Real-Time Traffic Management in Sensor Networks

In this work we propose a traffic management mechanism to support real-time flows in highly unpredictable sensor network environments. The mechanism is based on a joint traffic regulation and end-to-end scheduling approach; a traffic regulation component adjusts the incoming packet rate to implicitly control the channel load and intelligently rejects packets that are more likely to miss their deadline while a laxity-based scheduling component projects the packets' per-hop delay and compensates for network end-to-end delays. Thus, high success ratios without severely degrading the fidelity are achieved. Our mechanism attempts to maintain accuracy in a resource-efficient manner even under extremely unstable network conditions where delays are difficult to model and compute. Furthermore, the adoption of a component-based approach allows for substantial independence from both the MAC and routing layers. We thoroughly evaluate our mechanism and demonstrate its accuracy and performance merits