950 resultados para Railways, Scheduling, Heuristics, Search Algorithms


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Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a two-type heterogeneous multiprocessor platform. Each processor is either of type-1 or type-2 with each task having different execution time on each processor type. Jobs can migrate between processors of same type (referred to as intra-type migration) but cannot migrate between processors of different types. We present a new scheduling algorithm namely, LP-Relax(THR) which offers a guarantee that if a task set can be scheduled to meet deadlines by an optimal task assignment scheme that allows intra-type migration then LP-Relax(THR) meets deadlines as well with intra-type migration if given processors 1/THR as fast (referred to as speed competitive ratio) where THR <= 2/3.

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One of the most well-known bio-inspired algorithms used in optimization problems is the particle swarm optimization (PSO), which basically consists on a machinelearning technique loosely inspired by birds flocking in search of food. More specifically, it consists of a number of particles that collectively move on the search space in search of the global optimum. The Darwinian particle swarm optimization (DPSO) is an evolutionary algorithm that extends the PSO using natural selection, or survival of the fittest, to enhance the ability to escape from local optima. This paper firstly presents a survey on PSO algorithms mainly focusing on the DPSO. Afterward, a method for controlling the convergence rate of the DPSO using fractional calculus (FC) concepts is proposed. The fractional-order optimization algorithm, denoted as FO-DPSO, is tested using several well-known functions, and the relationship between the fractional-order velocity and the convergence of the algorithm is observed. Moreover, experimental results show that the FO-DPSO significantly outperforms the previously presented FO-PSO.

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Systems composed of distinct operational modes are a common necessity for embedded applications with strict timing requirements. With the emergence of multi-core platforms protocols to handle these systems are required in order to provide this basic functionality.In this work a description on the problems of creating an effective mode-transition protocol are presented and it is proven that in some cases previous single-core protocols can not be extended to handle the mode-transition in multi-core.

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We have developed SPARTS, a simulator of a generic embedded real-time device. It is designed to be extensible to accommodate different task properties, scheduling algorithms and/or hardware models for the wide variety of applications. SPARTS was developed to help the community investigate the behaviour of the real-time embedded systems and to quantify the associated constraints/overheads.

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Consider the problem of scheduling a set of sporadic tasks on a multiprocessor system to meet deadlines using a tasksplitting scheduling algorithm. Task-splitting (also called semipartitioning) scheduling algorithms assign most tasks to just one processor but a few tasks are assigned to two or more processors, and they are dispatched in a way that ensures that a task never executes on two or more processors simultaneously. A certain type of task-splitting algorithms, called slot-based task-splitting, is of particular interest because of its ability to schedule tasks at high processor utilizations. We present a new schedulability analysis for slot-based task-splitting scheduling algorithms that takes the overhead into account and also a new task assignment algorithm.

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Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.

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Embedded real-time systems often have to support the embedding system in very different and changing application scenarios. An aircraft taxiing, taking off and in cruise flight is one example. The different application scenarios are reflected in the software structure with a changing task set and thus different operational modes. At the same time there is a strong push for integrating previously isolated functionalities in single-chip multicore processors. On such multicores the behavior of the system during a mode change, when the systems transitions from one mode to another, is complex but crucial to get right. In the past we have investigated mode change in multiprocessor systems where a mode change requires a complete change of task set. Now, we present the first analysis which considers mode changes in multicore systems, which use global EDF to schedule a set of mode independent (MI) and mode specific (MS) tasks. In such systems, only the set of MS tasks has to be replaced during mode changes, without jeopardizing the schedulability of the MI tasks. Of prime concern is that the mode change is safe and efficient: i.e. the mode change needs to be performed in a predefined time window and no deadlines may be missed as a function of the mode change.

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We present a 12*(1+|R|/(4m))-speed algorithm for scheduling constrained-deadline sporadic real-time tasks on a multiprocessor comprising m processors where a task may request one of |R| sequentially-reusable shared resources.

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In this paper we consider global fixed-priority preemptive multiprocessor scheduling of constrained-deadline sporadic tasks that share resources in a non-nested manner. We develop a novel resource-sharing protocol and a corresponding schedulability test for this system. We also develop the first schedulability analysis of priority inheritance protocol for the aforementioned system. Finally, we show that these protocols are efficient (based on the developed schedulability tests) for a class of priority-assignments called reasonable priority-assignments.

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Consider the problem of scheduling sporadic tasks on a multiprocessor platform under mutual exclusion constraints. We present an approach which appears promising for allowing large amounts of parallel task executions and still ensures low amounts of blocking.

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Consider a distributed computer system comprising many computer nodes, each interconnected with a controller area network (CAN) bus. We prove that if priorities to message streams are assigned using rate-monotonic (RM) and if the requested capacity of the CAN bus does not exceed 25% then all deadlines are met.

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Componentised systems, in particular those with fault confinement through address spaces, are currently emerging as a hot topic in embedded systems research. This paper extends the unified rate-based scheduling framework RBED in several dimensions to fit the requirements of such systems: we have removed the requirement that the deadline of a task is equal to its period. The introduction of inter-process communication reflects the need to communicate. Additionally we also discuss server tasks, budget replenishment and the low level details needed to deal with the physical reality of systems. While a number of these issues have been studied in previous work in isolation, we focus on the problems discovered and lessons learned when integrating solutions. We report on our experiences implementing the proposed mechanisms in a commercial grade OKL4 microkernel as well as an application with soft real-time and best-effort tasks on top of it.

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We present a 12(1 + 3R/(4m)) competitive algorithm for scheduling implicit-deadline sporadic tasks on a platform comprising m processors, where a task may request one of R shared resources.

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It has been widely studied how to schedule real-time tasks on multiprocessor platforms. Several studies find optimal scheduling policies for implicit deadline task systems, but it is hard to understand how each policy utilizes the two important aspects of scheduling real-time tasks on multiprocessors:inter-job concurrency and job urgency. In this paper, we introduce a new scheduling policy that considers these two properties. We prove that the policy is optimal for the special case when the execution time of all tasks are equally one and deadlines are implicit, and observe that the policy is a new concept in that it is not an instance of Pfair or ERfair. It remains open to find a schedulability condition for general task systems under our scheduling policy.

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Cluster scheduling and collision avoidance are crucial issues in large-scale cluster-tree Wireless Sensor Networks (WSNs). The paper presents a methodology that provides a Time Division Cluster Scheduling (TDCS) mechanism based on the cyclic extension of RCPS/TC (Resource Constrained Project Scheduling with Temporal Constraints) problem for a cluster-tree WSN, assuming bounded communication errors. The objective is to meet all end-to-end deadlines of a predefined set of time-bounded data flows while minimizing the energy consumption of the nodes by setting the TDCS period as long as possible. Sinceeach cluster is active only once during the period, the end-to-end delay of a given flow may span over several periods when there are the flows with opposite direction. The scheduling tool enables system designers to efficiently configure all required parameters of the IEEE 802.15.4/ZigBee beaconenabled cluster-tree WSNs in the network design time. The performance evaluation of thescheduling tool shows that the problems with dozens of nodes can be solved while using optimal solvers.