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In Kee Kim
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Forecasting Cloud Application Workloads With CloudInsight for Predictive Resource Management
IK Kim, W Wang, Y Qi, M Humphrey
IEEE Transactions on Cloud Computing 10 (3), 1848-1863, 2020
762020
Empirical Evaluation of Workload Forecasting Techniques for Predictive Cloud Resource Scaling
IK Kim, W Wang, Y Qi, M Humphrey
9th IEEE International Conference on Cloud Computing, 2016
532016
CloudInsight: Utilizing a Council of Experts to Predict Future Cloud Application Workloads
IK Kim, W Wang, Y Qi, M Humphrey
2018 IEEE International Conference on Cloud Computing, 2018
462018
Wasserstein Adversarial Transformer for Cloud Workload Prediction
S Arbat, VK Jayakumar, J Lee, W Wang, IK Kim
Proceedings of the AAAI Conference on Artificial Intelligence, 2022
272022
Toward optimal resource provisioning for cloud mapreduce and hybrid cloud applications
A Ruiz-Alvarez, IK Kim, M Humphrey
2015 8th IEEE International Conference on Cloud Computing, 669-677, 2015
252015
PICS: A Public IaaS Cloud Simulator
IK Kim, W Wang, M Humphrey
8th IEEE International Conference on Cloud Computing, 2015
252015
Comprehensive Elastic Resource Management to Ensure Predictable Performance for Scientific Applications on Public IaaS Clouds
IK Kim, J Steele, Y Qi, M Humphrey
UCC'14: 7th IEEE/ACM International Conference on Utility and Cloud Computing,, 2014
242014
A self-optimized generic workload prediction framework for cloud computing
VK Jayakumar, J Lee, IK Kim, W Wang
2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2020
232020
A supervised learning model for identifying inactive VMs in private cloud data centers
IK Kim, S Zeng, C Young, J Hwang, M Humphrey
Proceedings of the Industrial Track of the 17th International Middleware …, 2016
222016
Edgefaasbench: Benchmarking edge devices using serverless computing
KR Rajput, CD Kulkarni, B Cho, W Wang, IK Kim
2022 IEEE International Conference on Edge Computing and Communications …, 2022
212022
AI Multi-Tenancy on Edge: Concurrent Deep Learning Model Executions and Dynamic Model Placements on Edge Devices
P Subedi, J Hao, IK Kim, L Ramaswamy
2021 IEEE 14th International Conference on Cloud Computing (CLOUD), 31-42, 2021
192021
An Empirical Analysis of VM Startup Times in Public IaaS Clouds
J Hao, T Jiang, W Wang, IK Kim
2021 IEEE 14th International Conference on Cloud Computing (CLOUD), 398-403, 2021
192021
iCSI: A cloud garbage VM collector for addressing inactive VMs with machine learning
IK Kim, S Zeng, C Young, J Hwang, M Humphrey
2017 IEEE International Conference on Cloud Engineering (IC2E), 17-28, 2017
172017
Reaching for the sky: Maximizing deep learning inference throughput on edge devices with ai multi-tenancy
J Hao, P Subedi, L Ramaswamy, IK Kim
ACM Transactions on Internet Technology 23 (1), 1-33, 2023
152023
Nonsuicidal self-injury on Instagram: examining hashtag trends
AL Giordano, LA Lundeen, KL Wester, J Lee, S Vickers, MK Schmit, ...
International Journal for the Advancement of Counselling, 1-16, 2022
132022
#selfharm on Instagram: Quantitative Analysis and Classification of Non-Suicidal Self-Injury
L Xian, SD Vickers, AL Giordano, J Lee, IK Kim, L Ramaswamy
2019 IEEE First International Conference on Cognitive Machine Intelligence …, 2019
132019
Near-Edge Computing Aware Object Detection: A Review
A Setyanto, T Sasongko, MA Fikri, IK Kim
IEEE Access, 2024
82024
ChatterHub: Privacy invasion via smart home hub
O Setayeshfar, K Subramani, X Yuan, R Dey, D Hong, KH Lee, IK Kim
2021 IEEE International Conference on Smart Computing (SMARTCOMP), 181-188, 2021
82021
Privacy invasion via smart-home hub in personal area networks
O Setayeshfar, K Subramani, X Yuan, R Dey, D Hong, IK Kim, KH Lee
Pervasive and Mobile Computing 85, 101675, 2022
72022
Characterizing Resource Heterogeneity in Edge Devices for Deep Learning Inferences
J Hao, P Subedi, IK Kim, L Ramaswamy
Proceedings of the 2021 on Systems and Network Telemetry and Analytics, 21-24, 2021
72021
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