Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
RECONF |
2019-09-19 14:20 |
Fukuoka |
KITAKYUSHU Convention Center |
RECONF2019-22 |
(To be available after the conference date) [more] |
RECONF2019-22 pp.9-12 |
ICM |
2019-03-08 09:20 |
Okinawa |
|
Pricing and Resource Allocation on Hadoop Data Centers Using Auction Mechanisms Yu Manabe, Jun Kawahara, Shoji Kasahara (NAIST) ICM2018-57 |
As storage capacity and computing performance grow due to the development of hardware, it is possible for applications t... [more] |
ICM2018-57 pp.43-48 |
PN |
2016-11-17 14:05 |
Saitama |
KDDI Research, Inc. |
A Task Allocation Scheme in Hadoop Clusters Considering Computational and Network Resources for Wide Area Networks Tomohiro Matsuno, Bijoy Chand Chatterjee, Nattapong Kitsuwan, Eiji Oki (UEC), Malathi Veeraraghavan (UVA), Satoru Okamoto, Naoaki Yamanaka (Keio) PN2016-31 |
This paper designs a Hadoop system, which considers both slave server's processing capacity and network delay for wide a... [more] |
PN2016-31 pp.31-37 |
IN, NV (Joint) |
2016-07-15 13:30 |
Hokkaido |
Matsumaecho Sougo Center |
[Invited Talk]
Data Virtualization for Data Source Integration Kazuhiro Satio, Nobuyuki Maita, Yasuhyuki Watanabe, Arei Kobayashi (KDDI R&D Labs.) IN2016-29 |
Data has become large and diversified by the drastic growth of the information technology, and is stored in a various da... [more] |
IN2016-29 pp.37-41 |
SC |
2015-03-28 10:55 |
Fukushima |
Aizu Univ. |
Parallel Processing of Large-Scale Graphs Using Spark on GPGPU Yuki Inamoto, Mikio Aoyama (Nanzan Univ.) SC2014-19 |
We propose a high performance computing method for large-scale graphs using the Spark on GPGPU. RDD, multiple sets of ab... [more] |
SC2014-19 pp.31-36 |
CPSY, DC (Joint) |
2014-07-28 17:00 |
Niigata |
Toki Messe, Niigata |
Performance Evaluation of Hadoop Applications in Hybrid Cloud Hayata Ohnaga (Tokyo Tech), Kento Aida (NII/Tokyo Tech), Omar Abdul-Rahman (NII) CPSY2014-13 |
In this paper, we present the performance evaluation results of Hadoop applications on hybrid clouds. We built three hyb... [more] |
CPSY2014-13 pp.19-24 |
ICSS, IPSJ-SPT |
2014-03-28 10:15 |
Okinawa |
Meio Univiersity |
MATATABI: Multi-layer Threat Analysis Platform with Hadoop Hajime Tazaki (Univ. of Tokyo), Kazuya Okada (NAIST), Yuji Sekiya (Univ. of Tokyo), Youki Kadobayashi (NAIST) ICSS2013-77 |
Threat detections and analyses are indispensable processes in today’s cyberspace, but current state of the arts are stil... [more] |
ICSS2013-77 pp.113-118 |
NS, IN (Joint) |
2014-03-07 10:40 |
Miyazaki |
Miyazaki Seagia |
Data Transfer Aware Scheduler for Hadoop Hyuma Watanabe, Masatoshi Kawarasaki (Univ. of Tsukuba) IN2013-173 |
Data transfer time occupies large amount of Hadoop job processing time. In this paper, we propose new Hadoop task schedu... [more] |
IN2013-173 pp.175-180 |
IN, IA (Joint) |
2013-12-20 14:15 |
Hiroshima |
Hiroshima City Univ. |
MapReduce Job Scheduling Based on Remaining Processing Times Tatsuma Matsuki, Tetsuya Takine (Osaka Univ.) IN2013-116 |
The MapReduce job scheduler implemented in Hadoop is a mechanism to
decide which jobs are assigned to idle resources in... [more] |
IN2013-116 pp.101-106 |
CPSY |
2013-11-08 17:25 |
Hiroshima |
|
Performance Fluctuation of Hadoop Jobs in the Clouds Kento Aida, Omar Abdul-Rahman, Eisaku Sakane, Kazutaka Motoyama (NII) CPSY2013-56 |
This paper presents the results of performance evaluation to investigate the fluctuation of application execution time i... [more] |
CPSY2013-56 pp.97-102 |
DC, CPSY (Joint) |
2013-08-02 15:15 |
Fukuoka |
Kitakyushu-Kokusai-Kaigijyo |
Implementation and Evaluation of JobTracker Initiative Task Scheduling on Hadoop Kazuki Yamazaki, Tomoaki Tsumura, Shoichi Saito, Hiroshi Matsuo (Nagoya Inst. of Tech.) CPSY2013-24 |
