We have a tendency to study the optimal management of communication networks in the presence of heterogeneous traffic necessities. Specifically, we have a tendency to distinguish the flows into two crucial categories: inelastic for modeling high-priority, delay-sensitive, and fastened-throughput applications; and elastic for modeling low-priority, delay-tolerant, and throughput-greedy applications. We note that the coexistence of such numerous flows creates complex interactions at multiple levels (e.g., flow and packet levels), which stop the utilization of earlier design approaches that dominantly assume homogeneous traffic. In this work, we tend to develop the mathematical framework and novel style methodologies needed to support such heterogeneous requirements and propose provably optimal network algorithms that account for the multilevel interactions between the flows. To that finish, we have a tendency to 1st formulate a network optimization problem that incorporates the above throughput and service prioritization necessities of the 2 traffic sorts. We have a tendency to, then develop a distributed joint load-balancing and congestion control algorithm that achieves the dual goal of maximizing the aggregate utility gained by the elastic flows while satisfying the fixed throughput and prioritization necessities of the inelastic flows. Next, we tend to extend our joint algorithm in 2 ways in which to more improve its performance: in delay through a virtual queue implementation with minimal throughput degradation and in utilization by permitting for dynamic multipath routing for elastic flows. A distinctive characteristic of our proposed dynamic routing answer is that the novel 2-stage queueing architecture it introduces to satisfy the service prioritization demand.
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