Nathan Fisher

The partitioned multiprocessor scheduling of sporadic task systems

A polynomial-time algorithm is presented for partitioning a collection of sporadic tasks among the processors of an identical multiprocessor platform. Since the partitioning problem is NP-hard in the strong sense, this algorithm is unlikely to be optimal. A quantitative characterization of its worst-case performance is provided in terms of resource augmentation; it is shown that any set of sporadic tasks that can be partitioned among the processors of an m-processor identical multiprocessor platform will be partitioned by this algorithm on an m-processor platform in which each processor is (4 - 2/m) times as fast

The partitioned scheduling of sporadic tasks according to static-priorities

A polynomial-time algorithm is presented for partitioning a collection of sporadic tasks among the processors of an identical multiprocessor platform with static-priority scheduling on each individual processor. Since the partitioning problem is easily seen to be NP-hard in the strong sense, this algorithm is not optimal. A quantitative characterization of its worst-case performance is provided in terms of sufficient conditions and resource augmentation approximation bounds. The partitioning algorithm is also evaluated over randomly generated task systems

The Design of an EDF-Scheduled Resource-Sharing Open Environment

We study the problem of executing a collection of independently designed and validated task systems upon a common platform comprised of a preemptive processor and additional shared resources. We present an abstract formulation of the problem and identify the major issues that must be addressed in order to solve this problem. We present (and prove the correctness of) algorithms that address these issues, and thereby obtain a design for an open real-time environment in the presence of shared global resources.

The partitioned multiprocessor scheduling of deadline-constrained sporadic task systems

A polynomial-time algorithm is presented for partitioning a collection of sporadic tasks, each constrained to have its relative-deadline parameter be no larger than its period parameter, among the processors of an identical multiprocessor platform. Since the partitioning problem is easily seen to be NP-hard in the strong sense, this algorithm is unlikely to be optimal. A quantitative characterization of its worst-case performance is provided in terms of resource augmentation. It is shown that any set of sporadic tasks that can be partitioned among the processors of an m-processor identical multiprocessor platform will be partitioned by this algorithm on an m-processor platform in which each processor is (3-(1/m)) times as fast.

Algorithms for Determining the Demand-Based Load of a Sporadic Task System

The load parameter of a sporadic task system is defined to be the largest possible cumulative execution requirement that can be generated by jobs of the task system over any time interval, normalized by the length of the interval. This parameter is known to play a very important role in the uniprocessor feasibility analysis of sporadic task systems. In this paper, it is shown that the load of a sporadic task system may be used as an accurate indicator of its feasibility upon preemptive multiprocessors as well. Exact algorithms, and approximate ones that can be guaranteed to be accurate to within an arbitrary additive error > 0, for computing a task systems load are presented and proven correct. The performance of these algorithms is evaluated by simulation over randomly generated task systems

Optimal online multiprocessor scheduling of sporadic real-time tasks is impossible

Optimal online scheduling algorithms are known for sporadic task systems scheduled upon a single processor. Additionally, optimal online scheduling algorithms are also known for restricted subclasses of sporadic task systems upon an identical multiprocessor platform. The research reported in this article addresses the question of existence of optimal online multiprocessor scheduling algorithms for general sporadic task systems. Our main result is a proof of the impossibility of optimal online scheduling for sporadic task systems upon a system comprised of two or more processors. The result is shown by finding a sporadic task system that is feasible on a multiprocessor platform that cannot be correctly scheduled by any possible online, deterministic scheduling algorithm. Since the sporadic task model is a subclass of many more general real-time task models, the nonexistence of optimal scheduling algorithms for the sporadic task systems implies nonexistence for any model which generalizes the sporadic task model.

Resource-Sharing Servers for Open Environments

We study the problem of executing a collection of independently designed and validated task systems upon a common platform composed of a preemptive processor and additional shared resources. We present an abstract formulation of the problem and identify the major issues that must be addressed in order to solve this problem. We present and prove the correctness of algorithms that address these issues, and thereby obtain a design for an open real-time environment.

Global fixed-priority scheduling of arbitrary-deadline sporadic task systems

Fixed Task Priority (FTP) scheduling algorithms are priority-driven scheduling algorithms in which all jobs generated by each recurrent task are restricted to have the same priority. The multiprocessor FTP scheduling of sporadic task systems is studied in this paper. A new sufficient schedulability test is presented and proved correct. It is shown that this test offers non-trivial quantitative guarantees, including a processor speedup bound.

Approximate Bandwidth Allocation for Compositional Real-Time Systems

Allocation of bandwidth among components is a fundamental problem in compositional real-time systems. State-of-the-art algorithms for bandwidth allocation use either exponential-time or pseudo-polynomial-time techniques for exact allocation, or linear-time, utilization-based techniques which may over-provision bandwidth. In this paper, we develop a fully-polynomial-time approximation scheme (FPTAS) for allocating bandwidth for sporadic task systems scheduled by earliest-deadline first (EDF) upon an Explicit-Deadline Periodic (EDP) resource. Our algorithm takes, as parameters, the task system and an accuracy parameter

The Design and Analysis of Thermal-Resilient Hard-Real-Time Systems

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