Multi-Dimensional Scheduling for Real-Time Tasks on Heterogeneous Clusters

Multiple performance requirements need to be guaranteed in some real-time applications such as multimedia data processing and real-time signal processing in addition to timing constraints.Unfortunately,most conventional scheduling algorithms only take one or two dimensions of them into account.Motivated by this fact,this paper investigates the problem of providing multiple performance guarantees including timeliness,QoS,throughput,QoS fairness and load balancing for a set of independent tasks by dynamic ...     

Fault-Tolerant Scheduling for Real-Time Embedded Control Systems

With the increasing complexity of industrial application, an embedded control system (ECS) requires processing a number of hard real-time tasks and needs fault-tolerance to assure high reliability. Considering the characteristics of real-time tasks in ECS, an integrated algorithm is proposed to schedule real-time tasks and to guarantee that all real-time tasks are completed before their deadlines even in the presence of faults. Based on the nonpreemptive critical-section protocol (NCSP), this paper analyzes the blocking time introduced by resource conflicts of relevancy tasks in fault-tolerant multiprocessor systems. An extended schedulability condition is presented to check the assignment feasibility of a given task to a processor. A primary/backup approach and on-line replacement of failed processors are used to tolerate processor failures. The analysis reveals that the integrated algorithm bounds the blocking time, requires limited overhead on the number of processors, and still assures good processor utilization. This is also demonstrated by simulation results. Both analysis and simulation show the effectiveness of the proposed algorithm in ECS.     

任务分配与调度中的遗传算法：知识表示与遗传算法子研究

Task matching and scheduling play an important role in parallel and distributed systems.In order to use genetic algorithms(Gas) for tasks matching and scheduling,not only appropriate representations of solutions but also genetic operators’efficiency and generality are very important.In this paper,analysis between problem space and representation space is given at the first.Then based on the representation of permutation,two general efficient genetic operators are proposed,order crossover(OCX)and migration. OCX generates new schedules with heuristic due to the problem space with constraints among tasks. Migration transfers a task from one processor to another within a schedule. The simulation results of algorithms and conclusions are given at last.     

Optimal Checkpoint Placement on Real-Time Tasks with Harmonic Periods

This paper presents an optimal checkpoint strategy for fault-tolerance in real-time systems where transient faults occur in Poisson distribution. In our environment, multiple real-time tasks with different deadlines and harmonic periods are scheduled in the system by rate-monotonic algorithm, and checkpoints are inserted at a constant interval in each task. When a fault is detected, the system carries out rollback to the latest checkpoint and re-executes tasks. The maximum number of re-executable checkpoints and an equation to check schedulability are derived, and the optimal number of checkpoints is selected to maximize the probability of completing all the tasks within their deadlines.     

Three novel opportunistic scheduling algorithms in CoMP-CSB scenario

Coordinated scheduling/beamforming(CSB),which belongs to the coordinated multi-point(CoMP) transmission,has received lots of attention recently due to its great potential to mitigate inter-cell interference(ICI) and to increase the cell-edge throughput,and meanwhile it only requires limited base station cooperation and is easy to implement.However,to the best of our knowledge,there are no effective scheduling algorithms with low complexity and overhead in CoMP-CSB scenario as yet.Thus,in this paper,we propose three novel opportunistic scheduling algorithms in CoMP-CSB scenario.All of them jointly consider the intended channel condition of the scheduled user from its serving cell and the orthogonality between the intended channel and the corresponding interference channels to concurrently scheduled users in nearby cells,thus exploiting multi-user diversity(MUD) and mitigating ICI at the same time.Algorithm 1 cooperatively chooses the most orthogonal user pair within a candidate user set in which all users have a large local channel feedback,while Algorithm 2 concurrently schedules the user pair with the largest ratio between the local channel feedbacks and the aforementioned orthogonality within the same candidate user set.Algorithm 3 performs in the way similar to the proportional fairness scheduling,while making a proper modification for its usage in CoMP-CSB scenario.The performance of the proposed scheduling algorithms are evaluated through simulation.Results show that,they all can significantly enhance the received signal to interference plus noise ratio(SINR) with relatively good fairness guarantee,thus achieving larger throughputs and utilities than several well-known scheduling algorithms.Algorithm 2 even outperforms Algorithm 1 when the aforementioned candidate user set is big enough in size and has a bit more overhead/complexity.Furthermore,Algorithms 3 is the best one among all the three proposed algorithms,but it requires more overhead/complexity than Algorithm 1 and 2.Finally,we give the optimal parameter for all of the three proposed algorithms,which can make a good tradeoff between performance and overhead/complexity.     

