Lightweight tracing for wireless sensor networks diagnostics

Wireless sensor networks (WSNs) are being increasingly deployed in various scientific as well as industrial domains to understand the micro-behavior of physical phenomena. WSNs are highly susceptible to post-deployment failures due to their in-situ deployments in harsh environments e.g., volcanoes. The traditional tools and techniques to handle such failures are inadequate because of inherent resource constraints of WSNs. The lack of diagnosis tools for post-deployment failures hinders the more widespread adoption of WSNs. An execution trace containing events in their order of execution can play a crucial role in postmortem diagnosis of these failures. Obtaining such a trace, however, is challenging due to stringent resource constraints. In this dissertation, we propose an efficient distributed control-flow tracing technique for WSNs based on two key observations. First, WSN executions are highly repetitive, and second, WSNs exhibit restricted communication patterns. Our distributed control-flow tracing combines three novel lightweight techniques: (1) an efficient interprocedural control-flow encoding technique that generates a succinct control-flow trace of all events happening within a node, (2) a generic hybrid trace compression technique that significantly compresses traces, and (3) a space efficient message tracing technique that is amenable to compression. We show our tracing technique\u27s effectiveness through failure case studies and efficiency through measurements and simulations

Efficient diagnostic tracing for wireless sensor networks

Wireless sensor networks are typically deployed in harsh environments, thus post-deployment failures are not infrequent. An execution trace containing events in their order of execution could play a crucial role in postmortem diagnosis of these failures. Obtaining such a trace however is challenging due to stringent resource constraints. We propose an efficient approach to intraprocedural and interprocedural control-flow tracing that generates traces of all interleaving concurrent events and of the control-flow paths taken inside those events. We demonstrate the effectiveness of our approach with the help of case studies and illustrate its low overhead through measurements and simulations

SeNDORComm: An Energy-Efficient Priority-Driven Communication Layer for Reliable Wireless Sensor Networks

In many reliable Wireless Sensor Network (WSN) applications, messages have different priorities depending on urgency or importance. For example, a message reporting the failure of all nodes in a region is more important than that for a single node. Moreover, traffic can be bursty in nature, such as when a correlated error is reported by multiple nodes running identical code. Current communication layers in WSNs lack efficient support for these two requirements. We present a priority-driven communication layer, called SeNDORComm, that schedules transmission of packets driven by application-specified priority, buffers and packs multiple messages in a packet, and honors latency guarantee for a message. We show that SeNDORComm improves energy efficiency, message reliability, network utilization and delays congestion collapse in a network. We extensively evaluate SeNDORComm using analysis, simulation and real experiments. We demonstrate the improvement in goodput of SeNDORComm over a default communication layer (134.78% for a network of 20 nodes), such as GenericComm in TinyOS

TARDIS: Software-Only System-Level Record and Replay in Wireless Sensor Networks

ABSTRACT Wireless sensor networks (WSNs) are plagued by the possibility of bugs manifesting only at deployment. However, debugging deployed WSNs is challenging for several reasonsthe 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. In this paper we introduce Trace And Replay Debugging In Sensornets (Tardis), a software-only approach for deterministic record and replay of WSN nodes. Tardis is able to record all sources of non-determinism, based on the observation that such information is compressible using a combination of techniques specialized for respective sources. Despite their domain-specific nature, the techniques presented are applicable to the broader class of resource-constrained embedded systems. We empirically demonstrate the viability of our approach and its effectiveness in diagnosing a newly discovered bug in a widely used routing protocol