RideSharing: Fault Tolerant Aggregation in Sensor Networks Using Corrective Actions

Abstract

In wireless sensor networks (WSNs), the users' objective is to extract useful global information by collecting individual sensor readings. Conventionally, this is done using in-network aggregation on a spanning tree from sensors to data sink. However, the spanning tree structure is not robust against communication errors; when a packet is lost, so is a complete subtree of values. Multipath routing can mask some of these errors, but on the other hand, may aggregate individual sensor values multiple times. This may produce erroneous results when dealing with duplicate-sensitive aggregates, such as SUM, COUNT, and AVERAGE. In this paper, we present and analyze two new fault tolerant schemes for duplicate-sensitive aggregation in WSNs: (1) cascaded ridesharing and (2) diffused ridesharing. These schemes use the available path redundancy in the WSN to deliver a correct aggregate result to the data sink. Compared to state-of-the-art, our schemes deliver results with lower root mean square (RMS) error and consume much less energy and bandwidth. RideSharing can consume as much as 50% less resources than hash-based schemes, such as SKETCHES and synopsis diffusion, while achieving lower RMS for reasonable link error rates