Modeling Job Lifespan Delays in Volunteer Computing Projects

Volunteer Computing (VC) projects harness the power of computers owned by volunteers across the Internet to perform hundreds of thousands of independent jobs. In VC projects, the path leading from the generation of jobs to the validation of the job results is characterized by delays hidden in the job lifespan, i.e., distribution delay,in-progress delay, and validation delay. These delays are difficult to estimate because of the dynamic behavior and heterogeneity of VC resources. A wrong estimation of these delays can cause the loss of project throughput and job latency in VC projects. In this paper, we evaluate the accuracy of several probabilistic methods to model the upper time bounds of these delays. We show how our selected models predict up-and-down trends in traces from existing VC projects. The use of our models provides valuable insights on selecting project deadlines and taking scheduling decisions. By accurately predicting job lifespan delays, our models lead to more efficient resource use, higher project throughput, and lower job latency in VC projects.

志愿计算（VC）项目利用互联网上志愿者所拥有的计算机的力量来执行数十万项独立任务。在VC项目中，从任务产生到任务结果验证的路径的特点是任务生命周期中隐藏着延迟，即分发延迟、进行中延迟和验证延迟。由于VC资源的动态行为和异构性，这些延迟很难估计。对这些延迟的错误估计可能会导致VC项目中项目吞吐量的损失和任务延迟。在本文中，我们评估了几种概率方法对这些延迟的上限时间进行建模的准确性。我们展示了我们所选的模型如何预测现有VC项目中的跟踪数据的上升和下降趋势。我们的模型的使用为选择项目期限和做出调度决策提供了有价值的见解。通过准确预测任务生命周期延迟，我们的模型能使VC项目中资源利用更高效、项目吞吐量更高以及任务延迟更低。