Context modeling in collaborative sensor network applications

A new WSN context model is developed to efficiently capture multiple context parameters in multiple dimensions and adjust the network behavior accordingly while simultaneously balancing the network load.

Abstract

The design of context aware protocols in Wireless Sensor Networks (WSNs) is an emerging challenge. The interpretation of the sensed information greatly depends on the context and for efficient processing and communication, context awareness can play a major role. In most of the existing WSN protocols, context awareness is exploited in a single dimension and is captured either at the application layer or at the routing layer using a single context parameter. In this paper, we develop a new WSN context model to efficiently capture multiple context parameters in multiple dimensions (i.e. context from/to different layers of the network stack) and adjust the network behavior accordingly while simultaneously balancing the network load. The new model not only considers context parameters reflecting run-time application demands from a node, but also takes into consideration the current state of the node as well as the state and demands of neighboring nodes (inter-nodal context sharing). The new model: (a) represents context demands from each layer; (b) reflects the current individual state of each layer; (c) communicates (a) and (b) to the neighboring nodes to impact the decision process; and (d) locally distributes available resources aiming to achieve an optimal load balance. We show the application of this model in realizing a cross-layer optimized protocol for routing multi-hop and multi-packet traffic in WSNs.