DICE: Monitoring Global Invariants of Physical Processes using Wireless Sensor Networks

Wireless sensor networks (WSNs) enable decentralized architectures to monitor the behavior of physical processes and to detect deviations from a specified “safe” behavior, e.g., to check the operation of control loops. Such correct behavior is typically expressed by global invariants over the state of different sensors or actuators. Nevertheless, to leverage the computing capabilities of WSN nodes, the application intelligence needs to reside inside the network. The task of ensuring that the monitored processes behave safely thus becomes inherently distributed, and hence more complex. In this paper we present DICE, a system enabling WSN-based distributed monitoring of global invariants. A DICE invariant is expressed by predicates defined over the state of multiple WSN nodes, e.g., the expected state of actuators based on given sensed environ- mental conditions. Our modular design allows two alternative protocols for detecting invariant violations: both perform in-network aggregation but with different degrees of decentralization, therefore supporting scenarios with different network and data dynamics. We characterize and compare the two protocols using large-scale simulations and a real-world testbed. Our results indicate that invariant violations are detected in a timely and energy-efficient manner. For instance, in a 225-node 15-hop network, invariant violations are detected in less than a second and with only a few packets sent by each node.