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.

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.

scholarly journals Pulsar Discovery by Global Volunteer Computing: Fig. 1

Science ◽  
2010 ◽  
Vol 329 (5997) ◽  
pp. 1305-1305 ◽  
Author(s):  
B. Knispel ◽  
B. Allen ◽  
J. M. Cordes ◽  
J. S. Deneva ◽  
D. Anderson ◽  
...  
Keyword(s):  
Survey Data ◽  
Large Data ◽  
Large Data Sets ◽  
Volunteer Computing ◽  
Data Sets ◽  
Pulse Profile ◽  
Computing Power ◽  
Spin Period ◽  
Arecibo Observatory ◽  
Computer Power

Einstein@Home aggregates the computer power of hundreds of thousands of volunteers from 192 countries to mine large data sets. It has now found a 40.8-hertz isolated pulsar in radio survey data from the Arecibo Observatory taken in February 2007. Additional timing observations indicate that this pulsar is likely a disrupted recycled pulsar. PSR J2007+2722’s pulse profile is remarkably wide with emission over almost the entire spin period; the pulsar likely has closely aligned magnetic and spin axes. The massive computing power provided by volunteers should enable many more such discoveries.

Failure probability estimation of steam turbine blades by enhanced Monte Carlo Method

2015 ◽  
Vol 56 ◽  
pp. 80-88 ◽  
Author(s):  
J.A. Rodríguez ◽  
J.C. Garcia ◽  
E. Alonso ◽  
Y. El Hamzaoui ◽  
J.M. Rodríguez ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Steam Turbine ◽  
Failure Probability ◽  
Turbine Blades ◽  
Probability Estimation ◽  
Steam Turbine Blades
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