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Young-ri Choi

Ulsan National Institute of Science and Technology · Computer Science

About the Lab

Professor Young-ri Choi's research lab specializes in computer systems and distributed computing, with a focus on high-performance, scalable, and resilient systems for extreme-scale wireless networks, persistent memory optimization, and efficient data management in emerging hardware environments. The lab explores challenges in wireless sensor networks, real-time data convergecast, and the integration of novel storage technologies like byte-addressable persistent memory to enhance system performance and reliability. Key research directions include protocol design for large-scale ad hoc networks, efficient key-value store architectures, and heterogeneous GPU-based deep learning training systems. The lab emphasizes practical system implementation and performance evaluation using real-world deployments and workloads.

wireless sensor networkspersistent memorykey-value storesheterogeneous GPU computingsystem optimization

Research Overview

Papers
50
Total Citations
2,026
Papers (5y)
9
Primary Field
Computer Science

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
9total
2019
2020
2023
2024
2025
Citations per year (5y)
218total
20192020202320242025

Selected Papers

15
1
Article|894 citations·2004
A line in the sand: a wireless sensor network for target detection, classification, and tracking
Anish Arora, Prabal Dutta, Sandip Bapat, Vinod Kulathumani, Hui Zhang, Vinayak Naik, Vikas Mittal, Hui Cao, Murat Demirbaş, Mohamed G. Gouda, Young-ri Choi, Ted Herman
SJR Q1Computer Networks
Computer Networks and CommunicationsComputer Science
2
Article|313 citations·2006
ExScal: Elements of an Extreme Scale Wireless Sensor Network
Anish Arora, Rajiv Ramnath, Emre Ertin, P. Sinha, Sandip Bapat, Vinayak Naik, Vinod Kulathumani, Hongwei Zhang, Hui Cao, M. Sridharan, Santosh Kumar, Nick Seddon

Project ExScal (for extreme scale) fielded a 1000+ node wireless sensor network and a 200+ node peer-to-peer ad hoc network of 802.11 devices in a 13km by 300m remote area in Florida, USA during December 2004. In comparison with previous deployments, the ExScal application is relatively complex and its networks are the largest ones of either type fielded to date. In this paper, we overview the key requirements of ExScal, the corresponding design of the hardware/software platform and application,

Computer Networks and CommunicationsComputer Science
3
Article|187 citations·2005
Reliable bursty convergecast in wireless sensor networks
Hongwei Zhang, Anish Arora, Young-ri Choi, Mohamed G. Gouda

We address the challenges of bursty convergecast in multi-hop wireless sensor networks, where a large burst of packets from different locations needs to be transported reliably and in real-time to a base station. Via experiments on a 49 MICA2 mote sensor network using a realistic traffic trace, we determine the primary issues in bursty convergecast, and accordingly design a protocol, RBC (for Reliable Bursty Convergecast), to address these issues: To improve channel utilization and to reduce ack

Computer Networks and CommunicationsComputer Science
4
Article|103 citations·2007
Reliable bursty convergecast in wireless sensor networks
Hongwei Zhang, Anish Arora, Young-ri Choi, Mohamed G. Gouda
SJR Q1Computer Communications
Computer Networks and CommunicationsComputer Science
5
Article|76 citations·2019
SLM-DB: Single-Level Key-Value Store with Persistent Memory
Olzhas Kaiyrakhmet, Song-Yi Lee, Beomseok Nam, Sam H. Noh, Young-ri Choi
Scholarworks@UNIST (Ulsan National Institute of Science and Technology)OA

This paper investigates how to leverage emerging byteaddressable persistent memory (PM) to enhance the performance of key-value (KV) stores. We present a novel KV store, the Single-Level Merge DB (SLM-DB), which takes advantage of both the B+-tree index and the Log-Structured Merge Trees (LSM-tree) approach by making the best use of fast persistent memory. Our proposed SLM-DB achieves high read performance as well as high write performance with low write amplification and near-optimal read ampli

Computer Networks and CommunicationsComputer Science
6
Article|68 citations·2012
Dynamic virtual machine scheduling in clouds for architectural shared resources
Jeongseob Ahn, Changdae Kim, Jaeung Han, Young-ri Choi, Jaehyuk Huh
USENIX conference on Hot Topics in Cloud Ccomputing

As research progresses, the surface texture tool can significantly reduce the cutting heat and cutting force. However, the tool surface texture width, depth, and spacing also have an impact on the cutting performance. Using the Taguchi method and finite element analysis, the changing laws of cutting temperature, pressure, stress distribution, and cutting force were studied. The results showed that the tool texture width had the greatest influence on the cutting performance, followed by the tool

Information SystemsComputer Science
7
Article|59 citations·2019
Write-optimized dynamic hashing for persistent memory
Moohyeon Nam, Hokeun Cha, Young-ri Choi, Sam H. Noh, Beomseok Nam
Scholarworks@UNIST (Ulsan National Institute of Science and Technology)

