New features are often added incrementally to avionics systems to minimize the need for redesign and recertification. However, it then becomes necessary to check that the timing constraints of existing as well as new applications are met. We facilitate these checks by introducing a new data switch that bounds the latency of end-to-end communications across a network. This switch runs a clock-driven switching algorithm that is throughput-optimal with a bounded worst-case delay for all feasible traffic. We propose associated heuristics that determine whether the timing constraints of an integrated modular avionics (IMA) system network that uses this switch are met, even if new features have caused traffic to increase, and then search for alternative network configurations if necessary. Virtual integration is used to make a combined analysis of the worst-case delay in the network and the local buses of individual computing modules. This analysis considers the shared network topology, local hardware architectures, and specified IMA configurations. Our approach can be used by a system architect as an effective method for quickly determining which possible system architectures should be pursued to meet timing constraints, and it allows the cascading effects of changes to be tracked and managed. We demonstrate how these heuristics work through an example in which changes are made to an environmental monitoring facility within an avionics system that uses our switch.

We propose a model-based description and analysis framework for the design of wireless system architectures. Its aim is to address the shortcomings of existing approaches to system verification and the tracking of anomalies in safety-critical wireless systems. We use Architecture Analysis and Description Language (AADL) to describe an analysis-oriented architecture model with highly modular components. We also develop the cooperative tool chains required to analyze the performance of a wireless system by simulation. We show how this framework can support a detailed and largely automated analysis of a complicated, networked wireless system using examples from wireless healthcare and video broadcasting.

With the advance of hardware technology, more features are incrementally added to already existing networked systems. Avionics has a stronger tendency to use preexisting applications due to its complexity and scale. As resource sharing becomes intense among the network and the computing modules, it has become a difficult task for the system designer to make confident architectural decisions even for incremental changes. Providing a tailored environment to model and analyze incremental changes requires a combination of software tools and hardware support. We have built a virtual integration tool called ASIIST which can provide a worst-case end-to-end latency of data that is sent through a network and the internal bus architecture of the end-systems. Also, we have devised a new real-time switching algorithm which guarantees the worst-case network delay of preexisting network traffic under feasible conditions. With the real-time switch support, ASIIST can provide an early modularized analysis of the end-to-end latency to make architectural design choices and incremental changes easier for the user.

Open Analytic Runtime (OAR) Models embed analysis algorithms into runtime architectural models, thus integrating the model and its analytic interpretations. Such an integration is critical for Cyber-Physical Systems (CPS) when model parts are independently developed by different teams as it is the case in multi-tier industries, e.g. avionics and automotive. Analysis algorithms play a central role augmenting the designer's capacity to automatically verify properties of interest in systems at the scale and complexity required by these industries. Unfortunately, the verification results are valid only if the assumptions of the different analysis algorithms (analytic assumptions) are consistent with each other. This paper presents our work on the automatic verification of one important class of analytic assumptions in OAR models: resource allocation assumptions. These assumptions are modeled as Resource Allocation (RA) contracts. RA contract constructs include not only the typical assumes and guarantees but also runtime facts and implications. Finally, we automatically determine the correct sequence of execution of the analysis algorithms based on the contract input/output dependencies described in our models. Together these characteristics enable the automatic assumption verification that preserves the scalability of analytic models. We illustrate our approach using an example model with analysis algorithms for security, schedulability, and energy efficiency.

New features are often added incrementally to avionics systems. This avoids redesign and recertification but still requires verifying the timing constraints of both new and existing applications. We introduce a new switch that facilitates this verification by bounding the latency of end-to-end communication across a network. Our clock-driven real-time switching algorithm is throughput-optimal with a bounded worst-case delay for all feasible traffic. Associated heuristics can verify whether the timing constraints of an avionics network are met, after new features have caused traffic to increase, and then search for alternative network configurations if necessary. We show how these heuristics cope with changes to an example environmental monitoring architecture within an avionics system that incorporates our switch. Our approach to analysis can be used to determine, quickly but rigorously, which system architecture meet timing constraints, and it allows the system architect to manage the cascading effects of component changes in a comprehensive manner.

