Biblio
The wireless spectrum is a scarce resource, and the number of wireless terminals is constantly growing. One way to mitigate this strong constraint for wireless traffic is the use of dynamic mechanisms to utilize the spectrum, such as cognitive and software-defined radios. This is especially important for the upcoming wireless sensor and actuator networks in aircraft, where real-time guarantees play an important role in the network. Future wireless networks in aircraft need to be scalable, cater to the specific requirements of avionics (e.g., standardization and certification), and provide interoperability with existing technologies. In this paper, we demonstrate that dynamic network reconfigurability is a solution to the aforementioned challenges. We supplement this claim by surveying several flexible approaches in the context of wireless sensor and actuator networks in aircraft. More specifically, we examine the concept of dynamic resource management, accomplished through more flexible transceiver hardware and by employing dedicated spectrum agents. Subsequently, we evaluate the advantages of cross-layer network architectures which overcome the fixed layering of current network stacks in an effort to provide quality of service for event-based and time-triggered traffic. Lastly, the challenges related to implementation of the aforementioned mechanisms in wireless sensor and actuator networks in aircraft are elaborated, and key requirements to future research are summarized.
Modeling and evaluating the performance of large-scale wireless sensor networks (WSNs) is a challenging problem. The traditional method for representing the global state of a system as a cross product of the states of individual nodes in the system results in a state space whose size is exponential in the number of nodes. We propose an alternative way of representing the global state of a system: namely, as a probability mass function (pmf) which represents the fraction of nodes in different states. A pmf corresponds to a point in a Euclidean space of possible pmf values, and the evolution of the state of a system is represented by trajectories in this Euclidean space. We propose a novel performance evaluation method that examines all pmf trajectories in a dense Euclidean space by exploring only finite relevant portions of the space. We call our method Euclidean model checking. Euclidean model checking is useful both in the design phase—where it can help determine system parameters based on a specification—and in the evaluation phase—where it can help verify performance properties of a system. We illustrate the utility of Euclidean model checking by using it to design a time difference of arrival (TDoA) distance measurement protocol and to evaluate the protocol’s implementation on a 90-node WSN. To facilitate such performance evaluations, we provide a Markov model estimation method based on applying a standard statistical estimation technique to samples resulting from the execution of a system.