Information Retrieval and Processing in Sensor Networks: Deterministic Scheduling Versus Random Access

We investigate the effect of medium-access control (MAC) used in information retrieval by a mobile access point (AP) on information processing in large-scale sensor network, where sensors are unreliable and subject to outage. We focus on a 1-D sensor network and assume that the location information is available locally at each sensor and unavailable to the AP. For a fixed collection interval, two types of MAC schemes are considered: the deterministic scheduling, which collects data from predetermined sensors locations, and random access, which collects data from random locations. We compare the signal estimation performance of the two MACs, using the expected maximum distortion as the performance measure. For large sensor networks with fixed density, we show that there is a critical threshold on the sensor outage probability P
_out
-For _P
_out
< e
^{-lambda(1+o(1))}
, where lambda is the throughput of the random access protocol, the deterministic scheduling provides better reconstruction performance. However, for P
_out
> e
^{-lambda(1+o(1))}
, the performance degradation from missing data samples due to sensor outage does not justify the effort of scheduling; simple random access outperforms the optimal scheduling.