Low latency storage media such as byte-addressable persistent memory (PM) requires rethinking of various data structures in terms of optimization. One of the main challenges in implementing hash-based indexing structures on PM is how to achieve efficiency by making effective use of cachelines while guaranteeing failure-atomicity for dynamic hash expansion and shrinkage. In this paper, we present Cacheline-Conscious Extendible Hashing (CCEH) that reduces the overhead of dynamic memory block manag

Computer Networks and CommunicationsComputer Science
8
Article|41 citations·2020
HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism
Jay Park, Gyeongchan Yun, Chang M. Yi, Nguyen T. Nguyen, Seungmin Lee, Jaesik Choi, Sam H. Noh, Young-ri Choi
arXiv (Cornell University)OA

Deep Neural Network (DNN) models have continuously been growing in size in order to improve the accuracy and quality of the models. Moreover, for training of large DNN models, the use of heterogeneous GPUs is inevitable due to the short release cycle of new GPU architectures. In this paper, we investigate how to enable training of large DNN models on a heterogeneous GPU cluster that possibly includes whimpy GPUs that, as a standalone, could not be used for training. We present a DNN training sys

Computer Vision and Pattern RecognitionComputer Science
9
Article|23 citations·2015
Resource Allocation Policies for Loosely Coupled Applications in Heterogeneous Computing Systems
Eunji Hwang, Suntae Kim, Tae-kyung Yoo, Jik‐Soo Kim, Soonwook Hwang, Young-ri Choi
SJR Q1IEEE Transactions on Parallel and Distributed Systems

High-Throughput Computing (HTC) and Many-Task Computing (MTC) paradigms employ loosely coupled applications which consist of a large number, from tens of thousands to even billions, of independent tasks. To support such large-scale applications, a heterogeneous computing system composed of multiple computing platforms with different types such as supercomputers, grids, and clouds can be used. On allocating heterogeneous resources of the system to multiple users, there are three important aspects

Computer Networks and CommunicationsComputer Science
10
Article|23 citations·2019
Constraint-aware VM placement in heterogeneous computing clusters
Seontae Kim, Young-ri Choi
SJR Q1Cluster Computing
Information SystemsComputer Science
11
Article|22 citations·2004
The mote connectivity protocol
Young-ri Choi, Mohamed G. Gouda, M.C. Kim, Anish Arora

An attractive architecture for sensor networks is to have the sensing devices mounted on small computers, called motes. Motes are battery-powered, and can communicate in a wireless fashion by broadcasting messages over radio frequency. In mote networks, the connectivity of a mote u can be defined by those motes that can receive messages from u with high probability and those motes from which u can receive messages with high probability. In this paper, we describe a protocol that can be triggered

Computer Networks and CommunicationsComputer Science
12
Article|22 citations·2006
Stabilization of Grid Routing in Sensor Networks
Young-ri Choi, Mohamed G. Gouda, Hongwei Zhang, Anish Arora
Journal of Aerospace Computing Information and Communication

We present a protocol for routing data messages from any sensor to the base station in a sensor network. The protocol maintains an incoming spanning tree whose root is the base station. The spanning tree is constructed as follows. First, each sensor in the network is assigned a unique identifier as if the sensors form a logical two-dimensional grid. Second, each sensor, other than the base station, uses its own identifier to compute the identifiers of its "potential parents" in

Computer Networks and CommunicationsComputer Science
13
Book Chapter|20 citations·2011
The Effect of Multi-core on HPC Applications in Virtualized Systems
Jaeung Han, Jeongseob Ahn, Changdae Kim, Youngjin Kwon, Young-ri Choi, Jaehyuk Huh
SJR Q2Lecture notes in computer scienceOA
Information SystemsComputer Science
14
Article|17 citations·2016
Interference Management for Distributed Parallel Applications in Consolidated Clusters
Jaeung Han, Seungheun Jeon, Young-ri Choi, Jaehyuk Huh

Consolidating multiple applications on a system can improve the overall resource utilization of data center systems. However, such consolidation can adversely affect the performance of some applications due to interference caused by resource contention. Despite many prior studies on the interference effects in single-node systems, the interference behaviors of distributed parallel applications have not been investigated thoroughly. With distributed applications, a local interference in a node ca

Information SystemsComputer Science
15
Article|15 citations·2016
In-Memory Caching Orchestration for Hadoop
Jaewon Kwak, Eunji Hwang, Tae-kyung Yoo, Beomseok Nam, Young-ri Choi

In this paper, we investigate techniques to effectively orchestrate HDFS in-memory caching for Hadoop. We first evaluate a degree of benefit which each of various MapReduce applications can get from in-memory caching, i.e. cache affinity. We then propose an adaptive cache local scheduling algorithm that adaptively adjusts the waiting time of a MapReduce job in a queue for a cache local node. We set the waiting time to be proportional to the percentage of cached input data for the job. We also de

Information SystemsComputer Science

Research Areas

Computer Networks and CommunicationsInformation SystemsComputer Vision and Pattern RecognitionPharmacologySignal Processing

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