Resource management for next generation heterogeneous networks

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The next generation networks (NGN) are envisioned to be an inter-working environment of heterogeneous transport networks that will provide a service platform that can integrate traditional and innovative IP services. These services should be available at any user location that can be also changing with time due to the user mobility. The heterogeneity of NGNs will have several dimensions that can be divided into two categories associated with technology and ownership, respectively. In particular the technology heterogeneity will require coopearation between wired and several wireless acces technologies such as 3G, 4G, WLAN, WiMAX, satellites, including wireless mesh. The resource management in such heterogeneous networks can be quite complex and to a large extent heuristic, which can lead to large inefficiencies, unless new models are developed that can address the issue in an automated and simple to understand manner. Therefore we propose to develop an integrated and consistent framework and mechanisms that would significantly facilitate NGN resource management and make it more efficient. The framework will be based on an economical model that can integrate and automate several timescales of operations and therefore can further reduce the network operation costs. Here we will use our experience and achievements with an economic model that was developed for homogeneous wired networks. In this proposal we address three main elements of resorce management: connection/flow admission and routing, adaptation of network capacity, and service pricing. The main challenges are related to extension of the economic models to wireless access networks and to encouraging coopeartion between network operators. To overcome these challenges we will use models derived from Markov decision and game theories. We expect that the results of this research will provide algorithms and knowledge that will be used by Canadian operators to improve service quality and resource utilization in a cost efficient manner.