A Constraint Satisfaction Neural Network and Heuristic Combined Approach for Concurrent Activities Scheduling

Scheduling activities in concurrent product development process is of great significance to shorten development lead time and minimize the cost. Moreover, it can eliminate the unnecessary redesign periods and guarantee that serial activities can be executed as concurrently as possible. This paper presents a constraint satisfaction neural network and heuristic combined approach for concurrent activities scheduling. In the combined approach, the neural network is used to obtain a feasible starting time of all the activities based on sequence constraints, the heuristic algorithm is used to obtain a feasible solution of the scheduling problem based on resource constraints. The feasible scheduling solution is obtained by a gradient optimization function. Simulations have shown that the proposed combined approach is efficient and feasible with respect to concurrent activities scheduling.     

Configuration Reusing in On-Line Task Scheduling for Reconfigurable Computing Systems

Reconfigurable computing systems can be reconfigured at runtime and support partial reconfigurability which makes us able to execute tasks in a true multitasking manner.To manage such systems at runtime,a reconfigurable operating system is needed.The main part of this operating system is resource management unit which performs on-line scheduling and placement of hardware tasks at runtime.Reconfiguration overhead is an important obstacle that limits the performance of on-line scheduling algorithms in reconfigurable computing systems and increases the overall execution time.Configuration reusing (task reusing) can decrease reconfiguration overhead considerably,particularly in periodic applications or the applications in which the probability of tasks recurrence is high.In this paper,we present a technique called reusing-based scheduling (RBS),for on-line scheduling and placement in which configuration reusing is considered as a main characteristic in order to reduce reconfiguration overhead and decrease total execution time of the tasks.Several experiments have been conducted on the proposed algorithm.Obtained results show considerable improvement in overall execution time of the tasks.     

Optimal feedback scheduling of model predictive controllers

Model predictive control （MPC） could not be reliably applied to real-time control systems because its computation time is not well defined. Implemented as anytime algorithm, MPC task allows computation time to be traded for control performance, thus obtaining the predictability in time. Optimal feedback scheduling （FS-CBS） of a set of MPC tasks is presented to maximize the global control performance subject to limited processor time. Each MPC task is assigned with a constant bandwidth server （CBS）, whose reserved processor time is adjusted dynamically. The constraints in the FS- CBS guarantee scheduler of the total task set and stability of each component. The FS-CBS is shown robust against the variation of execution time of MPC tasks at runtime. Simulation results illustrate its effectiveness.     

A Heuristic Algorithm for Task Scheduling Based on Mean Load on Grid

Efficient task scheduling is critical to achieving high performance on grid computing environment. The task scheduling on grid is studied as optimization problem in this paper. A heuristic task scheduling algorithm satisfying resources load balancing on grid environment is presented. The algorithm schedules tasks by employing mean load based on task predictive execution time as heuristic information to obtain an initial scheduling strategy. Then an optimal scheduling strategy is achieved by selecting two machines satisfying condition to change their loads via reassigning their tasks under the heuristic of their mean load. Methods of selecting machines and tasks are given in this paper to increase the throughput of the system and reduce the total waiting time. The efficiency of the algorithm is analyzed and the performance of the proposed algorithm is evaluated via extensive simulation experiments. Experimental results show that the heuristic algorithm performs significantly to ensure high load balancing and achieve an optimal scheduling strategy almost all the time. Furthermore, results show that our algorithm is high efficient in terms of time complexity.     

