Showing papers on "Deadline-monotonic scheduling published in 2010"
TL;DR: An Improved Genetic Algorithm to solve the Distributed and Flexible Job-shop Scheduling problem is proposed and has been compared with other algorithms for distributed scheduling and evaluated with satisfactory results on a large set of distributed-and-flexible scheduling problems derived from classical job-shop scheduling benchmarks.
252 citations
TL;DR: This work addresses the static resource-constrained multi-project scheduling problem (RCMPSP) with two lateness objectives, project lateness and portfolio lateness, and found several situations in which widely advocated priority rules perform poorly.
216 citations
06 Jul 2010
TL;DR: This paper develops a unifying theory with the DP- FAIR scheduling policy and examines how it overcomes problems faced by greedy scheduling algorithms, and presents a simple DP-FAIR scheduling algorithm, DP-WRAP, which serves as a least common ancestor to many recent algorithms.
Abstract: We consider the problem of optimal real-time scheduling of periodic and sporadic tasks for identical multiprocessors. A number of recent papers have used the notions of fluid scheduling and deadline partitioning to guarantee optimality and improve performance. In this paper, we develop a unifying theory with the DP-FAIR scheduling policy and examine how it overcomes problems faced by greedy scheduling algorithms. We then present a simple DP-FAIR scheduling algorithm, DP-WRAP, which serves as a least common ancestor to many recent algorithms. We also show how to extend DP-FAIR to the scheduling of sporadic tasks with arbitrary deadlines.
172 citations
TL;DR: This paper addresses a scheduling problem where patients with different priorities are scheduled for elective surgery in a surgical facility, which has a limited capacity, and formulated a stochastic dynamic programming model to address this problem.
126 citations
TL;DR: A list scheduling algorithm, called Heterogeneous Earliest Finish with Duplicator (HEFD), which considers the performance difference in target HCS using variance and significantly surpasses other three well-known algorithms.
118 citations
TL;DR: The objective is to find jointly the optimal time to perform maintenance, the optimal location and size of the due- window, and the optimal job sequence to minimize the total earliness, tardiness, and due-window related costs.
90 citations
TL;DR: This paper considers some scheduling problems with deteriorating jobs and learning effects, and several polynomial time algorithms are proposed to optimally solve the single-machine scheduling problems.
89 citations
TL;DR: The results show that the research on integrated process planning and scheduling (IPPS) is necessary and the proposed approach is a promising and very effective method on the research of IPPS.
88 citations
TL;DR: This paper designs a reliability-driven scheduling architecture that can effectively measure system reliability, based on an optimal reliability communication path search algorithm, and introduces reliability priority rank (RRank) to estimate the task's priority by considering reliability overheads.
82 citations
01 Jan 2010
TL;DR: StarPU as discussed by the authors is a runtime system capable of scheduling tasks over multicore machines equipped with GPU accelerators, which uses a software virtual shared memory (VSM) that provides a highlevel programming interface and automates data transfers between processing units so as to enable a dynamic scheduling of tasks.
Abstract: To fully tap into the potential of heterogeneous machines composed of multicore processors and multiple accelerators, simple offloading approaches in which the main trunk of the application runs on regular cores while only specific parts are offloaded on accelerators are not sufficient. The real challenge is to build systems where the application would permanently spread across the entire machine, that is, where parallel tasks would be dynamically scheduled over the full set of available processing units. To face this challenge, we previously proposed StarPU, a runtime system capable of scheduling tasks over multicore machines equipped with GPU accelerators. StarPU uses a software virtual shared memory (VSM) that provides a highlevel programming interface and automates data transfers between processing units so as to enable a dynamic scheduling of tasks. We now present how we have extended StarPU to minimize the cost of transfers between processing units in order to efficiently cope with multi-GPU hardware configurations. To this end, our runtime system implements data prefetching based on asynchronous data transfers, and uses data transfer cost prediction to influence the decisions taken by the task scheduler. We demonstrate the relevance of our approach by benchmarking two parallel numerical algorithms using our runtime system. We obtain significant speedups and high efficiency over multicore machines equipped with multiple accelerators. We also evaluate the behaviour of these applications over clusters featuring multiple GPUs per node, showing how our runtime system can combine with MPI.
