This dissertation first presents an uniprocessor real-time scheduling algorithm called the Generic Benefit Scheduling algorithm (or GBS). GBS solves a previously open real-time scheduling problem: scheduling activities subject to arbitrarily shaped, time/utility function (TUF) time constraints and mutual exclusion resource constraints. A TUF specifies the utility of completing an application activity as an application- or situation-specific function of when that activity completes. GBS considers the scheduling objective of maximizing system-wide, total accrued utility, while respecting mutual exclusion constraints. Since this problem is NP-hard, GBS heuristically computes schedules in polynomial-time. The performance of the GBS algorithm is evaluated through simulation and through an implementation on a Portable Operating System Interface (POSIX)-compliant real-time operating system. The simulation studies and implementation measurements reveal that GBS performs close to, if not better than existing algorithms for the cases that they apply. Further, the results verify the effectiveness of GBS for its unique model. We also analytically establish timeliness and non-timeliness properties of GBS including bounds on activity utilities and mutual exclusion. GBS targets real-time systems that are subject to significant non-determinism inherent in their operating environments e.g., completely unknown activity arrivals. When system uncertainties can be stochastically characterized (e.g., stochastic activity arrivals and execution times), it is possible to provide stochastic assurances on timeliness behavior. The dissertation also presents algorithmic solutions to fundamental assurance problems in TUF-driven real-time systems, including stochastically satisfying individual, activity utility lower bounds and system-wide, total utility lower bounds. The algorithmic solutions include algorithms for processor bandwidth allocation and TUF scheduling. While bandwidth allocation algorithms allocate processor bandwidth share to activities to satisfy utility lower bounds, TUF scheduling algorithms schedule activities to maximize accrued utility. The algorithmic solutions and analysis are extended with a class of lock-free and lock-based resource access protocols to satisfy mutual exclusion constraints. We show that satisfying utility lower bounds with lock-based resource access protocols does not imply doing so with the lock-free scheme, and vice versa. Finally, the dissertation presents a rule-based framework for trading off assurance requirements on utility lower bound satisfaction. / Ph. D.

In this dissertation, we consider timeliness and energy optimization in battery-powered, mobile embedded real-time systems. We focus on real-time systems that operate in environments with dynamically uncertain properties, including context-dependent activity execution times and arbitrary activity arrival patterns. We consider an application model where activities are subject to time/utility function (or TUF) time constraints, mutual exclusion constraints on concurrent sharing of non-CPU resources, timeliness requirements including assurances on individual activity timeliness behavior, and system-level energy consumption requirements including a non-exhaustable energy budget. To account for uncertainties in activity properties in dynamic systems, we stochastically describe activity execution demands, and describe activity arrival behaviors using the unimodal arbitrary arrival model, which allows unbounded arrival frequencies. We consider the scheduling optimality criteria of: (1) probabilistically satisfying lower bounds on individual activities' maximal timeliness utilities, and (2) maximizing system-level energy efficiency, while ensuring that the system's energy consumption never exhausts the energy budget and resource mutual exclusion constraints are satisfied. For this multi-criteria scheduling problem, we present a DVS (dynamic voltage scaling)-based, real-time scheduling algorithm called the Energy-Bounded Utility Accrual Algorithm (or EBUA). Since the scheduling problem is NP-hard, EBUA heuristically (and dynamically) allocates CPU cycles to activities, computes activity schedules, and scales CPU voltage and frequency with a polynomial-time cost. If activities' cumulative execution demands exceed the available CPU time or may exhaust the system's energy budget, the algorithm defers and rejects jobs in a controlled fashion, minimizing system-level energy consumption and maximizing total accrued utility. We analytically establish several properties of EBUA. We prove that the algorithm never exhausts the specified energy budget. Further, we establish EBUA's timeliness optimality during under-loads, freedom from deadlocks, and correctness in mutually exclusive resource sharing. In particular, we prove that the algorithm's timeliness behavior subsumes the optimal timeliness behavior of deadline scheduling as a special case, and identify the conditions under which lower bounds on individual activity utilities are satisfied. In addition, we upper bound the time needed for mutually exclusively accessing shared resources under EBUA. We conduct experimental studies by simulating the algorithm on the DVS-enabled AMD k6 processor model, and by implementing it on QNX Neutrino 6.2.1 RTOS. Our experimental results validate our analytical results. Further, they confirm EBUA's superiority over other energy-efficient real-time scheduling algorithms on timeliness and energy consumption behaviors. / Ph. D.