A constraint satisfaction neural network and heuristic combined approach for concurrent activities scheduling

Scheduling activities in concurrent product development process is of great sig-nificance to shorten developements lead time and minimize the cost.Moreover,it can eliminate the unnecessary redesign periods and guarantee that serial activities can be executed as concurrently as possible,This paper presents a constraint satisfaction neural network and heuristic combined approach for concurrent activities scheduling.In the combined approack,the neural network is used to obtain a feasible starting time of all the activities based on sequence constraints ,the heuristic algorithm is used to obtain a feasible solution of the scheduling problem based on resource constrainsts.The feasible scheduling solution is obtained by a gradient optimization function .Sim-ulations have shown that the proposed combined approach is efficient and fasible with respect to concurrent activities scheduling.     

基于至少连续满足弱硬实时限制的调度算法

对至少连续满足弱硬实时限制的性质进行了扩充，提出并证明了任务不满足子序列长度与任务连续满足的截止期限数之间的关系.在此基础上提出了改进的弱硬实时限制调度算法：MRA．MRA用于在弱硬实时系统中保证任务满足至少连续满足限制，是一种高效、易于实现的调度算法,仿真实验的结果表明，MRA调度算法在提高任务对限制的满足率和保证任务实时性方面优于同类算法．     

Singularity Analysis of Geometric Constraint Systems

Singularity analysis in an important subject of the geometric constraint satisfaction problem.In this paper,three kinds of singularities are described and corresponding identifcation methods are presented for both under0constrained systems and over-constrained systems,Another special but common singularity for under-constrained geometric systems,pseudo-singularity,is analyzed.Pseudo-singularity is caused by a variety of constraint mathching of under-constrained systems and can be removed by improving constraint distribution.To avoid pseudo-singularity and decide redundant constraints adaptively,a differentiaiton algorithm is proposed in the paper.Its corrctness and effciency have been validated through its practical applications in a 2D/3D geometric constraint solver CBA.     

An Algorithm Based on Tabu Search for Satisfiability Problem

In this paper,a computationally effective algorithm based on tabu search for solving the satisfiability problem(TSSAT)is proposed.Some novel and efficient heuristic strategies for generating candidate neighborhood of the curred assignment and selecting varibables to be flipped are presented. Especially,the aspiration criterion and tabu list tructure of TSSAT are different from those of traditional tabu search.Computational experiments on a class of problem insteances show that,TSSAT,in a reasonable amount of computer time ,yields better results than Novelty which is currently among the fastest known.Therefore TSSAT is feasible and effective.     

Controller Area Network (CAN) schedulability analysis: Refuted,revisited and revised