73 citations
12 Apr 2010
TL;DR: This article studies the scheduling of critical embedded systems, which consist of a set of communicating periodic tasks with constrained deadlines, and proposes fixed priority scheduling policies that do not require synchronization mechanisms (like semaphores).
Abstract: This article studies the scheduling of critical embedded systems, which consist of a set of communicating periodic tasks with constrained deadlines. Currently, tasks are usually sequenced manually, partly because available scheduling policies do not ensure the determinism of task communications. Ensuring this determinism requires scheduling policies supporting task precedence constraints (which we call dependent tasks), which are used to force the order in which communicating tasks execute. We propose fixed priority scheduling policies for different classes of dependent tasks: with simultaneous or arbitrary release times, with simple precedences (between tasks of the same period) or extended precedences (between tasks of different periods). We only consider policies that do not require synchronization mechanisms (like semaphores). This completely prevents deadlocks or scheduling anomalies without requiring further proofs.
TL;DR: This work proposes a novel two-phase approach for learning, where it first learns which part of the data correspond to best scheduling practices and then uses this data and decision tree induction to learn new and previously unknown dispatching rules.
TL;DR: This work identifies the priority structures for which the constrained efficient rule (CER) is singleton-valued and group strategy-proof, and describes the priorities under which such structures do not suffer welfare loss.
01 Mar 2010
TL;DR: A new heuristic scheduling strategy for Independent tasks based on two traditional scheduling heuristics Min-Min and Max-Min that outperforms in many cases than the existing ones.
Abstract: With the emergence of Grid technologies, the problem of scheduling tasks in heterogeneous systems has been arousing attention. Task scheduling is a NP-complete problem[5] and it is more complicated under the Grid environment. To better use tremendous capabilities of Grid system, effective and efficient scheduling algorithms are needed. In this paper, we are presenting a new heuristic scheduling strategy for Independent tasks. The strategy is based on two traditional scheduling heuristics Min-Min and Max-Min. The strategy also considers the overall performance of machines to decide the scheduling sequence of tasks. We have evaluated our scheduling strategy within a grid simulator known as GridSim. We compared the results given by our strategy with the existing scheduling heuristics Min-Min and Max-Min and the results shows that our strategy outperforms in many cases than the existing ones.
TL;DR: Gene expression programming-based scheduling rules constructor (GEPSRC) was proposed to construct effective scheduling rules (SRs) for DSMSPs with job release dates automatically, and results showed that GEPSRC achieved significant improvement.
Abstract: The paper considers the problems of scheduling n jobs that are released over time on a machine in order to optimize one or more objectives. The problems are dynamic single-machine scheduling problems (DSMSPs) with job release dates and needed to be solved urgently because they exist widely in practical production environment. Gene expression programming-based scheduling rules constructor (GEPSRC) was proposed to construct effective scheduling rules (SRs) for DSMSPs with job release dates automatically. In GEPSRC, Gene Expression Programming (GEP) worked as a heuristic search to search the space of SRs. Many experiments were conducted, and comparisons were made between GEPSRC and some previous methods. The results showed that GEPSRC achieved significant improvement.
TL;DR: A novel optimal gamma based scheduling algorithm for fixed head hydrothermal problems using genetic algorithm is presented, which includes the simulation results of four test cases with a view to highlight its superior performance and suitability for easy implementation, irrespective of the problem size.
Abstract: The short-term hydrothermal scheduling is a daily planning proposition in power system operation, a task which is usually more complex than the scheduling of all-thermal generation system. The traditional methods have become inadequate to handle large scheduling problems and tend to be ineffective in terms of their computational speed, robustness and accuracy. Alternative strategies have thus become an imminent necessity and intelligent techniques appear to suit the complex scheduling problems. This paper presents a novel optimal gamma based scheduling algorithm for fixed head hydrothermal problems using genetic algorithm. It includes the simulation results of four test cases with a view to highlight its superior performance and suitability for easy implementation, irrespective of the problem size.
