Results 21 to 30 of about 1,735,174 (276)

Predictable performance for unpredictable workloads

Proceedings of the VLDB Endowment, 2009
This paper introduces Crescando: a scalable, distributed relational table implementation designed to perform large numbers of queries and updates with guaranteed access latency and data freshness. To this end, Crescando leverages a number of modern query processing techniques and hardware trends.
Unterbrunner, P., Giannikis, G., Alonso, G., Fauser, D., Kossmann, D.   +4 more
openaire   +2 more sources

Efficient Query Workload Prediction Algorithm Based on TCN-A [PDF]

Jisuanji kexue
The query workload prediction algorithm based on a novel time series prediction model is proposed to address the pro-blem of database management system cannot be optimized in time due to the dynamic change of query workload and the difficulty of ...
BAI Wenchao, BAI Shuwen, HAN Xixian, ZHAO Yubo
doaj   +1 more source

Performance prediction for concurrent database workloads [PDF]

Proceedings of the 2011 ACM SIGMOD International Conference on Management of data, 2011
Current trends in data management systems, such as cloud and multi-tenant databases, are leading to data processing environments that concurrently execute heterogeneous query workloads. At the same time, these systems need to satisfy diverse performance expectations.
Jennie Duggan, Ugur Çetintemel, Olga Papaemmanouil, Eli Upfal   +3 more
openaire   +2 more sources

Managing Dynamic Enterprise and Urgent Workloads on Clouds Using Layered Queuing and Historical Performance Models [PDF]

, 2011
The automatic allocation of enterprise workload to resources can be enhanced by being able to make what-if response time predictions whilst different allocations are being considered.
Usmani, A., Lester Gilbert, van Hemert, J., Stephen A. Jarvis, David A. Bacigalupo, Adam P. Chester, Chester, Adam P., Wills, G. B., Gary B. Wills, He, Ligang, Jano van Hemert, Jarvis, Stephen A., Donna N. Dillenberger, Dillenberger, Donna N., Wills, Gary B., Jarvis, Stephen A.; id_orcid, Ligang He, Dillenberger, D. N., Chen, Xiaoyu, Usmani, Asif, Bacigalupo, David A., Wills, Gary, Asif Usmani, Gilbert, Lester, Gilbert, L., van Hemert, Jano, Xiaoyu Chen   +26 more
core   +2 more sources

Online EEG-Based Workload Adaptation of an Arithmetic Learning Environment

Frontiers in Human Neuroscience, 2017
In this paper, we demonstrate a closed-loop EEG-based learning environment, that adapts instructional learning material online, to improve learning success in students during arithmetic learning.
Carina Walter, Wolfgang Rosenstiel, Martin Bogdan, Peter Gerjets, Martin Spüler   +4 more
doaj   +1 more source

Fast and accurate interpretation of workload classification model

PLoS ONE, 2023
How can we interpret predictions of a workload classification model? A workload is a sequence of operations executed in DRAM, where each operation contains a command and an address.
Sooyeon Shim, Doyeon Kim, Jun-Gi Jang, Suhyun Chae, Jeeyong Lee, U. Kang   +5 more
doaj   +2 more sources

PREDICTION BASED WORKLOAD PERFORMANCE EVALUATION FOR DISASTER MANAGEMENT SPATIAL DATABASE [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018
This paper discusses a prediction based workload performance evaluation implementation during Disaster Management, especially at the response phase, to handle large spatial data in the event of an eruption of the Merapi volcano in Indonesia.
N. Suryana, M. S. Rohman, F. S. Utomo, F. S. Utomo   +3 more
doaj   +1 more source

A novel approach to workload prediction using attention-based LSTM encoder-decoder network in cloud environment

EURASIP Journal on Wireless Communications and Networking, 2019
Server workload in the form of cloud-end clusters is a key factor in server maintenance and task scheduling. How to balance and optimize hardware resources and computation resources should thus receive more attention.
Yonghua Zhu, Weilin Zhang, Yihai Chen, Honghao Gao   +3 more
doaj   +1 more source

Microservice-Oriented Workload Prediction Using Deep Learning

e-Informatica Software Engineering Journal, 2022
Background: Service oriented architectures are becoming increasingly popular due to their flexibility and scalability which makes them a good fit for cloud deployments.
Sebastian Ştefan, Virginia Niculescu
doaj   +1 more source

Workload Failure Prediction for Data Centers

2023 IEEE 16th International Conference on Cloud Computing (CLOUD), 2023
Failed workloads that consumed significant computational resources in time and space affect the efficiency of data centers significantly and thus limit the amount of scientific work that can be achieved. While the computational power has increased significantly over the years, detection and prediction of workload failures have lagged far behind and ...
Jie Li 0057, Rui Wang, Ghazanfar Ali, Tommy Dang, Alan Sill, Yong Chen 0001   +5 more
openaire   +2 more sources