System-on-Chip (SoC) is a promising paradigm to implement safety-critical embedded systems, but it poses significant challenges from a design and verification point of view. In particular, in a mixed-criticality system, low criticality applications must be prevented from interfering with high criticality ones. In this paper, we introduce a new design methodology for SoC that provides strong isolation guarantees to applications with different criticalities. A set of certificates describing the assumed application behavior is extracted from a functional Architectural Analysis and Design Language (AADL) specification. Our tools then automatically generate hardware wrappers that enforce at run-time the behavior described by the certificates. In particular, we employ run-time monitoring to formally check all data communication in the system, and we enforce timing reservations for both computation and communication resources. Verification is greatly simplified because certificates are much simpler than the components used to implement low-criticality applications. The effectiveness of our methodology is proven on a case study consisting of a medical pacemaker.

In hard real-time systems such as avionics, computer board level designs are typically customized to meet specific reliability and real time requirements. This paper focuses on computer-aided application-specific design of I/O architecture using PCI as an example. We have built a tool (ASIIST) that will enable engineers to explore design spaces at the I/O bus architecture level, performing analysis that incorporates bus protocols, to provide guarantees of real-time properties.

In complex hard real-time systems with tight constraints on system resources, small changes in one component of a system can cause a cascade of adverse effects on other parts of the system. We address the inherent complexity of making architectural decisions by raising the level of abstraction at which the analysis is performed. Our analysis approach gives the system architect a rigorous method for quickly determining which system architectures should be pursued, and it allows the architect to track and manage the cascading effects of subsystem/component changes in a comprehensive, quantitative manner. The end product is a virtual architecture analysis that systematically incorporates the inherent coupling among interacting system components that share limited system resources.

As the elderly population increases, elderly care using inexpensive technological means is becoming critical. This paper presents our prototype system that provides real-time indoor tracking of elderly residents and their belongings, which is essential to assisting and securing their independent living. For high-fidelity real-time tracking, we propose novel scheduling algorithms. Our scheduling algorithms are designed by harmonizing both sensing and communication signals and leveraging location awareness and mobility consciousness in order to improve tracking accuracy while reducing the energy consumption. We performed extensive experiments through both simulation and actual implementation. Our experimental result says that our scheduling algorithms can provide real-time tracking of residents within a 20 cm error bound in the typical range of human mobility.

As the elderly population increases, the elderly care using inexpensive technological means becomes critical. This paper proposes novel scheduling algorithms for real-time indoor tracking of elderly residents, which is essential to assist and secure their independent living. Our scheduling algorithms are designed by harmonizing both sensing and communication signals and leveraging location-awareness and mobility-consciousness, in order to improve the tracking accuracy while reducing the energy consumption. We performed extensive experiments through both simulation and actual implementation. Our experimental result says that our scheduling algorithms can provide real-time tracking of residents within 20 cm error bound in the typical range of human mobility

This paper proposes a novel task model in which its physical and temporal parameters are specified as time-parameterized functions and their values are finally determined at the actual dispatch time. This model is clearly differentiated from the classical task model where parameters are fixed at the job release time. The new model better suits sensing tasks in tracking applications, since the sensor parameters such as field-of-view and measurement duration can be properly adjusted at the actual sensing time. The new model, however, creates the cyclic dependency between task parameters and scheduling behavior, that is, the task parameters depend on scheduling behavior and the latter in turn depends on the former. This cyclic dependency makes the schedulability check even more difficult. We handle this difficulty by iterative convergence and probabilistic schedulability envelope, which provides an efficient online schedulability check. The experimental study shows that the new model significantly improves the effective capacity of tracking systems without losing track accuracy