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Algorithms and Complexity Concerning the Preemptive Scheduling of Periodic, RealTime Tasks on One Processor
 RealTime Systems
, 1990
"... We investigate the preemptive scheduling of periodic, realtime task systems on one processor. First, we show that when all parameters to the system are integers, we may assume without loss of generality that all preemptions occur at integer time values. We then assume, for the remainder of the pape ..."
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Cited by 242 (15 self)
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We investigate the preemptive scheduling of periodic, realtime task systems on one processor. First, we show that when all parameters to the system are integers, we may assume without loss of generality that all preemptions occur at integer time values. We then assume, for the remainder of the paper, that all parameters are indeed integers. We then give as our main lemma both necessary and sufficient conditions for a task system to be feasible on one processor. Although these conditions cannot, in general, be tested efficiently (unless P = NP), they do allow us to give efficient algorithms for deciding feasibility on one processor for certain types of periodic task systems. For example, we give a pseudopolynomial time algorithm for synchronous systems whose densities are bounded by a fixed constant less than 1. This algorithm represents an exponential improvement over the previous best algorithm. We also give a polynomialtime algorithm for systems having a fixed number of distinct typ...
PerformanceBased Design of Distributed RealTime Systems
 In Proceedings of the Third IEEE RealTime Technology and Applications Symposium
, 1997
"... This paper presents a design method for distributed systems with statistical, endtoend realtime constraints, and with underlying stochastic resource requirements. A system is modeled as a set of chains, where each chain is a distributed pipeline of tasks, and a task can represent any activity req ..."
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Cited by 5 (1 self)
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This paper presents a design method for distributed systems with statistical, endtoend realtime constraints, and with underlying stochastic resource requirements. A system is modeled as a set of chains, where each chain is a distributed pipeline of tasks, and a task can represent any activity requiring nonzero load from some CPU or network resource. Every chain has two endtoend performance requirements: Its delay constraint denotes the maximum amount time a computation can take to flow through the pipeline, from input to output. A chain's quality constraint mandates a minimum allowable success rate for outputs that meet their delay constraints. Our design method solves this problem by deriving (1) a fixed proportion of resource load to give each task; and (2) a deterministic processing rate for every chain, in which the objective is to optimize the output success rate (as determined by an analytical approximation). We demonstrate our technique on an example system, and compare the...