Saurabh Ganeriwal

TL;DR: It is argued that TPSN roughly gives a 2x better performance as compared to Reference Broadcast Synchronization (RBS) and verify this by implementing RBS on motes and use simulations to verify its accuracy over large-scale networks.

TL;DR: A Bayesian formulation, specifically a beta reputation system, is employed for the algorithm steps of reputation representation, updates, integration and trust evolution in sensor networks to allow the sensor nodes to develop a community of trust.

TL;DR: This work argues that the conventional view of security based on cryptography alone is not sufficient for the unique characteristics and novel misbehaviors encountered in sensor networks, and proposes a reputation-based framework for sensor networks where nodes maintain reputation for other nodes and use it to evaluate their trustworthiness.

TL;DR: This work proposes a new technique, called sparse topology and energy management (STEM), which efficiently wakes up nodes from a deep sleep state without the need for an ultra low-power radio, and shows that this scheme results in energy savings of over two orders of magnitude compared to sensor networks without topology management.

TL;DR: Recent advances in energy-aware platforms for information processing and communication protocols for sensor collaboration are described and emerging, hitherto largely unexplored techniques, such as the use of environmental energy harvesting and the optimization of the energy consumed during sensing are looked at.