# Task Migration with Partitioning for Load Balancing in Collaborative Edge Computing
## 4 Simulation Results and Discussion
_Proposed_ shows better performance than _IPSO_ in terms of load variance because proposed considers load difference to determine the task migration. _IPSO_ shows better performance than _Nearest_, _Random_ and _Least_, because it is affected by the delay, especially the queueing delay associated with the load of the MECS. Figure 10 depicts the average blocking rate and standard deviation of the blocking rate with varying arrival rates. The blocking rate is defined as the ratio of the number of tasks blocked by the MECS to the total number of offloaded tasks. The task is blocked by the MECS when the task is offloaded to a MECS whose queue is full. In _Nearest_ and _Random_, the target MECS may be another overloaded MECS or may become overloaded owing to concentrating tasks on it. In _Least_, because tasks in overloaded MECSs are migrated to the least loaded MECS, the least-loaded MECS becomes overloaded. Therefore, because some MECSs have a high load, the task may be blocked when it is offloaded to the MECS with a high load. In _IPSO_, when all MECSs in MEC system do not meet the delay constraints for the subtasks, the subtasks migrate to the MECS that minimizes the computing delay. In this case, since only the processing delay is considered, there is likely that the overloaded MECS is selected. _Proposed_ not only had the lowest blocking rate but also the smallest standard deviation compared with the other methods because the load was relatively well distributed. The system throughput with varying arrival rates is shown in Figure 11. The system throughput is defined as the multiplication of the number of tasks completed per time slot by the average task size. When the loads are balanced among the MECSs, the block rate decreases. In addition, if the block rate decreases, more tasks can be performed; thus, the system throughput increases. Figures 12 and 13 show the rate of task completion within the delay constraints and task reliability rate, respectively. The task completion rate within the delay constraints is affected by the task execution delay consisting of transmission, queueing, execution, and migration delay. Similarly, task reliability is affected by the task execution delay. A migration delay is the time a task is migrated to another MECS, which does not account for most of the total delay because it uses wired links. The queueing delay is affected by the load of the MECS, that is, the length of the queue of the MECS. Increasing the parallelism of task execution reduces the execution delay. Therefore, the better the loads of MECSs are distributed, the less the queuing delay affected by the MECS load and queue length,  
Figure 8: Task reliability rates for mobility speed. increasing the task completion rate within the delay constraints. The task completion rate of _Proposed_ was approximately 18-58% higher than that of other methods. If the task execution delay is prolonged, the vehicle may move out of the coverage of the MECS, which is offloaded to the task during a service session. Thus, service interruption may occur more often in receiving its result. To receive the result without the service interruption, the loads of the MECS must be appropriately distributed to reduce the task execution delay. The reliability rate of _Proposed_ was approximately 12-46% higher than that of the other methods because it distributed the loads of MECSs well. Figure 9: Load variance among MECSs of the five methods; **(a)** vehicle arrival rate = 0.3.; **(b)** vehicle arrival rate = 0.6; **(c)** vehicle arrival rate = 0.9. Figure 11: System throughput for vehicle arrival rate. Figure 4:0 Task completion rates for vehicle arrival rate. Figure 4:1 Blocking rates for vehicle arrival rate.