TL;DR: Three methods to handle overruns due to resource sharing between subsystems in the HSF are considered and corresponding scheduling algorithms and associated schedulability analysis are presented together with analysis that shows under what circumstances one or the other is preferred.
Abstract: The hierarchical scheduling framework (HSF) has been introduced as a design-time framework to enable compositional schedulability analysis of embedded software systems with real-time properties. In this paper, a software system consists of a number of semi-independent components called subsystems. Subsystems are developed independently and later integrated to form a system. To support this design process, in the paper, the proposed methods allow non-intrusive configuration and tuning of subsystem timing-behavior via subsystem interfaces for selecting scheduling parameters. This paper considers three methods to handle overruns due to resource sharing between subsystems in the HSF. For each one of these three overrun methods corresponding scheduling algorithms and associated schedulability analysis are presented together with analysis that shows under what circumstances one or the other is preferred. The analysis is generalized to allow for both fixed priority scheduling (FPS) and earliest deadline first (EDF) scheduling. Also, a further contribution of the paper is the technique of calculating resource-holding times within the framework under different scheduling algorithms; the resource holding times being an important parameter in the global schedulability analysis.
24 Oct 2010
TL;DR: A sufficient schedulability condition is derived for efficiently determining whether a given mixed-criticality system can be successfully scheduled by this algorithm and it is shown that this algorithm is strictly superior to prior algorithms that have been used for scheduling mixed- criticality systems needing certification.
Abstract: Many safety-critical embedded systems are subject to certification requirements. However, only a subset of the functionality of the system may be safety-critical and hence subject to certification; the rest of the functionality is non safety-critical and does not need to be certified. Certification requirements in such mixed-criticality systems give rise to some interesting scheduling problems, that cannot be satisfactorily addressed using techniques from conventional scheduling theory. In prior work, we have proposed a priority-based algorithm for scheduling such mixed-criticality systems on preemptive uniprocessor platforms. In this paper, we derive a sufficient schedulability condition for efficiently determining whether a given mixed-criticality system can be successfully scheduled by this algorithm. We show that this algorithm (and the associated schedulability test) is strictly superior to prior algorithms that have been used for scheduling mixed-criticality systems needing certification.
TL;DR: A new “per-priority” basis analysis scheme is proposed which computes the total time window at each priority level instead of each traffic-flow, so that a broad class of real-time communications with different QoS requirements can be explored and developed in a SoC/NoC communication platform.
Abstract: Priority-based wormhole switching with a priority share policy has been proposed as a possible solution for real-time on-chip communication. However, the blocking introduced by priority share complicates the analysis process. In this paper, we propose a new "per-priority" basis analysis scheme which computes the total time window at each priority level instead of each traffic-flow. By checking the release instance of each flow at the corresponding priority window, we can determine schedulability efficiently. Building on this static analysis, for a given set of tasks and network topology, we further propose a task mapping and priority assignment algorithm, in such a way that the hard time bounds are met with a reduced hardware overhead. Experiment results show that significant resource saving can be achieved with no performance degradation in terms of missed deadlines. By using this approach, a broad class of real-time communications with different QoS requirements can be explored and developed in a SoC/NoC communication platform.
13 Jun 2010
TL;DR: A (2+ε)-speed O(1)-competitive algorithm for scheduling jobs with arbitrary speed-up curves for the l2 norm of flow is given.
Abstract: We give a (2+e)-speed O(1)-competitive algorithm for scheduling jobs with arbitrary speed-up curves for the l2 norm of flow. We give a similar result for the broadcast setting with varying page sizes.
TL;DR: In this paper, the A* search algorithm has been used for task scheduling in a parallel system and the results show that the proposed A* scheduling algorithm significantly outperforms the previous approach, due to a much improved consistent and admissible cost function f(s).
