  Machine-to-Machine (M2M) communication is now playing a market-changing role
in a wide range of business world. However, in event-driven M2M communications,
a large number of devices activate within a short period of time, which in turn
causes high radio congestions and severe access delay. To address this issue,
we propose a Fast Adaptive S-ALOHA (FASA) scheme for M2M communication systems
with bursty traffic. The statistics of consecutive idle and collision slots,
rather than the observation in a single slot, are used in FASA to accelerate
the tracking process of network status. Furthermore, the fast convergence
property of FASA is guaranteed by using drift analysis. Simulation results
demonstrate that the proposed FASA scheme achieves near-optimal performance in
reducing access delay, which outperforms that of traditional additive schemes
such as PB-ALOHA. Moreover, compared to multiplicative schemes, FASA shows its
robustness even under heavy traffic load in addition to better delay
performance.
