A novel deep learning method for query task execution time prediction in graph database

2020 ◽  
Vol 112 ◽  
pp. 534-548 ◽  
Author(s):  
Zheng Chu ◽  
Jiong Yu ◽  
Askar Hamdulla
Keyword(s):  
Deep Learning ◽  
Execution Time ◽  
Graph Database ◽  
Learning Method ◽  
Task Execution ◽  
Time Prediction ◽  
Task Execution Time ◽  
Execution Time Prediction

scholarly journals Data-Intensive Task Scheduling for Heterogeneous Big Data Analytics in IoT System

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4508
Author(s):  
Xin Li ◽  
Liangyuan Wang ◽  
Jemal H. Abawajy ◽  
Xiaolin Qin ◽  
Giovanni Pau ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Task Scheduling ◽  
Execution Time ◽  
Data Centers ◽  
Big Data Analysis ◽  
Data Locality ◽  
Data Migration ◽  
Task Execution ◽  
Task Execution Time

Efficient big data analysis is critical to support applications or services in Internet of Things (IoT) system, especially for the time-intensive services. Hence, the data center may host heterogeneous big data analysis tasks for multiple IoT systems. It is a challenging problem since the data centers usually need to schedule a large number of periodic or online tasks in a short time. In this paper, we investigate the heterogeneous task scheduling problem to reduce the global task execution time, which is also an efficient method to reduce energy consumption for data centers. We establish the task execution for heterogeneous tasks respectively based on the data locality feature, which also indicate the relationship among the tasks, data blocks and servers. We propose a heterogeneous task scheduling algorithm with data migration. The core idea of the algorithm is to maximize the efficiency by comparing the cost between remote task execution and data migration, which could improve the data locality and reduce task execution time. We conduct extensive simulations and the experimental results show that our algorithm has better performance than the traditional methods, and data migration actually works to reduce th overall task execution time. The algorithm also shows acceptable fairness for the heterogeneous tasks.

scholarly journals Uncertainty aware query execution time prediction

2014 ◽  
Vol 7 (14) ◽  
pp. 1857-1868 ◽  
Author(s):  
Wentao Wu ◽  
Xi Wu ◽  
Hakan Hacigümüş ◽  
Jeffrey F. Naughton
Keyword(s):  
Execution Time ◽  
Query Execution ◽  
Time Prediction ◽  
Query Execution Time Prediction ◽  
Execution Time Prediction

A web browsing interface for people with severe speech and motor impairment

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Manjira Sinha ◽  
Tirthankar Dasgupta
Keyword(s):  
Execution Time ◽  
Motor Impairment ◽  
Cognitive Effort ◽  
Motor Disorder ◽  
Web Browsing ◽  
Task Execution ◽  
Content Type ◽  
Task Execution Time ◽  
Scanning Mechanism ◽  
The Web

Purpose The Web has become an indispensable medium used by people across the world for education, information, entertainment, social interaction as well as for various daily activities involving shopping and employment-related tasks. It is therefore becoming increasingly essential that the Web must be accessible to all people to provide equal access and equal opportunity. This is specifically more important for people with various kind of disabilities. Several initiatives such as development of Web accessibility guidelines, tools and technologies have been undertaken to make the Web usable for people with different disabilities. However, only a handful of them are aimed at people with Severe Speech and Motor Impairment (SSMI). This paper aims to present a Web browsing interface for people with severe speech and motor impairment. Design/methodology/approach The browser allows easy dissemination of information through World Wide Web for people with SSMI. The browser is augmented with both automatic as well as manual scanning mechanisms through which a motor disorder person can access the browser graphical user interface (GUI). Further, the browser provides an intelligent content scanning mechanism through which the Web contents can be accessed with less time and cognitive effort. Along with the desktop version, WebSanyog is successfully ported on Android-based tablets to make the system portable. Findings The system has been exhaustively field tested by people with SSMI. The browser has been deployed at the Indian Institute of Cerebral Palsy (IICP), Kolkata. The performance of the browser has been measured in terms of three parameters: The Task execution time (TET); Error rates analysis (ER); and Overall usability score by the subject. The evaluation results suggests that the proposed Web browsing interface is effective in terms of task execution time, cognitive effort and overall user satisfaction. Originality/value The browser GUI is integrated with an automatic scanning mechanism as an alternate way to access and navigate through Web pages, instead of using keyboard and mouse. The browser provides novel content access mechanisms that makes navigating through Web page contents like links, images and embedded videos easier and faster. To facilitate text entry, the browser provides two different options, namely, the predictive virtual scanning keyboard and a novel icon-based query entry scheme that allows generating search queries through the selection of multiple icons.

Prediction of Task Execution Time in Cloud Computing

2021 ◽  
Author(s):  
Saravanan C ◽  
Mahesh T R ◽  
Vivek V ◽  
Sindhu Madhuri G ◽  
Shashikala H K ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Execution Time ◽  
Task Execution ◽  
Task Execution Time
Sign in / Sign up

Export Citation Format

Share Document