Hard Real-Time Constraints in Implementing the Myopic Scheduling Algorithm

This paper presents an investigation into the constraints in implementing the Myopic scheduling algorithm. The Myopic algorithm is a hard real-time (RT) task scheduling algorithm for multiprocessor systems. It selects a suitable task based on a heuristic function, H from a subset (feasibility check window, K ) of all ready tasks. On the other hand, the original heuristic scheduling algorithm chooses the task with the least H value from all N ready tasks. Performance of the Myopic algorithm significantly depends on the chosen heuristic function and the size of the feasibility check window since it considers only K tasks from N tasks (where K ≤N ). This research investigates the impact of scheduling non-periodic hard RT tasks using the Myopic algorithm and evaluates the performance for different parameters to demonstrate the merits and constraints of the algorithm. The effects of the feasibility check window size, K , choice of heuristic function, H , the worst case processing time of tasks, p T on the performance of the Myopic algorithm under various loads are investigated. Finally, the performance of the algorithm is evaluated as task completion ratio, presented and discussed through a set of experiments

Value-based scheduling in real-time systems

A real-time system must execute functionally correct computations in a timely manner. Most of the current real-time systems are static in nature. However in recent years, the growing need for building complex real-time applications coupled with advancements in information technology drives the need for dynamic real-time systems. Dynamic real-time systems need to be designed not only to deal with expected load scenarios, but also to handle overloads by allowing graceful degradation in system performance. Value-based scheduling is a means by which graceful degradation can be achieved by executing critical tasks that offer high values/benefits/rewards to the functioning of the system. This thesis identifies the following two issues in dynamic real-time scheduling: (i) maintaining high system reliability without affecting its schedulability and (ii) providing graceful degradation to the system during overload and maintaining high schedulability during underloads or near full loads. Further, we use value-based scheduling techniques to address these issues. The first contribution of this thesis is a reliability-aware value-based scheduler capable of maintaining high system reliability and schedulability. We use a performance index (PI) based value function for scheduling, which can capture the tradeoff between schedulability and reliability. The proposed scheduler selects a suitable redundancy level for each task so as to increase the performance index of the system. We show through our simulation studies that proposed scheduler maintains a high system value (PI). The second contribution of this thesis is an adaptive value-based scheduler that can change its scheduling behavior from deadline-based scheduling to value-based scheduling based on the system workload, so that it can maintain a high system value with fewer deadline misses. Further, the scheduler is extended to heterogeneous computing (HC) systems, wherein the computing capabilities of processors/machines are different, and propose two adaptive schedulers (Basic and Integrated) for HC systems. The performance of the proposed scheduling algorithms is studied through extensive simulation studies for both homogeneous and heterogeneous computing systems. We have concluded that the proposed adaptive scheduling scheme maintains a high system value with fewer deadlines misses for all range workloads. Amongst the schedulers for HC systems, we conclude that the Basic scheduler, which has a lesser run-time complexity, performs better for most of the workloads. The last contribution of this thesis is the design and implementation of the proposed adaptive value-based scheduler for homogeneous computing systems in a real-time Linux operating system, RT-Linux. We compare the performance of the implementation with EDF and Highest Value-Density First (HVDF) schedulers for various ranges of workloads and show that the proposed scheduler performs better in maintaining a high system value with fewer deadline misses

Flexible error handling for embedded real time systems

Due to advancements of semiconductor fabrication that lead to shrinking geometries and lowered supply voltages of semiconductor devices, transient fault rates will increase significantly for future semiconductor generations [Int13]. To cope with transient faults, error detection and correction is mandatory. However, additional resources are required for their implementation. This is a serious problem in embedded systems development since embedded systems possess only a limited number of resources, like processing time, memory, and energy. To cope with this problem, a software-based flexible error handling approach is proposed in this dissertation. The goal of flexible error handling is to decide if, how, and when errors have to be corrected. By applying this approach, deadline misses will be reduced by up to 97% for the considered video decoding benchmark. Furthermore, it will be shown that the approach is able to cope with very high error rates of nearly 50 errors per second