17289303
Spare CASH: reclaiming holes to minimize aperiodic response times in a firm real-time environment
Scheduling periodic tasks that allow some instances to be skipped produces spare capacity in the schedule. Only a fraction of this spare capacity is uniformly distributed and can easily be reclaimed for servicing aperiodic requests. The remaining fraction of the spare capacity is non-uniformly distributed, and no existing technique has been able to reclaim it. We present a method for improving the response times of aperiodic tasks by identifying the non-uniform holes in the schedule and adding these holes as extra capacity to the capacity queue of the CASH mechanism. The non-uniform holes can account for a significant portion of spare capacity, and reclaiming this capacity results in considerable improvements to aperiodic response times.
195349457
Analysis of cache-related preemption delay in fixed-priority preemptive scheduling
We propose a technique for analyzing cache-related preemption delays of tasks that cause unpredictable variation in task execution time in the context of fixed-priority preemptive scheduling. The proposed technique consists of two steps. The first step performs a per-task analysis to estimate cache-related preemption cost for each execution point in a given task from the number of useful cache blocks at the execution point. The second step computes the worst case response time of each task using a response time equation and a linear programming technique which takes as its input the preemption cost information of tasks obtained in the first step. Our experimental results show that the proposed technique gives a prediction of the worst case cache-related preemption delay that is up to 60% tighter than that obtained from previous approaches.
41856010
Enhanced utilization bounds for QoS management
In many practical real-time applications, there is a given set of task frequencies (i.e., inverse of task periods) corresponding to predetermined QoS options that the applications can choose. For example, in audio applications, the typical choices of playback frequencies are for CD quality, radio quality, and phone quality. Similar configurations can be found in streaming video and in control applications. In such systems, applications dynamically arrive requesting one of the periods provided by the QoS manager. Thus, the accurate and efficient online schedulability test is essential for any task set whose periods are chosen from the QoS period set. For this purpose, we propose new utilization bounds as a function of given QoS periods. As long as there is a set of given periods that can be chosen by applications, the bounds developed can be used by the QoS manager to quickly determine the schedulability of dynamic applications.
20686264
Finite-Horizon Scheduling of Radar Dwells with Online Template Construction
Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism that is inherent in schedulers that assume a task executes forever. We also develop the notion of modular schedule update which allows portions of a schedule to be altered without affecting the entire schedule, thereby simplifying the scheduler. Through extensive simulations, we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline.
16111193
Bounding Cache-Related Preemption Delay for Real-Time Systems
Cache memory is used in almost all computer systems today to bridge the ever increasing speed gap between the processor and main memory. However, its use in multitasking computer systems introduces additional preemption delay due to the reloading of memory blocks that are replaced during preemption. This cache-related preemption delay poses a serious problem in realtime computing systems where predictability is of utmost importance. We propose an enhanced technique for analyzing and thus bounding the cache-related preemption delay in fixed-priority preemptive scheduling focusing on instruction caching. The proposed technique improves upon previous techniques in two important ways. First, the technique takes into account the relationship between a preempted task and the set of tasks that execute during the preemption when calculating the cache-related preemption delay. Second, the technique considers the phasing of tasks to eliminate many infeasible task interactions. These two features are expressed as constraints of a linear programming problem whose solution gives a guaranteed upper bound on the cache-related preemption delay. This paper also compares the proposed technique with previous techniques using randomly generated task sets. The results show that the improvement on the worst-case response time prediction by the proposed technique over previous techniques ranges between 5 percent and 18 percent depending on the cache refill time when the task set utilization is 0.6. The results also show that as the cache refill time increases, the improvement increases, which indicates that accurate prediction of cache-related preemption delay by the proposed technique becomes increasingly important if the current trend of widening speed gap between the processor and main memory continues.
