Adaptive beamforming and rate control in real-time wireless sensor networks for QoS optimization
William S. Hortos · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Quality-of-service (QoS) metrics for sensor types in a wireless sensor network (WSN) can be associated with metrics for multimedia that describe the quality of fused information, e.g., throughput, delay, jitter, packet error rate, information correlation, congestion, etc. These QoS metrics are typically set by the application layer of the protocol stack. Application-layer metrics, in turn, depend on the support from lower protocol layers: session, transport, network, data link (MAC), and physical. Protocol dependencies of QoS metrics motivate a cross-layer design approach to QoS optimization for heterogeneous sensor types in a WSN. Cross-layer interactions in the protocol are represented, in previous work by the author, by a set of concatenated parameters and resource levels. The best cross-layer designs that optimize QoS are established by applying the general theory of martingale representations to parameterized multivariate point processes (MVPPs) for discrete random events occurring in the WSN. Adaptive control of WSN behavior through cross-layer design is realized through parametric factorization of stochastic conditional rates of the MVPPs. Cross-layer parameters that optimize QoS are determined in solutions to stochastic dynamic programming conditions derived from models of transient flows of heterogeneous data. Adaptive transmit beamforming, simplified as sectored antennas, and rate control at sensor nodes are introduced to enhance the performance metrics of successful throughput, known as goodput, congestion, capacity, etc. Adaptive antenna and rate controls are parametrized in realtime cross-layer models of WSN dynamics. Simulations demonstrate that adaptive antenna directionality and rate allocations improve overall QoS performance of a baseline design without such adaptation.