A Reliability Model for Result Checking in Volunteer Computing

2008 ◽  
Author(s):  
Ling Xu ◽  
Hong Wang ◽  
Hiroyuki Takizawa ◽  
Hiroaki Kobayashi
Keyword(s):  
Volunteer Computing ◽  
Reliability Model

scholarly journals Task Assignment Algorithm Based on Trust in Volunteer Computing Platforms

Information ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 244 ◽  
Author(s):  
Ling Xu ◽  
Jianzhong Qiao ◽  
Shukuan Lin ◽  
Ruihua Qi
Keyword(s):  
Completion Time ◽  
Fuzzy Model ◽  
Task Assignment ◽  
Experimental Results ◽  
Volunteer Computing ◽  
Time Interval ◽  
Reliability Model ◽  
Assignment Algorithm ◽  
Computing Platforms ◽  
Task Segmentation

In volunteer computing (VC), the expected availability time and the actual availability time provided by volunteer nodes (VNs) are usually inconsistent. Scheduling tasks with precedence constraints in VC under this situation is a new challenge. In this paper, we propose two novel task assignment algorithms to minimize completion time (makespan) by a flexible task assignment. Firstly, this paper proposes a reliability model, which uses a simple fuzzy model to predict the time interval provided by a VN. This reliability model can reduce inconsistencies between the expected availability time and actual availability time. Secondly, based on the reliability model, this paper proposes an algorithm called EFTT (Earliest Finish Task based on Trust, EFTT), which can minimize makespan. However, EFTT may induce resource waste in task assignment. To make full use of computing resources and reduce task segmentation rate, an algorithm IEFTT (improved earliest finish task based on trust, IEFTT) is further proposed. Finally, experimental results verify the efficiency of the proposed algorithms.

Nuclear Hybrid Energy System Reliability Model Progress Report

2017 ◽  
Author(s):  
Askin Guler Yigitoglu ◽  
Thomas Harrison ◽  
Michael Scott Greenwood
Keyword(s):  
System Reliability ◽  
Energy System ◽  
Progress Report ◽  
Reliability Model ◽  
Hybrid Energy System ◽  
Hybrid Energy

Face detection in single and multiple images using different skin color models

2020 ◽  
Vol 13 ◽  
Author(s):  
Manpreet Kaur ◽  
Jasdev Bhatti ◽  
Mohit Kumar Kakkar ◽  
Arun Upmanyu
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Input Image ◽  
Morphological Operations ◽  
Reliability Model ◽  
Multiple Images ◽  
Face Region ◽  
Bounding Box ◽  
The Face ◽  
Precision And Accuracy

Introduction: Face Detection is used in many different steams like video conferencing, human-computer interface, in face detection, and in the database management of image. Therefore, the aim of our paper is to apply Red Green Blue ( Methods: The morphological operations are performed in the face region to a number of pixels as the proposed parameter to check either an input image contains face region or not. Canny edge detection is also used to show the boundaries of a candidate face region, in the end, the face can be shown detected by using bounding box around the face. Results: The reliability model has also been proposed for detecting the faces in single and multiple images. The results of the experiments reflect that the algorithm been proposed performs very well in each model for detecting the faces in single and multiple images and the reliability model provides the best fit by analyzing the precision and accuracy. Moreover Discussion: The calculated results show that HSV model works best for single faced images whereas YCbCr and TSL models work best for multiple faced images. Also, the evaluated results by this paper provides the better testing strategies that helps to develop new techniques which leads to an increase in research effectiveness. Conclusion: The calculated value of all parameters is helpful for proving that the proposed algorithm has been performed very well in each model for detecting the face by using a bounding box around the face in single as well as multiple images. The precision and accuracy of all three models are analyzed through the reliability model. The comparison calculated in this paper reflects that HSV model works best for single faced images whereas YCbCr and TSL models work best for multiple faced images.

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