44806973
Cache-Conscious Limited Preemptive Scheduling
In multi-tasking real-time systems, inter-task cache interference due to preemptions degrades schedulability as well as performance. To address this problem, we propose a novel scheduling scheme, called limited preemptive scheduling (LPS), that limits preemptions to execution points with small cache-related preemption costs. Limiting preemptions decreases the cache-related preemption costs of tasks but increases blocking delay of higher priority tasks. The proposed scheme makes an optimal trade-off between these two factors to maximize the schedulability of a given task set while minimizing cache-related preemption delay of tasks. Experimental results show that the LPS scheme improves the maximum schedulable utilization by up to 40\% compared with the traditional fully preemptive scheduling (FPS) scheme. The results also show that up to 20\% of processor time is saved by the LPS scheme due to reduction in the cache-related preemption costs. Finally, the results show that both the improvement of schedulability and the saving of processor time by the LPS scheme increase as the speed gap between the processor and main memory widens.
17677434
A framework for designing intelligent task-oriented augmented reality user interfaces
A task-oriented space can benefit from an augmented reality interface that layers the existing tools and surfaces with useful information to make cooking more easy, safe and efficient. To serve experienced users as well as novices, augmented reality interfaces need to adapt modalities to the user's expertise and allow for multiple ways to perform tasks. We present a framework for designing an intelligent user interface that informs and choreographs multiple tasks in a single space according to a model of tasks and users. A residential kitchen has been outfitted with systems to gather data from tools and surfaces and project multi-modal interfaces back onto the tools and surfaces themselves. Based on user evaluations of this augmented reality kitchen, we propose a system to tailor information modalities based on the spatial and temporal qualities of the task, and the expertise, location and progress of the user. The intelligent augmented reality user interface choreographs multiple tasks in the same space at the same time.
1695864
Supporting Multi-Dimensional Range Query for Sensor Networks
This paper presents the design of Pool, an efficient and scalable data storage scheme for supporting multidimensional queries. The foundation of the work that makes the Pool approach superior in executing multi-dimensional queries is that it provides a novel and elegant higher dimension to two-dimensional data mapping mechanism. Our performance study proves the efficiency of the design.
9639915
Support for adaptivity in ARMCI using migratable objects
Many new paradigms of parallel programming have emerged that compete with and complement the standard and well-established MPI model. Most notable, and successful, among these are models that support some form of global address space. At the same time, approaches based on migratable objects (also called virtualized processes) have shown that resource management concerns can be separated effectively from the overall parallel programming effort. For example, Charm++ supports dynamic load balancing via an intelligent adaptive run-time system. It is also becoming clear that a multi-paradigm approach that allows modules written in one or more paradigms to coexist and co-operate will be necessary to tame the parallel programming challenge. ARMCI is a remote memory copy library that serves as a foundation of many global address space languages and libraries. This paper presents our preliminary work on integrating and supporting ARMCI with the adaptive run-time system of Charm++ as a part of our overall effort in the multi-paradigm approach
33610569
Compression-based broadcast strategies in wireless information systems
Data delivery is through broadcast in wireless information systems due to the asymmetric communication property. However, broadcasting data easily wastes large access time because the large amount of data pages needs to be broadcast. In this paper we propose three compression-based strategies considering access order to reduce access time. Then, the expected access time of three proposed strategies is also derived by using the probability model. Our analytic and experimental results show that the compression-based broadcast strategies can dramatically reduce the access time for mobile users (MU).
33340433
An evolutionary approach to the job-shop scheduling problem
This paper focuses on the heuristic hybridization and the genetic search as a methodology to develop a computationally efficient heuristic for the job-shop scheduling problem (JSP). In order to adapt the JSP to a genetic algorithm (GA), the ASGPL (Active-Schedule Generation with a Priority-List) algorithm with a hopping scheme was proposed, and using a GA, an iterative schedule improvement procedure called EVIS (Evolutionary Intracell Scheduler) was designed. The genetic search in EVIS was parallelized with a model of subpopulations and migration. Without implementing any problem-tailored heuristic for the job-shop scheduling problem, EVIS was able to find optimal solutions to a number of different problem instances in reasonable computation time.<<ETX>>