Wireless sensor networks (WSNs) are used for event detection and data collection in
a plethora of environmental monitoring applications. However a critical factor limits
the extension of WSNs into new application areas: energy constraints. This thesis
develops self-organising energy efficient data collection and dissemination protocols in
order to support WSNs in event detection and data collection and thus extend the use
of sensor-based networks to many new application areas.
Firstly, a Dual Prediction and Probabilistic Scheduler (DPPS) is developed. DPPS
uses a Dual Prediction Scheme combining compression and load balancing techniques
in order to manage sensor usage more efficiently. DPPS was tested and evaluated
through computer simulations and empirical experiments. Results showed that DPPS
reduces energy consumption in WSNs by up to 35% while simultaneously maintaining
data quality and satisfying a user specified accuracy constraint.
Secondly, an Adaptive Detection-driven Ad hoc Medium Access Control (ADAMAC)
protocol is developed. ADAMAC limits the Data Forwarding Interruption problem
which causes increased end-to-end delay and energy consumption in multi-hop sensor
networks. ADAMAC uses early warning alarms to dynamically adapt the sensing
intervals and communication periods of a sensor according to the likelihood of any
new events occurring. Results demonstrated that compared to previous protocols such
as SMAC, ADAMAC dramatically reduces end-to-end delay while still limiting energy
consumption during data collection and dissemination. The protocols developed in this thesis, DPPS and ADAMAC, effectively alleviate
the energy constraints associated with WSNs and will support the extension of sensorbased
networks to many more application areas than had hitherto been readily possible