Abstract: Scheduling tasks onto the processors of a parallel system is a crucial part of program parallelisation. Due to the NP-hard nature of the task scheduling problem, scheduling algorithms are based on heuristics that try to produce good rather than optimal schedules. Nevertheless, in certain situations it is desirable to have optimal schedules, for example for time-critical systems or to evaluate scheduling heuristics. This paper investigates the task scheduling problem using the A* search algorithm which is a best-first state space search. The adaptation of the A* search algorithm for the task scheduling problem is referred to as the A* scheduling algorithm. The A* scheduling algorithm can produce optimal schedules in reasonable time for small to medium sized task graphs with several tens of nodes. In comparison to a previous approach, the here presented A* scheduling algorithm has a significantly reduced search space due to a much improved consistent and admissible cost function f(s) and additional pruning techniques. Experimental results show that the cost function and the various pruning techniques are very effective for the workload. Last but not least, the results show that the proposed A* scheduling algorithm significantly outperforms the previous approach.
TL;DR: The simulation results reveal the significant role of the implemented migration scheme as a load balancing factor in a heterogeneous environment and the reduction of the fragmentation caused in the schedule by gang scheduled jobs and the alleviation of the performance impact of the high priority jobs.
Patent•
03 May 2010
TL;DR: In this article, the authors proposed a system and method for enhancing scheduling/priority handling and multiplexing on transmitting data of different logical channels including a receiver and a processor, where the receiver receives a payload unit.
Abstract: System and method for enhancing scheduling/priority handling and multiplexing on transmitting data of different logical channels includes a receiver and a processor. The receiver receives a payload unit. The processor processes payload unit and enhances scheduling/priority handling and multiplex from different logical channels. The processor calculates data that can be transmitted with available resource for each logical channel, prioritizes the logical channels with decreasing priority order, performs first round resource allocation without partition, prioritizes logical channels with remaining data that is not performed with first round resource allocation with strict decreasing priority order, and performs second round resource allocation with partition. As such, scheduling/priority handling and the multiplexing in a multiple carrier system will be carried out so as to increase the efficiency of resource allocation.
Proceedings Article•
27 Sep 2010TL;DR: In this paper, a reduction from a concurrent real-time program with priority preemptive scheduling to a sequential program that has the same set of behaviors is presented, and the reduction enables the application of any sequential program analysis to be applied to concurrent realtime programs.
Abstract: We present a reduction from a concurrent real-time program with priority preemptive scheduling to a sequential program that has the same set of behaviors. Whereas many static analyses of concurrent programs are undecidable, our reduction enables the application of any sequential program analysis to be applied to a concurrent real-time program with priority preemptive scheduling.
01 Mar 2010
TL;DR: Books and internet are the recommended media to help you improving your quality and performance.
Abstract: Stochastic scheduling is in the area of production scheduling. There is a dearth of work that analyzes the variability of schedules. In a stochastic environment, in which the processing time of a job is not known with certainty, a schedule is typically analyzed based on the expected value of a performance measure. This book addresses this problem and presents algorithms to determine the variability of a schedule under various machine configurations and objective functions. It is intended for graduate and advanced undergraduate students in manufacturing, operations management, applied mathematics, and computer science, and it is also a good reference book for practitioners. Computer software containing the algorithms is provided on an accompanying website for ease of student and user implementation.
TL;DR: An optimal dynamic multi-air threat evaluation and weapon allocation algorithm using a variant of Stable Marriage Algorithm (SMA) and a new dynamic weapon scheduling algorithm, allowing multiple engagements using shoot-look-shoot strategy, to compute near-optimal solution.
Abstract: Real time scheduling problems demand high level of flexibility and robustness under complex dynamic scenarios. Threat Evaluation (TE) and Weapon Assignment (WA), together TEWA is one such complex dynamic system that has optimal or near optimal utilization of scarce defensive resources, a supreme priority. Several static solutions of TEWA have been proposed. This paper discusses an optimal dynamic multi-air threat evaluation and weapon allocation algorithm using a variant of Stable Marriage Algorithm (SMA). WA uses a new dynamic weapon scheduling algorithm, allowing multiple engagements using shoot-look-shoot strategy, to compute near-optimal solution. For optimality different types of constraints are identified and defined. Testing part of this paper shows feasibility of this approach for a range of scenarios.
26 Mar 2010
TL;DR: Results given in this paper demonstrate that the average waiting time and the average turnaround time in the proposed algorithm are better than that obtained using priority scheduling, and closed to that obtained from shortest-job-first (SJF) scheduling.
