Demo Data from VLDB 2026 / reviewers in the wild / expert
Jin Gon Shon
dblp:41/4403
· DBLP profile ↗
6ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-0540-4640ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2Computer networks · 1Human-computer interaction and ubiquitous computing · 1Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer networks
1 paper |
Cellular and mobile networks · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 50% Storage systems · 50% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cellular and mobile networks
mobility management |
0.0 | 1 | 2001 | Restoration scheme of mobility databases by mobility learning and prediction in PCS networks · IEEE J. Sel. Areas Commun. 2001 |
Cellular and mobile networks › mobility management
mobility prediction |
0.0 | 1 | 2001 | Restoration scheme of mobility databases by mobility learning and prediction in PCS networks · IEEE J. Sel. Areas Commun. 2001 |
Cellular and mobile networks › mobile networks
personal communications services |
0.0 | 1 | 2001 | Restoration scheme of mobility databases by mobility learning and prediction in PCS networks · IEEE J. Sel. Areas Commun. 2001 |
Storage systems
database recovery |
0.0 | 1 | 2001 | Restoration scheme of mobility databases by mobility learning and prediction in PCS networks · IEEE J. Sel. Areas Commun. 2001 |
Distributed systems
fault tolerance |
0.0 | 1 | 2001 | Restoration scheme of mobility databases by mobility learning and prediction in PCS networks · IEEE J. Sel. Areas Commun. 2001 |
Methods — techniques the papers use, named apart from their topics
prediction · 0.1neuro-fuzzy inference system · 0.1mobility learning · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Differential data processing technique to improve the performance of wireless sensor networks
Kwang Kyu Lim, Jin Gon Shon |
J. Supercomput. | 3 |
| 2015 | A Clustering Method using Entropy for Grouping Students
Byoung Wook Kim, Jon Mason, Jin Gon Shon |
ICCE | 3 |
| 2007 | A Design of Cooperation Management System to Improve Reliability in Resource Sharing Computing Environment
Kwang-Sik Chung, Jin Gon Shon |
GPC | 3 |
| 2004 | Region-based Stage Construction Protocol for Fault tolerant Execution of Mobile AgentabstractFault tolerance is essential to the development of reliable mobile agent systems in order to guarantee continuous execution of mobile agents. For this purpose, previous work has proposed fault tolerant protocols for mobile agent execution based on stage construction. However, when previous protocols are applied to a multiregion mobile agent computing environment, the overhead of work such as monitoring, election, voting and agreement is increased. We propose a region-based stage construction (RBSC) protocol for fault tolerant execution of mobile agents in a multiregion mobile agent computing environment. The RBSC protocol uses new concepts of quasiparticipant and substage in order to put together some places located in different regions within a stage in the same region. Therefore, the RBSC protocol decreases the overhead of stage works. Consequently, the RBSC protocol decreases the total execution time of mobile agents. SungJin Choi, MaengSoon Baik, HongSoo Kim, JunWeon Yoon, Jin Gon Shon, Chong-Sun Hwang |
AINA (2) | 5 |
| 2001 | Restoration scheme of mobility databases by mobility learning and prediction in PCS networksabstractThis paper proposes a restoration scheme based on mobility learning and prediction in the presence of the failure of mobility databases in personal communication systems (PCSs). In PCSs, mobility databases must maintain the current location information of users to provide a fast connection for them. However, the malfunction of mobility databases may cause some location information to be lost. As a result, without an explicit restoration procedure, incoming calls to users may be rejected. Therefore, an explicit restoration scheme against the malfunction of mobility databases is needed to guarantee continuous service availability to users. Introducing mobility learning and prediction into the restoration process allows systems to locate users after a failure of mobility databases. In failure-free operations, the movement patterns of users are learned by a neuro-fuzzy inference system (NFIS). After a failure, an inference process of the NFIS is initiated and the users' future location is predicted. This is used to locate lost users after a failure. This proposal differs from previous approaches using a checkpoint because it does not need a backup process nor additional storage space to store checkpoint information. In addition, simulations show that our proposal can reduce the cost needed to restore the location records of lost users after a failure when compared to the checkpointing scheme. Joon-Min Gil, Chan Yeol Park, Chong-Sun Hwang, Doo-Soon Park, Jin Gon Shon, Young-Sik Jeong |
IEEE J. Sel. Areas Commun. | 5 |
| 1997 | Hybrid checkpointing protocol based on selective-sender-based message loggingabstractThis paper presents a hybrid checkpointing protocol-an asynchronous checkpointing protocol using a message sending/receiving state change for reducing the overhead of failure-free operation combined with a selective sender-based message logging protocol for reducing the cascade rollback of asynchronous checkpointing protocol. The selective sender-based message logging protocol records only potential orphan messages when taking a checkpoint. And this paper presents a message dependency tree recording the inter-process message sending/receiving information on a volatile storage for reducing the search time of inter-process information during the failure recovery. Kwang-Sik Chung, Kibom Kim, Chong-Sun Hwang, Jin Gon Shon, Heon-Chang Yu |
ICPADS | 4 |