Cooperative Locality-aware Data Processing in
Heterogeneous Wireless Sensor Networks
Abstract
Wireless Sensor Networks deployed in recent years often share the commonality of relying on homogeneous hardware platforms. The upcoming vision of the Internet of Things, how- ever, is strongly based on the co-existence of embedded devices manufactured and operated by different stakeholders. While heterogeneity was primarily seen as an obstacle in the past, and numerous ways to compensate for it had been devised, this shift will turn device heterogeneity into an omnipresent characteristic of future sensor network deployments. In this paper we present CLAP, a collaborative data processing approach that exploits device heterogeneity for collaborative data processing, instead of trying to mitigate its effects. CLAP is interoperable with many data collection and routing protocols and offers a dynamic discovery of in-network processing services on nearby devices with higher computational power. The volume of traffic in the network can be reduced when CLAP is used to collaboratively process data in the network, and thus energy savings be attained. In several simulations, we demonstrate the benefits of having data processed by a neighboring (one-hop or two-hop) device instead of forwarding it to its destination without processing.
