An Efficient Algorithm for Scheduling Jobs in Volunteer Computing Platforms

2014 ◽  
Author(s):  
Adel Essafi ◽  
Denis Trystram ◽  
Zied Zaidi
Keyword(s):  
Efficient Algorithm ◽  
Volunteer Computing ◽  
Computing Platforms

scholarly journals Research on the Task Assignment Problem with Maximum Benefits in Volunteer Computing Platforms

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 862
Author(s):  
Ling Xu ◽  
Jianzhong Qiao ◽  
Shukuan Lin ◽  
Xiaowei Wang
Keyword(s):  
Assignment Problem ◽  
Low Cost ◽  
Task Assignment ◽  
Task Completion ◽  
Volunteer Computing ◽  
Computing Services ◽  
Pruning Strategy ◽  
Computing Platforms ◽  
Deadline Constraints ◽  
Task Assignment Problem

As a type of distributed computing, volunteer computing (VC) has provided unlimited computing capacity at a low cost in recent decades. The architecture of most volunteer computing platforms (VCPs) is a master–worker model, which defines a master–slave relationship. Therefore, VCPs can be considered asymmetric multiprocessing systems (AMSs). As AMSs, VCPs are very promising for providing computing services for users. Users can submit tasks with deadline constraints to the VCPs. If the tasks are completed within their deadlines, VCPs will obtain the benefits. For this application scenario, this paper proposes a new task assignment problem with the maximum benefits in VCPs for the first time. To address the problem, we first proposed a list-based task assignment (LTA) strategy, and we proved that the LTA strategy could complete the task with a deadline constraint as soon as possible. Then, based on the LTA strategy, we proposed a maximum benefit scheduling (MBS) algorithm, which aimed at maximizing the benefits of VCPs. The MBS algorithm determined the acceptable tasks using a pruning strategy. Finally, the experiment results show that our proposed algorithm is more effective than current algorithms in the aspects of benefits, task acceptance rate and task completion rate.

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.

A Performance Study of Secure Data Mining on the Cell Processor

Cyber Crime ◽  
2013 ◽  
pp. 966-978
Author(s):  
Hong Wang ◽  
Hiroyuki Takizawa ◽  
Hiroaki Kobayashi
Keyword(s):  
Data Mining ◽  
Clustering Algorithm ◽  
Hardware Security ◽  
Volunteer Computing ◽  
Cell Processor ◽  
Performance Study ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Secure Data ◽  
Computing Platforms

This article examines the potential of the Cell processor as a platform for secure data mining on the future volunteer computing systems. Volunteer computing platforms have the potential to provide massive computing power. However, privacy and security concerns prevent using volunteer computing for data mining of sensitive data. The Cell processor comes with hardware security features. The secure volunteer data mining can be achieved by using those hardware security features. In this article, we present a general security scheme for the volunteer computing, and a secure parallelized K-Means clustering algorithm for the Cell processor. We also evaluate the performance of the algorithm on the Cell secure system simulator. Evaluation results indicate that the proposed secure data clustering outperforms a non-secure clustering algorithm on the general purpose CPU, but incurs a huge performance overhead introduced by the decryption process of the Cell security features. Possible optimization for the secure K-Means clustering is discussed.

Adaptive Control of Redundant Task Execution for Dependable Volunteer Computing

2011 ◽  
pp. 135-154
Author(s):  
Hong Wang ◽  
Yoshitomo Murata ◽  
Hiroyuki Takizawa ◽  
Hiroaki Kobayashi
Keyword(s):  
Adaptive Control ◽  
Failure Probability ◽  
Task Assignment ◽  
Probability Estimation ◽  
Volunteer Computing ◽  
Data Sets ◽  
Task Dependency ◽  
Computing Platforms ◽  
Multiple Task ◽  
Dispatch Policy

On the volunteer computing platforms, inter-task dependency leads to serious performance degradation for failed task re-execution because of volatile peers. This paper discusses a performance-oriented task dispatch policy based on the failure probability estimation. The tasks with the highest failure probabilities are selected for dispatch when multiple task enquiries come to the dispatcher. The estimated failure probability is used to find the optimized task assignment that minimizes the overall failure probability of these tasks. This performance-oriented task dispatch policy is evaluated with two real world trace data sets on a simulator. Evaluation results demonstrate the effectiveness of this policy.

Evolutionary Algorithms on Volunteer Computing Platforms: The MilkyWay@Home Project

2010 ◽  
pp. 63-90 ◽  
Author(s):  
Nate Cole ◽  
Travis Desell ◽  
Daniel Lombraña González ◽  
Francisco Fernández de Vega ◽  
Malik Magdon-Ismail ◽  
...  
Keyword(s):  
Evolutionary Algorithms ◽  
Volunteer Computing ◽  
Computing Platforms

Computational Micrograph Registration with Sieve Processes

1996 ◽  
Vol 54 ◽  
pp. 440-441
Author(s):  
P.J. Phillips ◽  
J. Huang ◽  
S. M. Dunn
Keyword(s):  
Planar Graph ◽  
Efficient Algorithm ◽  
Spatial Organization ◽  
Spatial Arrangement ◽  
Stereo Image ◽  
Image Model ◽  
Geometric Invariants ◽  
Point Set

In this paper we present an efficient algorithm for automatically finding the correspondence between pairs of stereo micrographs, the key step in forming a stereo image. The computation burden in this problem is solving for the optimal mapping and transformation between the two micrographs. In this paper, we present a sieve algorithm for efficiently estimating the transformation and correspondence.In a sieve algorithm, a sequence of stages gradually reduce the number of transformations and correspondences that need to be examined, i.e., the analogy of sieving through the set of mappings with gradually finer meshes until the answer is found. The set of sieves is derived from an image model, here a planar graph that encodes the spatial organization of the features. In the sieve algorithm, the graph represents the spatial arrangement of objects in the image. The algorithm for finding the correspondence restricts its attention to the graph, with the correspondence being found by a combination of graph matchings, point set matching and geometric invariants.

Energy efficient algorithm for lookup-tables on mobile devices

2016 ◽  
Vol 2016 (7) ◽  
pp. 1-6
Author(s):  
Sergey Makov ◽  
Vladimir Frantc ◽  
Viacheslav Voronin ◽  
Igor Shrayfel ◽  
Vadim Dubovskov ◽  
...  
Keyword(s):  
Mobile Devices ◽  
Efficient Algorithm ◽  
Energy Efficient ◽  
Lookup Tables
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