UC San Diego

In this study, we consider two types of interference limited multi-hop networks. The first type is a micro- buffered multi-hop networks, whereas the second type is a CDMA based multi-hop wireless access network. Micro- buffered networks are high speed packet switched networks, and consist of either nodes with no buffering or nodes with limited buffering such that there is no specific collision resolution mechanism inside the core. Packet losses inside the core are dealt with using end-to-end or edge-to-edge coding techniques. In this study, we discuss the rate allocation problem for a micro-buffered high speed network. First the classical slotted aloha type protocols with exponential backoff are examined and it is observed that such mechanisms may result in unfair rate allocations. Next, we consider weighted alpha-proportional , weighted max-min and hierarchical max-min fair rate assignments. Simple distributed algorithms achieving these notions of fairness by exchanging local information are discussed. It is found that weighted max-min fair information rate allocation assigns information rates to each flow in the same group inversely proportional to their weights. Furthermore, we also show that hierarchical max-min fairness can be achieved in a micro-buffered network if and only if weighted max-min fairness among the flows is ensured. Secondly, the problem of end-to-end weighted max-min fair rate assignment in a two-channel multi-hop CDMA wireless access network is discussed. We show that end-to-end weighted global max-min fairness (hierarchical as well as flow-based) can be achieved by a simple extension of mac-layer fairness. In particular, we show that weighted end-to-end flow-based as well as hierarchical global max-min fairness can be simply insured if and only if weighted mac-layer max-min and weighted transport-layer max-min fair rates are achieved. The same results can easily be shown to be valid for more general wireless networks, which will be briefly discussed in this study as well. In addition, we discuss a mac-layer algorithm, MAC-alpha-G algorithm, that, with careful choice of parameters, not only provides weighted alpha- proportional fairness at the mac layer, but also leads to end-to-end weighted global max-min fairness (both flow- based and hierarchical) with an appropriate higher-layer protocol (i.e. weighted transport-layer max-min fair protocol)