Sanjian Chen

Challenges and Research Directions in Medical Cyber–Physical Systems

Medical cyber-physical systems (MCPS) are life-critical, context-aware, networked systems of medical devices. These systems are increasingly used in hospitals to provide high-quality continuous care for patients. The need to design complex MCPS that are both safe and effective has presented numerous challenges, including achieving high assurance in system software, intoperability, context-aware intelligence, autonomy, security and privacy, and device certifiability. In this paper, we discuss these challenges in developing MCPS, some of our work in addressing them, and several open research issues.

Realizing Compositional Scheduling through Virtualization

We present a co-designed scheduling framework and platform architecture that together support compositional scheduling of real-time systems. The architecture is built on the Xen virtualization platform, and relies on compositional scheduling theory that uses periodic resource models as component interfaces. We implement resource models as periodic servers and consider enhancements to periodic server design that significantly improve response times of tasks and resource utilization in the system while preserving theoretical schedulability results. We present an extensive evaluation of our implementation using workloads from an avionics case study as well as synthetic ones.

On effective testing of health care simulation software

Health care professionals rely on software to simulate anatomical and physiological elements of the human body for purposes of training, prototyping, and decision making. Software can also be used to simulate medical processes and protocols to measure cost effectiveness and resource utilization. Whereas much of the software engineering research into simulation software focuses on validation (determining that the simulation accurately models real-world activity), to date there has been little investigation into the testing of simulation software itself, that is, the ability to effectively search for errors in the implementation. This is particularly challenging because often there is no test oracle to indicate whether the results of the simulation are correct. In this paper, we present an approach to systematically testing simulation software in the absence of test oracles, and evaluate the effectiveness of the technique.

CARTS: a tool for compositional analysis of real-time systems

As real-time embedded systems are increasingly complex, integration becomes a great challenge in their design and development. Managing complexity of the system design is therefore essential for high-assurance and cost-effective development. Component-based design has consequently been developed and gained its importance over the years as a powerful technique for complexity management. In this design paradigm, a large complex system is first decomposed into smaller and simpler components - which are developed independently - before recomposing them into a complete system using interfaces that abstract away their internal complexities.

The MIDdleware Assurance Substrate: Enabling Strong Real-Time Guarantees in Open Systems with OpenFlow

Middleware designed for use in Distributed Real-Time and Embedded (DRE) systems enable cost and development time reductions by providing simple communications abstractions and hiding operating system-level networking API details from developers. While current middleware technologies can hide many low-level details, designers must provide a static configuration for the systems underlying network in order to achieve required performance characteristics. This has not been a problem for many types of DRE systems where the configuration of the system is relatively fixed from the factory (e.g., aircraft or naval vessels). However for truly open systems (i.e., systems where end users can add or substract components at runtime)the standard static network configuration approach cannot guarantee that required performance will be met because network resource demands are not fully known a priori. Open systems with stringent performance requirements need middleware that can dynamically manage the underlying network configuration automatically in response to changing demands. Fortunately, recent trends in networking have resulted in a wide variety of networking equipment that expose a standardized low-level interface to their configuration via the OpenFlow protocol. In this paper we discuss how OpenFlow can be leveraged by DRE middleware to automatically provide performance guarantees. In order to make the discussion concrete, we describe the architecture of our prototype middleware MIDAS as well as the details of one example network resource management strategy. We demonstrate the feasibility of our approach via performance assesment of a simple DRE application using our MIDAS and commerically available OpenFlow hardware.

Extending Task-level to Job-level Fixed Priority Assignment and Schedulability Analysis Using Pseudo-deadlines

In global real-time multiprocessor scheduling, a recent analysis technique for Task-level Fixed-Priority (TFP) scheduling has been shown to outperform many of the analyses for Job-level Fixed-Priority (JFP) scheduling on average. Since JFP is a generalization of TFP scheduling, and the TFP analysis technique itself has been adapted from an earlier JFP analysis, this result is counter-intuitive and in our opinion highlights the lack of good JFP scheduling techniques. Towards generalizing the superior TFP analysis to JFP scheduling, we propose the Smallest Pseudo-Deadline First (SPDF) JFP scheduling algorithm. SPDF uses a simple task-level parameter called pseudo-deadline to prioritize jobs, and hence can behave as a TFP or JFP scheduler depending on the values of the pseudodeadlines. This natural transition from TFP to JFP scheduling has enabled us to incorporate the superior TFP analysis technique in an SPDF schedulability test. We also present a pseudo-deadline assignment algorithm for SPDF scheduling that extends the well-known Optimal Priority Assignment (OPA) algorithm for TFP scheduling. We show that our algorithm is optimal for the derived schedulability test, and also present a heuristic to overcome the computational complexity issue of the optimal algorithm. Our simulation results show that the SPDF algorithm with the new analysis significantly outperforms state-of-the-art TFP and JFP analysis.

Improving resource utilization for compositional scheduling using DPRM interfaces

The paper revisits the generation of interfaces for compositional real-time scheduling. Following an established line of research, we use periodic resource models in component interfaces to describe resource demand of the component. We identify a deficiency of existing interface generation algorithms that may require parameters of the resource model to be infeasibly small. We propose a new algorithm for interface generation that avoids this deficiency. We further demonstrate that resource utilization can be improved by using dual-periodic resource model (DPRM) interfaces that employ two periodic resource models to characterize the resource demand more precisely.

Parameter-Invariant Design of Medical Alarms

In this tutorial, we present a design methodology for medical parameter-invariant monitors. We begin by providing a motivational review of currently employed medical alarm techniques, followed by the introduction of the parameter-invariant design approach. Finally, we present a case study example to demonstrate the design of a parameter-invariant alarm for critical shunt detection in infants during surgical procedures.

GSA: a framework for rapid prototyping of smart alarm systems

We describe the Generic Smart Alarm, an architectural framework for the development of decision support modules for a variety of clinical applications. The need to quickly process patient vital signs and detect patient health events arises in many clinical scenarios, from clinical decision support to tele-health systems to home-care applications. The events detected during monitoring can be used as caregiver alarms, as triggers for further downstream processing or logging, or as discrete inputs to decision support systems or physiological closed-loop applications. We believe that all of these scenarios are similar, and share a common framework of design. In attempting to solve a particular instance of the problem, that of device alarm fatigue due to numerous false alarms, we devised a modular system based around this framework. This modular design allows us to easily customize the framework to address the specific needs of the various applications, and at the same time enables us to perform checking of consistency of the system. In this paper we discuss potential specific clinical applications of a generic smart alarm framework, present the proposed architecture of such a framework, and motivate the benefits of a generic framework for the development of new smart alarm or clinical decision support systems.

Removing Abstraction Overhead in the Composition of Hierarchical Real-Time Systems

The hierarchical real-time scheduling framework is a widely accepted model to facilitate the design and analysis of the increasingly complex real-time systems. Interface abstraction and composition are the key issues in the hierarchical scheduling framework analysis. Schedulability is essential to guarantee that the timing requirements of all components are satisfied. In order for the design to be resource efficient, the composition must be bandwidth optimal. Associativity is desirable for open systems in which components may be added or deleted at run time. Previous techniques on compositional scheduling are either not resource efficient in some aspects, or cannot achieve optimality and associativity at the same time. In this paper, several important properties regarding the periodic resource model are identified. Based on those properties, we propose a novel interface abstraction and composition framework which achieves schedulability, optimality, and associativity. Our approach eliminates abstraction overhead in the composition.