Controller Area Network (CAN) is used extensively in automotive applications, with in excess of 400 million CAN enabled microcontrollers manufactured each year. In 1994 schedulability analysis was developed for CAN, showing how worst-case response times of CAN messages could be calculated and hence guarantees provided that message response times would not exceed their deadlines. This seminal research has been cited in over 200 subsequent papers and transferred to industry in the form of commercial CAN schedulability analysis tools. These tools have been used by a large number of major automotive manufacturers in the design of in-vehicle networks for a wide range of cars, millions of which have been manufactured during the last decade. This paper shows that the original schedulability analysis given for CAN messages is flawed. It may provide guarantees for messages that will in fact miss their deadlines in the worst-case. This paper provides revised analysis resolving the problems with the original approach. Further, it highlights that the priority assignment policy, previously claimed to be optimal for CAN, is not in fact optimal and cites a method of obtaining an optimal priority ordering that is applicable to CAN. The paper discusses the possible impact on commercial CAN systems designed and developed using flawed schedulability analysis and makes recommendations for the revision of CAN schedulability analysis tools. Robert I. Davis received a DPhil in Computer Science from the University of York in 1995. Since then he has founded three start-up companies, all of which have succeeded in transferring real-time systems research into commercial product. At Northern Real-Time Technologies Ltd. (1995–1997) he was responsible for development of the Volcano CAN software library. At LiveDevices Ltd. (1997–2001) he was responsible for development of the Real-Time Architect suite of products, including an OSEK RTOS and schedulability analysis tools. In 2002, Robert returned to the University of York, and in 2004 he was involved in setting up a spin out company, Rapita Systems Ltd., aimed at transferring worst-case execution time analysis technology into industry. Robert is a member of the Real-Time Systems Research Group at the University of York, and a director of Rapita Systems Ltd. His research interests include scheduling algorithms and schedulability analysis for real-time systems. Alan Burns is head of the Real-Time Systems Research Group at the University of York. His research interests cover a number of aspects of real-time systems including the assessment of languages for use in the real-time domain, distributed operating systems, the formal specification of scheduling algorithms and implementation strategies, and the design of dependable user interfaces to real-time applications. He has authored/co-authored over 370 papers and 10 books, with a large proportion of them concentrating on real-time systems and the Ada programming language. Professor Burns has been actively involved in the creation of the Ravenscar Profile, a subset of Ada”s tasking model, designed to enable the analysis of real-time programs and their timing properties. Reinder J. Bril received a B.Sc. and an M.Sc. (both with honours) from the University of Twente, and a Ph.D. from the Technische Universiteit Eindhoven, the Netherlands. He started his professional career in January 1984 at the Delft University of Technology. From May 1985 until August 2004, he was with Philips, and worked in both Philips Research as well as Philips’ Business Units. He worked on various topics, including fault tolerance, formal specifications, software architecture analysis, and dynamic resource management, and in different application domains, e.g. high-volume electronics consumer products and (low volume) professional systems. In September 2004, he made a transfer back to the academic world, to the System Architecture and Networking (SAN) group of the Mathematics and Computer Science department of the Technische Universiteit Eindhoven. His main research interests are currently in the area of reservation-based resource management for networked embedded systems with real-time constraints. Johan J. Lukkien has been head of the System Architecture and Networking Research group at Eindhoven University of Technology since 2002. He received an M.Sc. and a Ph.D. from Groningen University in the Netherlands. In 1991, he joined Eindhoven University, after two years leave at the California Institute of Technology. His research interests include the design and performance analysis of parallel and distributed systems. Until 2000 he was involved in large-scale simulations in physics and chemistry. Since 2000, his research focus has shifted to the application domain of networked resource-constrained embedded systems. Contributions of the SAN group are in the area of component-based middleware for resource-constrained devices, distributed co-ordination, Quality of Service in networked systems and schedulability analysis in real-time systems.     

The Non-preemptive Scheduling of Periodic Tasks upon Multiprocessors

The non-preemptive scheduling of periodic task systems upon processing platforms comprised of several identical processors is considered. The exact problem has previously been proven intractable even upon single processors; sufficient conditions are presented here for determining whether a given periodic task system will meet all deadlines if scheduled non-preemptively upon a multiprocessor platform using the earliest-deadline first scheduling algorithm. Supported in part by the National Science Foundation (Grant Nos. CCR-9988327 and ITR-0082866). Sanjoy Baruah is a professor of Computer Science at the University of North Carolina at Chapel Hill. He received his Ph.D. from the University of Texas at Austin in 1993. His research and teaching interests are in scheduling theory, real-time and safety-critical system design, and resource-allocation and sharing in distributed computing environments.     