Abstract: Scheduling in computer science means determining which tasks run when there are multiple runnable tasks Several CPU scheduling algorithms have different features, and no single one is ideal absolutely for every application This paper presents an attempt to apply fuzzy logic in the design and implementation of a rule-based scheduling algorithm to solve the shortcoming of well-known scheduling algorithms Results given in this paper demonstrate that the average waiting time and the average turnaround time in the proposed algorithm are better than that obtained using priority scheduling, and closed to that obtained from shortest-job-first (SJF) scheduling The new proposed algorithm is a dynamic scheduling algorithm which deals with both task priority and its execution time, while the SJF algorithm doesn’t
14 Mar 2010
TL;DR: This paper first formulate the optimal scheduling problems with and without minimum per-flow throughput constraints, and proposes two simple yet effective searching algorithms which can achieve high network throughput and maintain long-term fairness among competing flows with low computational complexity.
Abstract: Optimal scheduling for concurrent transmissions in rate-nonadaptive wireless networks is NP-hard. Optimal scheduling in rate-adaptive wireless networks is even more difficult, because, due to mutual interference, each flow's throughput in a time slot is unknown before the scheduling decision of that slot is finalized. The capacity bound derived for rate-nonadaptive networks is no longer applicable either. In this paper, we first formulate the optimal scheduling problems with and without minimum per-flow throughput constraints. Given the hardness of the problems and the fact that the scheduling decisions should be made within a few milliseconds, we propose two simple yet effective searching algorithms which can quickly move towards better scheduling decisions. Thus, the proposed scheduling algorithms can achieve high network throughput and maintain long-term fairness among competing flows with low computational complexity. For the constrained optimization problem involved, we consider its dual problem and apply Lagrangian relaxation. We then incorporate a dual update procedure in the proposed searching algorithm to ensure that the searching results satisfy the constraints. Extensive simulations are conducted to demonstrate the effectiveness and efficiency of the proposed scheduling algorithms which are found to achieve throughputs close to the exhaustive searching results with much lower computational complexity.
18 Dec 2010
TL;DR: Simulations have shown that the performance of P-TSA is better than other scheduling algorithms such as Min-min and Max-min, and this paper compares it with existed grid scheduling algorithms on scheduling length and resource utilization rates.
Abstract: Grid is proposed to solve large scale and complicated problems, and it is a form of parallel computing on Internet Task scheduling in grid is one of the most important technologies in grid system, and it is a NP complete problem, which is used to schedule a task on an appropriate grid node Task scheduling algorithms are used to improve the grid performance by minimizing the scheduling length A priority-based task scheduling algorithm (P-TSA) in grid is proposed in this paper In this kind of priority-based algorithm, tasks are scheduled according to the priority order firstly And then assign processors Comparing P-TSA with existed grid scheduling algorithms on scheduling length and resource utilization rates Simulations are done on examples of DAG, and simulation results shown that the performance of P-TSA is better than other scheduling algorithms such as Min-min and Max-min
TL;DR: The authors conclude that CEAS is applicable for OFDMA real-time scheduling due to low computational complexity and high performance.
Abstract: The authors consider network utility maximisation problem in orthogonal frequency division multiple access (OFDMA) networks to study cross-layer, fair and efficient resource allocation. Assuming knowledge of the instantaneous channel gains, this problem is decomposed into rate control and scheduling problems at the transport and medium access control/physical layers, respectively. In contrast to the rate control problem that is solved using subgradient method, the scheduling problem has high computational complexity owing to optimising integer and continuous variables simultaneously. Based on the results from analysing the integer relaxed scheduling problem, computationally efficient adaptive scheduling (CEAS) and opportunistic time division multiple access (Opp-TDMA) scheduling schemes are proposed to joint subcarrier assignment and power allocation. Simulation results demonstrate that aggregate utility achieved in the network with the cooperation between rate control and proposed scheduling schemes outperforms those of previously proposed joint channel-aware and queue-aware scheduling schemes. Also, through comparison with the optimal solution, the authors conclude that CEAS is applicable for OFDMA real-time scheduling due to low computational complexity and high performance.