Multi-objective optimization based flow control in multipoint-to-point communication

Multipoint-to-point communication allows a group of sources to transfer data to one destination. A major requirement of flow control for such connections is to ensure a fair allocation of resources while maintaining a high level of resource utilization. This work treats multipoint-to-point flow control as a multiple-objective optimization problem and presents a theoretical centralized model to compute rate allocations based on this global optimization. Three control objectives have been identified as critical to the flow control of multipoint-to-point connections: overall network throughput; fairness amongst sources; fairness amongst groups. The theoretical model is a linearly constrained quadratic programming model with an objective of minimizing the weighted sums of individual objective functions. The weighting factors become tuning factors with which decision makers can set their decision preferences. It is shown that the three objectives may indeed conflict with each other, and, by varying the values of tuning factors, an optimum rate allocation can be achieved to realize many flavors of objective mix.