AI for next generation computing: Emerging trends and future directions

SS Gill, M Xu, C Ottaviani, P Patros, R Bahsoon… - Internet of Things, 2022 - Elsevier
Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …

An empirical assessment of autonomicity for autonomic query optimizers using fuzzy-AHP technique

P Dehraj, A Sharma - Applied Soft Computing, 2020 - Elsevier
Quality assurance and evaluation has always been a key cause of concern for software
developers. This problem has been further aggravated by the complete dependence of …

Toward a smart data transfer node

Z Liu, R Kettimuthu, I Foster, PH Beckman - Future Generation Computer …, 2018 - Elsevier
Scientific computing systems are becoming significantly more complex, with distributed
teams and complex workflows spanning resources from telescopes and light sources to fast …

Retracted: Green intelligent financial system construction paradigm based on deep learning and concurrency models

X Feng, H Shi, J Wang, S Wang - … and Computation: Practice …, 2021 - Wiley Online Library
Green finance represents a new trend and new direction for future financial development,
and it is an innovation and change in the financial field. The role of the financial market in …

Evaluation of deep learning models for network performance prediction for scientific facilities

M Nakashima, A Sim, J Kim - … of the 3rd International Workshop on …, 2020 - dl.acm.org
Large data transfers are getting more critical with the increasing volume of data in scientific
computing. While scientific facilities manage dedicated infrastructures to support large data …

Cookie-Jar: An Adaptive Re-configurable Framework for Wireless Network Infrastructures

O Bel, BO Mutlu, J Manzano, C Wright-Hamor… - Proceedings of the 21st …, 2024 - dl.acm.org
5G advancements like Massive Multiple Input Multiple Output (MIMO) bring high capacity
and low latency, but also intensify interference challenges. Static and dynamic coordination …

Building a wide-area file transfer performance predictor: An empirical study

Z Liu, R Kettimuthu, P Balaprakash, NSV Rao… - … Conference on Machine …, 2018 - Springer
Wide-area data transfer is central to geographically distributed scientific workflows. Faster
delivery of data is important for these workflows. Predictability is equally (or even more) …

Dynamic online performance optimization in streaming data compression

JK Gibson, D Lee, J Choi, A Sim - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Compression is essential to high bandwidth applications such as scientific simulations and
sensing applications to reduce resource burden such as storage, network transmission, and …

Leveraging History to Predict Infrequent Abnormal Transfers in Distributed Workflows

R Shao, A Sim, K Wu, J Kim - Sensors, 2023 - mdpi.com
Scientific computing heavily relies on data shared by the community, especially in
distributed data-intensive applications. This research focuses on predicting slow …

Predicting Slow Network Transfers in Scientific Computing

R Shao, J Kim, A Sim, K Wu - … on Systems and Network Telemetry and …, 2022 - dl.acm.org
Data access throughput is one of the key performance metrics in scientific computing,
particularly for distributed data-intensive applications. While there has been a body of …