Consider the concept of the Utility Model [5]: the optimal allocation of resources of a server or network while meeting the absolute Quality of Service (QoS) requirements of users' multimedia sessions. Past algorithms and heuristics to solve the Utility Model mapped the problem onto a variant of the Combinatorial Knapsack Problem, with server utility (e.g. revenue) as the quantity to be optimized and with user QoS requirements expressed as constraints on the resource allocation. Both optimal (algorithmic) and fast but sub-optimal (heuristic) methods were derived to solve the resulting Multidimensional Multiconstraint Knapsack Problem (MMKP) and hence to perform admission control of proposed user sessions However, previous algorithms and heuristics were restricted to solving the Utility Model on an enterprise network (a network of less than 30 nodes), owing to the need in admission control to solve the problem in real time, typically a few seconds or less. The methods used for the path finding and admission processes had unfavorable computational complexities. As a result, only small (i.e. enterprise) networks could be treated in real time. Also, considerable time was wasted on frequently unnecessary traversals during upgrading. In this thesis we attempt to solve and implement the Utility Model using a modified version of a Multicommodity Flow algorithm, which has better computational complexity than Knapsack Algorithms or many heuristics and hence is capable of finding paths relatively quickly for larger networks. What's more, the Multicommodity flow algorithm used keeps essential information about the current networks and user sessions, thus further reducing the overall admission time.