Dynamic Real-time Scheduling of Firm Periodic Tasks with Hard and Soft Aperiodic Tasks

In this paper, we address the problem of the dynamic scheduling of skippable periodic task sets (i.e., period tasks allowing occasional skips of instances), together with aperiodic tasks. Scheduling of tasks is handled thanks to the merging of two existing approaches: the Skip-Over task model and the EDL (Earliest Deadline as Late as possible) aperiodic task server. The objective is to provide two on-line scheduling algorithms, namely EDL-RTO and EDL-BWP, in order to minimize the average response time of soft aperiodic requests, while ensuring that the QoS (Quality of Service) of periodic tasks will never be less than a specified bound. We also extend our results to the acceptance of sporadic tasks (i.e., aperiodic tasks with deadlines). We show that these novel scheduling algorithms have better performance compared to related algorithms regarding aperiodic response time and acceptance ratio. Audrey Marchand guaduated in Computer Engineering at the Ecole polytechnique of the University of Nantes (France), in 2002. She is currently a PhD student at the University of Nantes. Her research interests include real-time scheduling theory, aperiodic service mechanisms, quality of service guarantees in soft real-time systems, and Linux-based real-time operating systems and applications. Maryline Chetto received the degree of Docteur de 3ème cycle in control engineering and the degree of Habilitée à Diriger des Recherches in Computer Science from the University of Nantes, France, in 1984 and 1993, respectively. From 1984 to 1985, she held the position of Assistant professor of Computer Science at the University of Rennes, while her research was with the Institut de Recherche en Informatique et Systèmes Aléatoires, Rennes. In 1986, she returned to Nantes and is currently a professor with the Institute of Technology of the University of Nantes. She is conducting her research at IRCCyN. Her main research interests include scheduling and fault-tolerance technologies for real-time applications. She has published more than 60 journal articles and conference papers in the area of real-time operating systems. She is the leader of a French national R&D project, namely Cleopatre, supported by the French government, which aims to provide free open source real-time solutions.     

I/O performance of an RAID-10 style parallel file system

Without any additional cost, all the disks on the nodes of a cluster can be connected together through CEFT-PVFS, an RAID-10 style parallel file system, to provide a multi-GB/s parallel I/O performance.I/O response time is one of the most important measures of quality of service for a client. When multiple clients submit data-intensive jobs at the same time, the response time experienced by the user is an indicator of the power of the cluster. In this paper, a queuing model is used to analyze in detail the average response time when multiple clients access CEFT-PVFS. The results reveal that response time is with a function of several operational parameters. The results show that I/O response time decreases with the increases in I/O buffer hit rate for read requests, write buffer size for write requests and the number of server nodes in the parallel file system, while the higher the I/O requests arrival rate, the longer the I/O response time. On the other hand, the collective power of a large cluster supported by CEFT-PVFS is shown to be able to sustain a steady and stable I/O response time for a relatively large range of the request arrival rate.     

Pre-Scheduling

Static scheduling has been well accepted for its predictability and online simplicity. Traditional static schedule generation techniques are usually based on the assumption of constant rate of resource supply known at design time. Under resource composition schemes, however, this assumption may not be valid for a workload to be statically scheduled. A pre-schedule is a static schedule without assuming constant and completely predictable rate of resource supply. In this paper, concepts of supply function and supply contract are introduced to define the actual online resource supply rate and the constraints to this rate known off-line. Based on these concepts, this paper defines the pre-scheduling problem, and presents a sound, complete, and PTIME pre-scheduler.This research is supported partially by grants from the Office of Naval Research under ONR contract N00014-03-1-0705 and the National Science Foundation under NSF grant CCR0207853.Weirong Wang received B.E. in computer engineering from Beijing University of Technology, M.A. and Ph.D. in computer science from the University of Texas at Austin. He is currently an automation engineer in Intel. His research interests include real-time and embedded systems, software engineering and algorithms.Aloysius K. Mok Aloysius K. Mok is Quincy Lee Centennial Professor in Computer Science at the University of Texas at Austin. He received the S.B. in electrical engineering, the S.M. in electrical engineering and computer science and the Ph.D. degrees in computer science, all from the Massachusetts Institute of Technology. Since 1983, Dr. Mok been on the faculty of the Department of Computer Sciences at the University of Texas at Austin. Professor Mok has done extensive research on computer software systems and is internationally known for his work in real-time systems. He is a past Chairman of the Techni- cal Committee on Real-Time Systems of the Institute of Electrical and Electronics Engineers, and has served on numerous national and international research and advisory panels. His current interests include real-time and embed- ded systems, robust and secure network-centric computing and real-time knowledge-based systems. Dr. Mok received in 2002 the IEEE TC on Real-Time Systems Award for his outstanding technical contributions and leadership achievements in real-time systems.Gerhard Fohler is Professor and leader of the predictably flexible real-time systems group at SDL. He received his Ph.D. from Vienna University of Technology in 1994 for research towards flexibility for offline scheduling in the MARS system. He then worked at the University of Massachusetts at Amherst as postdoctoral researcher within the SPRING project. During 1996–97, he was a researcher at Humboldt University Berlin, investigating issues of adaptive reliability and real-time. Gerhard Fohler is currently chairman of the Technical Committee on Real-Time Systems of EUROMICRO.     

