We consider packet transmission scheduling at the MAC-layer via adaptive backoff algorithms that are favorable in terms of queue occupancies in a wireless network. General network topologies are considered under the operational constraint that transmitters within close proximity of each other cannot be transmitting simultaneously. Transmitters probe the channel at random instants and transmit if the channel is idle. We adopt a measurement based framework in which channel probing rates are adaptively determined based on feedback measured from the network. We consider two separate objectives associated with minimization of packet delay and packet loss rate in the network. We obtain dynamic algorithms that strictly improve channel access rates in a related fluid model. Analytical development of the algorithms is based on a convenient decomposition technique that decouples channel access and queue occupancy statistics, and that leads to a favorable tradeoff between analytical insight and modeling accuracy. Obtained algorithms are oblivious to network load and topology. We also consider versions of these algorithms that are suitable for distributed implementation and study their effectiveness numerically.