The dynamic and lossy nature of wireless communication poses major challenges to reliable, self-organizing multihop networks. These non-ideal characteristics are more problematic with the primitive, low-power radio transceivers found in sensor networks, and raise new issues that routing protocols must address. Link connectivity statistics should be captured dynamically through an efficient yet adaptive link estimator and routing decisions should exploit such connectivity statistics to achieve reliability. Link status and routing information must be maintained in a neighborhood table with constant space regardless of cell density. We study and evaluate link estimator, neighborhood table management, and reliable routing protocol techniques. We focus on a many-to-one, periodic data collection workload. We narrow the design space through evaluations on large-scale, high-level simulations to 50-node, in-depth empirical experiments. The most effective solution uses a simple time averaged EWMA estimator, frequency based table management, and cost-based routing.

The traditional approach of providing network security has been to borrow tools from cryptography and authentication. However, we argue that the conventional view of security based on cryptography alone is not sufficient for the unique characteristics and novel misbehaviors encountered in sensor networks. Fundamental to this is the observation that cryptography cannot prevent malicious or non-malicious insertion of data from internal adversaries or faulty nodes. We believe that in general tools from different domains such as economics, statistics and data analysis will have to be combined with cryptography for the development of trustworthy sensor networks. Following this approach, we propose a reputation-based framework for sensor networks where nodes maintain reputation for other nodes and use it to evaluate their trustworthiness. We will show that this framework provides a scalable, diverse and a generalized approach for countering all types of misbehavior resulting from malicious and faulty nodes. We are currently developing a system within this framework where we employ a Bayesian formulation, specifically a beta reputation system, for reputation representation, updates and integration. We will explain the reasoning behind our design choices, analyzing their pros & cons. We conclude the paper by verifying the efficacy of this system through some preliminary simulation results.

Real-time wireless link reliability estimation is a fundamental building block for self-organization of multihop sensor networks. Observed connectivity at low-power is more chaotic and unpredictable than in wireless LANs, and available resources are severely constrained. We seek estimators that react quickly to large changes, yet are stable, have a small memory footprint and are simple to compute. We create a simple model that generates link loss characteristics similar to empirical traces collected under different contexts. With this model, we simulate a variety of estimators, and uses the simple exponentially weighted moving average (EWMA) estimator, as a basis for comparison. We find that recently propose flip-flop estimators are not superior. However, our cascaded EWMA on windowed averaging is very efective.

Power management is an important technique to prolong the lifespan of sensor networks. Many power management protocols employ wake-up/sleep schedules, which are often complicated and inefficient. We present power management schemes that eliminate such wake-up periods unless the node indeed needs to wake up. This type of wake-up capability is enabled by a new radio-triggered hardware component inspired by the observation that the wake-up radio signal contains enough energy to trigger a wake-up process. We evaluate the potential power saving in terms of the lifespan of a sensor network application, using experiment data and SPICE circuit simulations. Comparing the result with always-on and rotation-based power management schemes, we find the radio-triggered scheme saves 98 % of the energy used in the always-on scheme, and saves over 70 % of the energy used in the rotation-based scheme. Consequently, the lifespan increases from 3.3 days (always-on) or 49.5 days (rotation-based) to 178 days (radio-triggered). Furthermore, a store-energy technique can extend operating distance from 10 feet to 22 feet, or even longer if longer latency is acceptable. Wake-up efficiency is evaluated in NS-2 simulations, which show that radio-triggered wake-up has fewer failures, shorter latency, and consistently larger sensing laxity than rotation based wake-up. We also present amplification and radio-triggered IDs which can further enhance performance. 1.

We propose a new methodology for creating embedded software that meets real-time deadlines. Our approach is a synthesis of real-time analysis and traditional systems debugging techniques, based on two main ideas. First, we use probabilistic modeling techniques to make quantitative predictions about system behavior, as opposed to real-time analysis techniques whose results are binary and often pessimistic (either the system can be shown to always work or it cannot). In particular, we focus on application-level reliability requirements where traditional real-time analyses focus on individual failures irrespective of their effect on overall system behavior. Second, we have developed a systematic method, based on hierarchical scheduling, for restructuring systems software in order to solve real-time design problems. We validate our approach by applying it to software running on networked sensor nodes.