Analysis of window-constrained execution time systems

Feasibility tests for hard real-time systems provide information about the schedulability of the task set. However, this information is a yes or a no answer, that is, whether the task set achieves the test or not. From the real-time system design point of view, having more information available would be useful. For example, how much the computation time can vary without jeopardising the system feasibility. This work specifically provides methods to determine off-line how much a task can increase its computation time, by maintaining the system feasibility under a dynamic priority scheduling. The extra time can be determined not only in all the task activations, but in n of a window of m invocations. This is what we call a window-constrained execution time system. The results presented in this work can be used in all kinds of real-time systems: fault tolerance management, imprecise computation, overrun handling, control applications, etc. Patricia Balbastre is an assistant professor of Computer Engineering. She graduated in Electronic Engineering at the Technical University of Valencia, Spain, in 1998. And the Ph.D. degree in Computer Science at the same university in 2002. Her main research interests include real-time operating systems, dynamic scheduling algorithms and real-time control. Ismael Ripoll received the B.S. degree from the Polytechnic University of Valencia, Spain, in 1992; the Ph.D. degree in Computer Science at the Polytechnic University of Valencia, Spain, in 1996. Currently he is Professor in the DISCA Department of the same University. His research interests include embedded and real-time operating systems. Alfons Crespo is Professor of the Department of Computer Engineering of the Technical University of Valencia. He received the PhD in Computer Science from the Technical University of Valencia, Spain, in 1984. He held the position of Associate professor in 1986 and full Professor in 1991. He leads the group of Industrial Informatics and has been the responsible of several European and Spanish research projects. His main research interest include different aspects of the real-time systems (scheduling, hardware support, scheduling and control integration, …). He has published more than 60 papers in specialised journals and conferences in the area of real-time systems.     

Robust control design of a class of nonlinear systems in polynomial lower-triangular form

This paper investigates the problem of global robust stabilization for a wide class of nonlinear systems, called polynomial lower-triangular form (pLTF), which expands LTF to a more general case. The aim is explicitly constructing the smooth controller for the class of systems with static uncertainties, by adding and modifying a power integrator in a recursive manner. The pLTF relaxes the restrictions on the structure of the normal LTF and enlarges the family of systems that are stabilizable. Examples are also provided to show the practical usage of this class of systems and the effectiveness of the design method. Recommended by Editorial Board member Hyungbo Shim under the direction of Editor Jae Weon Choi. Bing Wang received the B.S. degree from the Huazhong University of Science and Technology, and the Ph.D. degree from the University of Science and Technology of China, in 1998 and 2006, respectively. He is currently working in College of Electrical Engineering, Hohai University. His research interests include robust control, nonlinear control and power systems. Haibo Ji received the B.S. and Ph.D. degrees in Mechanical Engineering from ZheJiang University and Beijing University in 1984 and 1990 respectively. He is currently a Professor in the Dept. of Automation, USTC. His research interests include nonlinear control and adaptive control. Jin Zhu received the B.S. and Ph.D. degrees in Control Science and Engineering from University of Science & Technology of Chinain 2001 and 2006 respectively. He is currently a Post-doc in Han-Yang University, Korea. His research interests include Markovian jump systems and nonlinear control.