(Created page with " == Abstract == This thesis focuses on the QoS-constrained Traffic Engineering (TE) of Wireless Mesh Networks (WMNs) affected by Multiple Access Interference (MAI). The goal...") |
m (Scipediacontent moved page Draft Content 814768669 to Polli 2012a) |
(No difference)
|
This thesis focuses on the QoS-constrained Traffic Engineering (TE) of Wireless Mesh Networks (WMNs) affected by Multiple Access Interference (MAI). The goal is to develop a tool for the optimization of network/physical resource allocation that enable to design WMNs supporting multicast multimedia sessions with different Quality of Service (QoS) requirements when intra-session Network Coding (NC), besides routing, can be performed at the network nodes. A wide-applicability integrated framework is proposed, that allows to jointly optimize session utilities, flow control, QoS differentiation, intra-session network coding, Media Access Control (MAC) design and power control. To cope with the nonconvex nature of the resulting cross-layer optimization problem, this thesis proposes a two-level decomposition that provides the means to attain the optimal solution through suitably designed convex subproblems. Sufficient conditions for the feasibility of the primary (nonconvex) problem and for the equivalence to its related (convex) version are derived. Furthermore, a general procedure to devise simple polyhedral outer-bounds of the capacity region, which will be shown to have a key role in the decomposition, has been developed. Algorithmic implementation of the two-level decomposition is discussed in both centralized and distributed approaches. Moreover, the asynchronous, iterative Distributed Resource Allocation Algorithm (DRAA), that quickly self-adapts to network time-evolutions (e.g., node failures and/or fading fluctuations), is developed. Numerical results that delve into the potential of both the proposed solution and the resource allocation algorithm, are provided. In detail, the two-level decomposition will be tested in unicast, multicast and multisource scenarios so as to show the performance gain achievable by the joint optimization with respect to the conventional solutions.
The different versions of the original document can be found in:
Published on 01/01/2012
Volume 2012, 2012
Licence: Other
Are you one of the authors of this document?