### Fair share
Its goal is to distribute the load evenly across all workers. To achieve this, the strategy keeps track of the average task execution time for each worker and assigns the next task to the worker with the lowest task end prediction time: `task_end_prediction = max(current_time, task_end_prediction) + average_task_execution_time`.
-By default, the strategy uses the average task execution time for each worker but it can be configured to use the event loop utilization (ELU) active time instead.
+By default, the strategy uses the average task execution time for each worker but it can be configured to use the task event loop utilization (ELU) active time instead.
### Weighted round robin
-The strategy assigns the next task using a robin round algorithm. The worker weights are maximum tasks execution time, once the worker has reached its maximum tasks execution time, the next task is assigned to the next worker.
+The worker weights are maximum tasks execution time, once the worker has reached its maximum tasks execution time, the next task is assigned to the next worker. The default worker weights are the same for all workers and is computed given the CPU cores speed and theirs numbers.
### Interleaved weighted round robin
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