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.