A Dynamic Job Scheduling Method for Reliable and High-Performance Volunteer Computing

This paper proposes a dynamic job scheduling method for reliable and high-performance volunteer computing. In volunteer computing, each job is replicated and allocated to multiple participants (workers) to remove incorrect results by a voting mechanism. Hence, the number of workers necessary to complete a job is an important factor for the system performance; however, this is not well-considered in the existing methods. The proposed method defines the expected probability of completion for each job based on the worker's secession probability. By allocating each job so that the expected probability is always greater than a specified value, the proposed method avoids excess job allocation, which leads to the higher performance. The performance of the proposed method is evaluated by computer simulation, under the two scenarios of workers having uniform and different processing speeds. It is found that the performance of the proposed method is higher than the existing method especially under the practical latter scenario.