Ad-hoc wireless networks use multi-hop transmissions to communicate, without exploiting any infrastructure. Logical links create unreliable connections between nodes: the capacity of the channel can unpredictably change due to the presence of obstructions, interferences between nodes and stochastic phenomena such as fading. Moreover the medium is multi-access and resources are contended by different users. It is possible to notice that adjusting the power at the physical layer affects the interference perceived, which in turn modifies the resources availability, alters the queue length at the network layer and eventually influences the source rates at the transport layer. To this end, a lot of works have shown that a better understanding of inherent coupling between different layers in the networking stack is worth. Specifically, network performances can be increased if the traditionally separated network layers are jointly optimized. Network utility maximization has emerged as a powerful framework for studying such cross-layer issues and optimizing performances overall the network. In particular, we focus on distributed cross-layer algorithms that achieve a global optimum recurring to local information only.
Although the literature is vast in this field, most of works remain as theory. We aim at clarifying the practical feasibility of such theoretical dissertations and what considerations are needed in order to establish a bridge between theory and practice. After analyzing different crosslayer methods, we focus on the work of Papandriopoulos et al.. We first discuss its theoretical benefits in an interference limited system such as CDMA, without accounting physical constraints of the network. In order to validate the performances in a more realistic scenario, we implement the algorithm of Papandriopoulos et al. in the NS-2 network simulator without breaking up the hierarchy of the standard ISO/OSI stack. We focus on modeling physical, data link, network and transport layer, underlining issues and possible solutions from a practical perspective. For instance, we propose a novel approach to calculate the congestion prices of the network.
After discussing benefits and drawbacks of the underlying theory, we propose several results under many simulation scenarios and eventually a comparison with the standard protocol for wireless networks IEEE/802.11.
2008. , 120 p.