Abstract-We consider the question of what performance metric to maximize when designing ad-hoc wireless network protocols such BS routing or MAC. We focus on maximizing rates under battery Lifetime and power constraints. Commonly used metria are total capacity (in the case of cellular networks) and transport capacity (in the case of ad-hoc networks). However, it is known in traditional wired networking that maximizing total capacity cnnflids with fairness. and this is why fairness oriented rate allocations, such as max-min fairness, are often used. We review this issue for wireless ad-hoc networks. Indeed, the mathematical model fnr wireless networks has a specificity that makes some of the findings different. It has been reported in the literature on Ultra Wide Band that gross uniairness occurs when maximizing total capacity or transport capacity ,and we confvm hy a theoretical analysis that this is a fundamental shortcoming of such metria in wireless ad-hoe networks, as it is for wired networks. The story is different for max-min fairnes. Although it is perfectly viable for a wired network, it is much less w in our setting. We show that, in the limit of long hattery lifetime. the max-min allocation of r a t s always leads to strictly equal rates, regardless of the MAC layer, network topology, choice of mutes and power constraints. This is due to the "solidarity" property of the set of feasible rates. This results in all flows receiving the rate of the worst flow, and leads to severe inefficiency. We show numerically that the problem persists when battery Lifetime constraints are finite. This generalizes the ohservation reported in the literature that. in heterogeneow settings. 802.11 allocates the worst rate to all stations, and shows that this is inherent to any protocol that implements max-min fairness. Proportional fairness is an alternative to max-min fairness that approximates rate allocation performed by TCP in the Internet. We show by numerical simulations that proportional fairness of rates or transport rates is mhust and achieves a good trade-off between efficiency and fairness, unlike total rate or maximum fairness. We thus recommend that metria for the rate performance of mobile ad-hoc networking pmtocols he based on proportional fairness. [41) . In conuast. some sensor networks put more emphasis on minimizing energy under minimum rate consuaints. We study here the former and leave the latter to a companion paper. For cellular wireless networks. a frequently chosen performance metric is total capacity. i.e. the sum of the rates of all flows. An extension that maximizes a weighted sum of the rates is applied in CDMA/HDR [5]. In multi-hop wireless networks, the same mevics are used. but also uauspon capacity, a variant popularized by Gupta and Kumar in [61. This is in fact a weighted sum of rate, where weights are the distances between the source and the destination of each How. The tradition in wired networking has also focused on performance meuics that incorporate some form of fairness. Indeed, it is known that considering only total capacity yields goss unfairness if implemented in a wired network [71. There-fore. different performance meuics that account for fairness have been developed. A typical example is maw-min fairness [SI. which is used in many existing networking protocols. including the ABR mode of ATM [9]. This is an egalitarian approach by which the rate of a How can be increased only when it is not possible to increase the rate of an already smaller How. Max-min fairness is often viewed as an extreme fairness; this justifies using a fairness inde.r. which measures the departure from max-min fairness (it is a slight variant of the fairness index defined by Jain in [IO]; see Section 111-D).
Other relevant prior work includes a discussion of the trade-off between network capacity and fairness for heterogeneous multihop wireless networks REF , which concludes with advocacy of proportional fairness as a reasonable compromise between rate efficiency and fairness, and observes that max-min fairness yields poor performance because all flows obtain essentially the same rate as the minimum rate flow.
Rate performance objectives of multihop wireless networks
IEEE INFOCOM 2004
IEEE INFOCOM 2004
Computer Science