website are subject to copyrights owned by ETRI and protected by the Copyright Act. Any reproduction, modification, or distribution, in whole or in part, requires the prior explicit approval of ETRI. However, under Article 24.2 of the Copyright Act, the materials may be freely used provided the user complies with the following terms:
The materials to be used must have attached a Korea Open Government License (KOGL) Type 4 symbol, which is similar to CC-BY-NC-ND (Creative Commons Attribution Non-Commercial No Derivatives License). Users are free to use the materials only for non-commercial purposes, provided that original works are properly cited and that no alterations, modifications, or changes to such works is made. This website may contain materials for which ETRI does not hold full copyright or for which ETRI shares copyright in conjunction with other third parties. Without explicit permission, any use of such materials without KOGL indication is strictly prohibited and will constitute an infringement of the copyright of ETRI or of the relevant copyright holders.
J. Kim et. al, "Trends in Lightweight Kernel for Many core Based High-Performance Computing", Electronics and Telecommunications Trends. Vol. 32, No. 4, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
J. Sim et.al, “the Fourth Industrial Revolution and ICT – IDX Strategy for leading the Fourth Industrial Revolution”, ETRI Insight, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
If you have any questions or concerns about these terms of use, or if you would like to request permission to use any material on this website, please feel free to contact us
KOGL Type 4:(Source Indication + Commercial Use Prohibition+Change Prohibition)
Contact ETRI, Research Information Service Section
Privacy Policy
ETRI KSP Privacy Policy
ETRI does not collect personal information from external users who access our Knowledge Sharing Platform (KSP). Unathorized automated collection of researcher information from our platform without ETRI's consent is strictly prohibited.
[Researcher Information Disclosure] ETRI publicly shares specific researcher information related to research outcomes, including the researcher's name, department, work email, and work phone number.
※ ETRI does not share employee photographs with external users without the explicit consent of the researcher. If a researcher provides consent, their photograph may be displayed on the KSP.