Lead


Lay summary

Energy efficiency is a major concern in the design of Wireless Sensor Networks (WSNs) and their communication protocols. As the radio transceiver typically accounts for a major portion of a WSN node's energy consumption, researchers have proposed Energy-Efficient Medium Access (E2-MAC) protocols that switch the radio transceiver off for a major part of the time. Today's E2-MAC protocols are able to deliver little amounts of data with a low energy cost, but fail to adapt to changing traffic loads and changing requirements (e.g. throughput and delay constraints) of the imposed traffic. They are generally not sufficiently adaptive with respect to traffic. This project will investigate, develop, and evaluate mechanisms targeting at adaptive and flexible behaviour of E2-MAC protocols that are able to perceive variations in the traffic and its requirements and react to these variations in a timely manner. Similarly as in dynamic voltage scaling an adaptive E2-MAC protocol to be developed should react to changing traffic requirements by (de)allocation of battery resources by correspondingly tuning the radio transceiver, and should further be able to prioritize high priority frames versus frames of lower priority. We will evaluate metrics to assess and quantify the effects of our developed protocol mechanisms and compare them with existing approaches. Our goal is to design an adaptive E2-MAC protocol that in case of low traffic rates of low importance offers data delivery at a low energy cost, which however can adaptively change its behaviour in order to fully exploit the channel capacity whenever the traffic intensity and/or the traffic requirements require it. Applications of priority schemes are manifold: in sensor network applications, messages may have different levels of importance, e.g., alarm messages vs. periodic reporting messages, or signalling messages vs. data messages of higher layer protocols. Application scenarios of flexible, adaptive and mature E2-MAC protocols are manifold - we particularly envisage monitoring systems for the health-care system, but also the broad area of environmental monitoring sensor networks, e.g. networks deployed to alert in case of environmental dangers, such as fire, flood, rock fall or avalanches. More information about the project can be found at http://www.iam.unibe.ch/~hurni/TRAWSN.