A systematic and automatic method for dynamically optimizing medium access control (MAC) protocol parameters is presented. Our meta-protocol approach is capable of performing on-line optimization of critical MAC parameters without knowing in advance what network conditions will arise or how they may fluctuate over time. Furthermore, this dynamic optimization is achieved without any centralized control or exchange of control messages between nodes. The power of the new technique is demonstrated by two examples. In a LAN environment, it outperforms traditional contention based MAC protocols that adjust retransmission probabilities, e.g., employing binary exponential backoff. In a synchronous multi-hop environment, it automatically converges to the proper transmission schedule assignments for the actual node density.

This paper presents ABROAD, an adaptive medium access control (MAC) protocol for reliable broadcast packet transmission in wireless networks. ABROAD incorporates a collision-avoidance handshake within each slot of a synchronous transmission schedule, allowing nodes to reclaim and/or reuse idle slots while maintaining bounded access delay. Thus, ABROAD provides worst-case performance guarantees while remaining adaptive to local changes in traffic load and node connectivity. We analyze the optimal worst-case performance of ABROAD, and show that there is a strict increase in the number of broadcast packets per second over a pure time division multiple access (TDMA) protocol. Extensive simulation confirms our analysis, and also demonstrates that ABROAD outperforms broadcast protocols based on reliable unicast packet delivery schemes, such as the IEEE 802.11 MAC standard.

A systematic and automatic method to dynamically combine any set of existing MAC protocols into a single higher layer, or meta-MAC protocol, is presented. The new approach makes it possible to always achieve the performance of the best component protocol, without knowing in advance which protocol will match the potentially changing and unpredictable network conditions. Moreover, this dynamic optimization is entirely automatic and runs without any centralized control or any exchange of messages, using only local network feedback information. We describe the method and prove that the resulting meta-MAC protocol achieves optimal performance in a well-defined sense. Through simulation on different types of networks and with different component MAC protocols, we demonstrate that our simple and practical combination algorithm yields highly adaptive and scalable MAC solutions.