MapReduce is one of a framework to process large-scale data efficiently. Describing only two methods, Map and Reduce, di... [more] |
CPSY2013-24 pp.85-90 |
ICM, IPSJ-IOT, IPSJ-CSEC |
2013-05-10 11:45 |
Aomori |
Hirosaki University |
A Study on Design Method of Hadoop-based OSSs Manabu Nishio, Naoki Take (NTT) ICM2013-8 |
In recent years, with expanding of network scale and diversification of services, it also increases the amount of data t... [more] |
ICM2013-8 pp.151-156 |
IN |
2013-01-25 15:00 |
Kagoshima |
Kagoshima-Ken-Sangyo-Kaikan |
Enhancing Hadoop Performance by Network-Aware Task Scheduling Shun Kataoka, Hyuma Watanabe, Masatoshi Kawarasaki (Tsukuba Univ.) IN2012-152 |
Hadoop uses MapReduce for distributed processing of large-scale data. Although a large amount of data transfer
between ... [more] |
IN2012-152 pp.81-86 |
NS |
2012-10-11 15:25 |
Kyoto |
Kyoto Univ. |
Data Sharing among Hadoop Clusters by Hadoop on Demand Manhee Jo, Satoshi Tanaka, Kenji Ishii (NTT DoCoMo) NS2012-93 |
One of the most tough problems in maintaining large scale Hadoop testing clusters is data copying overhead among the clu... [more] |
NS2012-93 pp.73-78 |
IN, NV (Joint) |
2012-07-20 10:25 |
Hokkaido |
Hokkaido Univ. |
A Study about Hadoop Throughput Improvement Technique over WAN Takeshi Miyamae, Ryoichi Mutoh (Fujitsu Labs.) IN2012-42 |
Recently, a vast amount of data has being stored everyday all over the world. In the field of big-data analysis such as ... [more] |
IN2012-42 pp.55-60 |
LOIS |
2012-03-09 15:15 |
Okinawa |
Meio Univ. |
A Study on Data Platform for Collecting and Using Large-scale House Log in Smart City Shintaro Yamamoto, Hideharu Seto, Shinsuke Matsumoto, Masahide Nakamura (Kobe Univ.) LOIS2011-107 |
Smart city is a next-generation societal concept which aims to provide low-carbon and sustainable social infrastructure.... [more] |
LOIS2011-107 pp.207-212 |
NS, RCS (Joint) |
2011-12-16 10:35 |
Yamaguchi |
Yamaguchi University |
[Encouragement Talk]
Improvement in packet import method of Hadoop-based Packet Analyzer for High Volume Packet Data Takato Naritomi, Yutaka Arakawa, Kenta Kawaguchi, Mitsuhide Honda, Takuya Mizokami, Kouji Mima (Kyushu Univ), Shigeaki Harada (NTT WEST), Shigeru Kusakabe (Kyushu Univ) NS2011-139 |
Traffic analysis based on packet capturing become hard to analyze quickly, because captured packet data has become too h... [more] |
NS2011-139 pp.121-126 |
CPSY |
2011-10-21 14:55 |
Hyogo |
|
Parallelization of Tree-Puzzle Program for Phylogenetic Analysis in Molecular Evolution by Hadoop using JNI Tsutomu Koyama, Mitsuhisa Sato (Univ. Tsukuba) CPSY2011-34 |
We have parallelized of Tree-Puzzle that is a phylogenetic analysis program in molecular evolution by using MapReduce as... [more] |
CPSY2011-34 pp.49-54 |
PRMU, DE |
2011-06-06 11:30 |
Kanagawa |
|
Characterization of Remote Data Access for Hadoop Distributed File System over a long-latency environment Asuka Momose, Masato Oguchi (Ochanomizu Univ.) DE2011-4 PRMU2011-35 |
Under the Info-plosion age, Distributed File System (DFS), on which intensive transaction is executed with commodity mac... [more] |
DE2011-4 PRMU2011-35 pp.19-24 |
NS |
2011-04-22 13:00 |
Fukui |
Fukui University |
Design and Implementation of Hadoop-based Packet Analyzer for High Volume Packet Data Takato Naritomi, Kenta Kawaguchi, Takuya Mizokami, Kouji Mima (Kyushu Univ.), Shigeaki Harada (NTT WEST), Yutaka Arakawa, Shigeru Kusakabe (Kyushu Univ.) NS2011-12 |
Traffic analysis based on packet capturing is often used for monitoring and checking network failure. However, it become... [more] |
NS2011-12 pp.67-72 |