Power-Performance-Predictability: Managing the Three Cornerstones of Resource Constrained Real-Time System Design

This dissertation explores several challenges that plague the hardware-software co-design of popular resource constrained real-time embedded systems. We specifically tackle existing real-world problems, and address them through our design solutions which are highly scalable, and have practical feasibility as verified through our solution implementation on real-world hardware.

We address the problem of poor battery life in mobile embedded devices caused due to side-by-side execution of multiple applications in split-screen mode. Existing industry solutions either restricts the number of applications that can run simultaneously, limit their functionality, and/or increase the hardware capacity of the battery associated with the system. We exploit the gap in research on performance and power trade-off in smartphones to propose an integrated energy management solution, that judiciously minimizes the system-wide energy consumption with negligible effect on its quality of service (QoS).

Another important real-world requirement in today's interconnected world is the need for security. In the domain of real-time computing, it is not only necessary to secure the system but also maintain its timeliness. Some example security mechanisms that may be used in a hard real-time system include, but are not limited to, security keys, protection of intellectual property (IP) of firmware and application software, one time password (OTP) for software certification on-the-fly, and authenticated computational off-loading. Existing design solutions require expensive, custom-built hardware with long time-to-market or time-to-deployment cycle. A readily available alternative is the use of trusted execution environment (TEE) on commercial off-the-shelf (COTS) embedded processors. However, utilizing TEE creates multiple challenges from a real-time perspective, which includes additional time overhead resulting in possible deadline misses. Second, trusted execution may adversely affect the deterministic execution of the system, as tasks running inside a TEE may need to communicate with other tasks that are executing on the native real-time operating system. We propose three different solutions to address the need for a new task model that can capture the complex relationship between performance and predictability for real-time tasks that require secure execution inside TEE. We also present novel task assignment and scheduling frameworks for real-time trusted execution on COTS processors to improve task set schedulability. We extensively assess the pros and cons of our proposed approaches in comparison to the state-of-the-art techniques in custom-built real-world hardware for feasibility, and simulated environments to test our solutions' scalability.