Dual ceiling protocol for real-time synchronization under preemption threshold scheduling

AbstractThe application of object-oriented design methods to real-time embedded systems is seriously hindered by the lack of existing real-time scheduling techniques that can be seamlessly integrated into these methods. Preemption threshold scheduling (PTS) enables a scalable real-time system design and thus has been suggested as a solution to this problem. However, direct adoption of PTS may lead to long priority inversion since object-oriented real-time systems require synchronization considerations in order to maintain consistent object states. In this paper, we propose the dual ceiling protocol (DCP) in order to solve this problem. While DCP exploits both priority ceilings and preemption threshold ceilings, this is not a straightforward integration of existing real-time synchronization protocols for PTS. We present the rationale for the locking conditions of DCP and show that it leads to the least blocking and response times by comparison with other real-time synchronization protocols. We also present its blocking properties and schedulability analyses. We implemented PTS and DCP in a real-time object-oriented CASE tool and present the associated experimental results, which show that the proposed protocol is a viable solution that is superior to other real-time synchronization protocols for PTS

Dynamic voltage scaling algorithms for soft and hard real-time system

Dynamic Voltage Scaling (DVS) has not been investigated completely for further minimizing the energy consumption of microprocessor and prolonging the operational life of real-time systems. In this dissertation, the workload prediction based DVS and the offline convex optimization based DVS for soft and hard real-time systems are investigated, respectively. The proposed algorithms of soft and hard real-time systems are implemented on a small scaled wireless sensor network (WSN) and a simulation model, respectively

Trustworthiness in Mobile Cyber Physical Systems

Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS

Optimized Slowdown in Real Time Task Systems

Slowdown factors determine the extent of slowdown a computing system can experience based on functional and performance requirements. Dynamic Voltage Scaling (DVS) of a processor based on slowdown factors can lead to considerable energy savings. We address the problem of computing slowdown factors for dynamically scheduled tasks with specified deadlines. We present an algorithm to compute a near optimal constant slowdown factor based on the bisection method. As a further generalization, for the case of tasks with varying power characteristics, we present the computation of near optimal slowdown factors as a solution to convex optimization problem using the ellipsoid method. The algorithms are practically fast and have the same time complexity as the algorithms to compute the feasibility of a task set. Our simulation results show on an average 20 % energy gains over known slowdown techniques using static slowdown factors and 40 % gains with dynamic slowdown

Optimized slowdown in real-time task systems via geometric programming

savings due to optimal slowdown of periodic tasks in real-time task systems, where tasks have varying power characteristics and task deadlines are less than the periods. The authors presented a bisection method for computing near-optimal constant slowdown factors, when all the tasks are assigned the same slowdown factor. For the case when tasks have different slowdown factors, they presented a method for computing near-optimal slowdown factors as a solution to a convex optimization problem, using the ellipsoid method. In this note, we show a method to cast the problem of finding near-optimal slowdown factors that minimize the total energy consumption as a geometric program (GP), which can be efficiently solved using modern interior-point methods. More importantly, we show that the problem of finding nearoptimal constant slowdown factors has an analytic solution. We demonstrate the GP approach by solving several numerical instances using a publicly available interior-point GP solver. Index Terms — EDF scheduling, real-time systems, low power scheduling, dynamic voltage scaling, slowdown factors, convex optimization, geometric programming. I