Comparison With Other Resource Sharing Policies
If there are large differences between the "cost" of each data flow, which is the case especially in wireless networking, resources may be assigned to only one or very few data flows per physical channel in the network. If there are many simultaneously active data flows, a majority of the data flows will have to wait until the most inexpensive flows have no more data to transfer, and will suffer from scheduling starvation.
A maximum throughput scheduling policy may be tempting since it would optimize the resource utilization in a given network, but it would not be likely to maximize profit for the network operator. The levels of customer satisfaction would remain low due to many customers experiencing long or permanent service outages.
Proportional fairness would result in lower throughput, but starvation would be avoided.
Max-min fairness would result in even lower throughput, but higher level of fairness, meaning that the service quality that each data flow achieves would be even more stable.
Unlike max-min fair scheduling based on the fair queuing or round robin algorithms, a maximum throughput scheduling algorithm relies on the calculation of a cost function, which in wireless networks may require fast and truthful measurement of the path loss. Proportional fairness based on weighted fair queuing also require measurement or calculation of the cost function.
Read more about this topic: Maximum Throughput Scheduling
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