## 4 Algorithm Description
### The Deadline Preference Dispatch Scheduling (DPDS) Algorithm
The completion rate is defined as follows:

\[\text{completion rate}=\text{number of tasks completed on time/number of tasks in the task set }T, \tag{2}\]

#### 5.1.1 The Impact of Average Size of Tasks

As shown in Figure 8, we test the impact of the different average size of tasks on the performance of the algorithms. It can be seen that IDCS perform the best among the three algorithms in both the number of the completed tasks and completion rate, and the MOC algorithm is slightly worse than the IDCS algorithm. The DPDS algorithm is much less efficient. This is because the IDCS algorithm divides the task priority, which can ensure that the IDCS algorithm completes the less expensive task first, and discards the risky task. In contrast, the DPDS algorithm can't fully utilize the computing power of the volunteer computing system. Even if it encounters the task that is expensive, the DPDS algorithm will also calculate it, which causes a waste of computing resources. Since the objective of MOC is complete each task before its deadline, it is less efficient than the IDCS algorithm. Moreover, since the computing power of the system is fixed in a certain period of time, the performance of three algorithms decreases as the average size of tasks increases. #### 5.1.2 The Impact of Task Set Scale

In Figure 9, we analyze the impact of task set scale. It can be seen that with the increase of the task set scale, the number of the completed task of the three algorithms finally tends to be stable. This is because the number of nodes does not increase, but the number of tasks increases. Therefore, the number of the completed tasks by VN is changeless. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Default** & **Value Range** \\ \hline average size of tasks(unit) & 4 & 3–9 \\ task set scale & 20 & 10–30 \\ the number of VN & 700 & 500–1000 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Experimental default parameters. Figure 8: The impact of the average size of the tasks on the performance of the algorithms: (**a**) The impact of average size of tasks on task completion rate; (**b**) the impact of the average size of tasks on number of the tasks completed. At the same time, it can be seen from Figure 9b that the larger the size of the task set scale is, the more the number of tasks completed by the IDCS algorithm is. This is mainly because IDCS can make full use of computing resources to discards the tasks with high risks, which improves the number of tasks completed. The task completion rate of the three algorithms decreases with the task set scale increase. This is because the number of tasks has increased, but there has been no relative increase in computing resources. In Figure 9a, it is obvious that the increase of task set scale has the least impact on IDCS algorithm. #### 5.1.3 The Impact of the Number of Volunteer Nodes

Figure 10 shows the impact of the number of volunteer nodes on the performance of the algorithms. It can be seen that the task completion rate increases when the number of volunteer nodes increases, and the number of the completed tasks also increases. This is because the more nodes there are, the more computing power there is. At the same time, the IDCS algorithm is superior to the MOC algorithm and DPBS algorithm in both task completion rate and the number of the completed tasks. Figure 10: The impact of the number of volunteer nodes on the performance of the algorithms: (**a**) The impact of the number of volunteer nodes task completion rate; (**b**) the impact of the number of volunteer nodes on the number of tasks completed. Figure 9: The impact of task set scale on the performance of the algorithms: (**a**) The impact of task set scale on task completion rate; (**b**) the impact of the task set scale on the number of tasks completed. ### Experimental Results and Analysis of Dynamic Task Sets

In order to be closer to the real application scenario, this section uses a dynamic set of application tasks.