Abstract-A Constrained Multicommodity Maximum-FlowMinimum-Cost routing algorithm is presented. The algorithm computes maximum-flow routings for all smooth unicast traffic demands within the Capacity Region of a network subject to routing cost constraints. The edge cost can be a distance, reliability, congestion or an energy metric. It is shown that every network has a finite Bandwidth-Cost capacity. The BandwidthDistance and the Bandwidth-Energy capacities are explored. The routing algorithm requires the formulation of two Linear Programs (LPs). The first LP finds a multicommodity MaximumFlow, when the flows are constrained to a sub-graph of the network to enforce cost constraints. The second LP minimizes the routing cost, given that the maximum-flow is fixed. A related Constrained Multicast-Max-Flow-Min-Cost algorithm is also presented, to maximize the throughput of a multicast tree using network coding, subject to routing cost constraints. These algorithms have polynomial-time solutions, whereas traditional multipath routing algorithms can be NP-Hard. The addition of routing cost constraints can significantly reduce the size of the LPs, resulting in faster solutions, with lower edge utilizations and with higher energy efficiencies. The application of these algorithms to route aggregated video streams from cloud data centers in a Future-Internet network, with improved throughput, energy-efficiency and QoS guarantees is presented.
For instance, two routing algorithms subject to routing cost and rigid QoS constraints were proposed in REF , that is, a constrained Unicast-Max-Flow-Min-Cost algorithm (UMFMC) for routing unicast traffic flows and a constrained Multicast-Max-Flow-Min-Cost algorithm (MMFMC) to maximize the throughput of a one-to-many multicast tree while simultaneously minimizing energy costs.
Max-Flow Min-Cost Routing in a Future-Internet with Improved QoS Guarantees
IEEE Transactions on Communications
IEEE Transactions on Communications
Computer Science