Randomized binary exponential backoff (BEB) is a popular algorithm for coordinating access to a shared channel. With an operational history exceeding four decades, BEB is currently an important component of several wireless standards. Despite this track record, prior theoretical results indicate that under bursty traffic (1) BEB yields poor makespan and (2) superior algorithms are possible. To date, the degree to which these findings manifest in practice has not been resolved. To address this issue, we examine one of the strongest cases against BEB: @math packets that simultaneously begin contending for the wireless channel. Using Network Simulator 3, we compare against more recent algorithms that are inspired by BEB, but whose makespan guarantees are superior. Surprisingly, we discover that these newer algorithms significantly underperform. Through further investigation, we identify as the culprit a flawed but common abstraction regarding the cost of collisions. Our experimental results are complemented by analytical arguments that the number of collisions -- and not solely makespan -- is an important metric to optimize. We believe that these findings have implications for the design of contention-resolution algorithms.
Binary Exponential Backoff (BEB) is a key component of the IEEE 802.11 DCF protocol. It has been shown that BEB can achieve the theoretical limit of throughput as long as the initial backoff window size is properly selected. It, however, suffers from significant delay degradation when the network becomes saturated. It is thus of special interest for us to further design backoff schemes for IEEE 802.11 DCF networks that can achieve comparable throughput as BEB, but provide better delay performance. This paper presents a systematic study on the effect of backoff schemes on throughput and delay performance of saturated IEEE 802.11 DCF networks. In particular, a backoff scheme is defined as a sequence of backoff window sizes @math . The analysis shows that a saturated IEEE 802.11 DCF network has a single steady-state operating point as long as @math is a monotonic increasing sequence. The maximum throughput is found to be independent of @math , yet the growth rate of @math determines a fundamental tradeoff between throughput and delay performance. For illustration, Polynomial Backoff is proposed, and the effect of polynomial power @math on the network performance is characterized. It is demonstrated that Polynomial Backoff with a larger @math is more robust against the fluctuation of the network size, but in the meanwhile suffers from a larger second moment of access delay. Quadratic Backoff (QB), i.e., Polynomial Backoff with @math , stands out to be a favorable option as it strikes a good balance between throughput and delay performance. The comparative study between QB and BEB confirms that QB well preserves the robust nature of BEB and achieves much better queueing performance than BEB.