Variants of the carrier-sense multiple access (CSMA) protocol has been employed in many communications protocols such as the IEEE 802.11 and Ethernet standards. CSMA based medium access control (MAC) mechanisms have been recently proposed for other communications scenarios such as sensor networks and acoustical underwater networks. Despite its widespread use, the performance of the CSMA protocol is not well-studied from the perspective of these newly encountered networking scenarios. We here investigate the performance of the CSMA protocol from the point of three different aspects: throughput in networks with large propagation delay, short-term fairness for delay sensitive applications in large networks and energy efficiency-throughput trade-off in networks with battery operated devices. Firstly, we investigate the performance of the CSMA protocol for channels with large propagation delay. Such channels are recently encountered in underwater acoustic networks and in terrestrial wireless networks covering larger areas. However, a mathematical model of CSMA performance in such networks is not known. We propose a semi-Markov model for a 2-node CSMA channel and then extend this model for arbitrary number of users. Using this model, we obtain the optimum symmetric probing rate that achieves the maximum network throughput as a function of the average propagation delay, ¯d, and the number of nodes sharing the channel, N. The proposed model predicts that the total capacity decreases with ¯d −1 as N goes to infinity when all nodes probe the channel at the optimum rate. The optimum probing rate for each node decreases with 1/N and the total optimum probing rate decreases faster than ¯d −1 as N goes to infinity. Secondly, we investigate whether the short-term fairness of a large CSMA network degrades with the network size and density. Our results suggest that (a) the throughput region that can be achieved within the acceptable limits of shortterm fairness reduces as the number of contending neighboring nodes increases for random regular conflict graphs, (b) short-term fair capacity weakly depends on the network size for a random regular conflict graph but a stronger dependence is observed for a grid topology. We also present related results from the statistical physics literature on long-range correlations in large systems and point out the relation between these results and short-term fairness of CSMA systems. Thirdly, we investigate the energy efficiency of a CSMA network proposing a model for the energy consumption of a node as a function of its throughput. We show that operating the CSMA network at a very high or at a very low throughput is energy inefficient because of increasing carrier-sensing and sleeping costs, respectively. Achieving a balance between these two opposite operating regimes, we derive the energy-optimum carrier-sensing rate and the energy-optimum throughput which maximize the number of transmitted bits for a given energy budget. For the single-hop case, we show that the energy-optimum total throughput increases as the number of nodes sharing the channel increases. For the multi-hop case, we show that the energy-optimum throughput decreases as the degree of the conflict graph of the network increases. For both cases, the energy-optimum throughput reduces as the power required for carrier-sensing increases. The energy-optimum throughput is also shown to be substantially lower than the maximum throughput and the gap increases as the degree of the conflict graph increases for multi-hop networks.