Wireless sensor networks (WSNs) are plagued by the possibility of bugs manifesting only at deployment. However, debugging deployed WSNs is challenging for several reasons---the remote location of deployed sensor nodes, the non-determinism of execution that can make it difficult to replicate a buggy run, and the limited hardware resources available on a node. In particular, existing solutions to record and replay debugging in WSNs fail to capture the complete code execution, thus negating the possibility of a faithful replay and causing a large class of bugs to go unnoticed. In short, record and replay logs a trace of predefined events while a deployed application is executing, enabling replaying of events later using debugging tools. Existing recording methods fail due to the many sources of non-determinism and the scarcity of resources on nodes.

Wireless sensor networks (WSNs) are plagued by the possibility of bugs manifesting only at deployment. However, debugging deployed WSNs is challenging for several reasons---the remote location of deployed sensor nodes, the non- determinism of execution that can make it difficult to replicate a buggy run, and the limited hardware resources available on a node. In particular, existing solutions to record and replay debugging in WSNs fail to capture the complete code execution, thus negating the possibility of a faithful replay and causing a large class of bugs to go unnoticed. In short, record and replay logs a trace of predefined events while a deployed application is executing, enabling replaying of events later using debugging tools. Existing recording methods fail due to the many sources of non-determinism and the scarcity of resources on nodes.

It is important to get an idea of the events occurring in an embedded wireless node when it is deployed in the field, away from the convenience of an interactive debugger. Such visibility can be useful for post-deployment testing, replay-based debugging, and for performance and energy profiling of various software components. Prior software-based solutions to address this problem have incurred high execution overhead and intrusiveness. The intrusiveness changes the intrinsic timing behavior of the application, thereby reducing the fidelity of the collected profile. Prior hardware-based solutions have involved the use of dedicated ASICs or other tightly coupled changes to the embedded node's processor, which significantly limits their applicability.

Ad-hoc wireless networks are being deployed in critical applications that require protection against sophisticated adversaries. However, wireless routing protocols, such as the widely-used AODV, are often designed with the assumption that nodes are benign. Cryptographic extensions such as Secure AODV (SAODV) protect against some attacks but are still vulnerable to easily-performed attacks using colluding adversaries, such as the wormhole attack. In this paper, we make two contributions to securing routing protocols. First, we present a protocol called Route Verification (RV) that can detect and isolate malicious nodes involved in routing-based attacks with very high likelihood. However, RV is expensive in terms of energy consumption due to its radio communications. To remedy the high energy cost of RV, we make our second contribution. We propose a multigrade monitoring (MGM) approach. The MGM approach employs a previously developed lightweight local monitoring technique to detect any necessary condition for an attack to succeed. However, local monitoring suffers from false positives due to collisions on the wireless channel. When a necessary condition is detected, the heavy-weight RV protocol is triggered. We show through simulation that MGM applied to AODV generally requires little extra energy compared to baseline AODV, under the common case where there is no attack present. It is also more resource-efficient and powerful than SAODV in detecting attacks. Our work, for the first time, lays out the framework of multigrade monitoring, which we believe fundamentally addresses the tension between security and resource consumption in ad-hoc wireless networks.