About: Aperiodic graph is a research topic. Over the lifetime, 2105 publications have been published within this topic receiving 39134 citations.
Papers published on a yearly basis
TL;DR: The value of depth-first search or “backtracking” as a technique for solving problems is illustrated by two examples of an improved version of an algorithm for finding the strongly connected components of a directed graph.
Abstract: The value of depth-first search or “backtracking” as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected componen...
TL;DR: A new algorithm is presented, the Sporadic Server algorithm, which greatly improves response times for soft deadline a periodic tasks and can guarantee hard deadlines for both periodic and aperiodic tasks.
Abstract: This thesis develops the Sporadic Server (SS) algorithm for scheduling aperiodic tasks in real-time systems. The SS algorithm is an extension of the rate monotonic algorithm which was designed to schedule periodic tasks. This thesis demonstrates that the SS algorithm is able to guarantee deadlines for hard-deadline aperiodic tasks and provide good responsiveness for soft-deadline aperiodic tasks while avoiding the schedulability penalty and implementation complexity of previous aperiodic service algorithms. It is also proven that the aperiodic servers created by the SS algorithm can be treated as equivalently-sized periodic tasks when assessing schedulability. This allows all the scheduling theories developed for the rate monotonic algorithm to be used to schedule aperiodic tasks. For scheduling aperiodic and periodic tasks that share data, this thesis defines the interactions and schedulability impact of using the SS algorithm with the priority inheritance protocols. For scheduling hard-deadline tasks with short deadlines, an extension of the rate monotonic algorithm and analysis is developed. To predict performance of the SS algorithm, this thesis develops models and equations that allow the use of standard queueing theory models to predict the average response time of soft-deadline aperiodic tasks serviced with a high-priority sporadic server. Implementation methods are also developed to support the SS algorithm in Ada and on the Futurebus+.
01 May 1963
TL;DR: In this article, the authors define S(P) as a SIA matrix where all the rows of Q are the same and all the columns of Q have the same columns.
Abstract: exists and all the rows of Q are the same. SIA matrices are defined differently in books on probability theory; see, for example,  or . The latter definition is more intuitive, takes longer to state, is easier to verify, and explains why the probabilist is interested in SIA matrices. A theorem in probability theory or matrix theory then says that the customary definition is equivalent to the one we have given. The latter is brief and emphasizes the property which will interest us in this note. We define S(P) by
01 Dec 1987
02 Dec 1992
TL;DR: A novel algorithm for servicing soft deadline aperiodic tasks in a real-time system in which hard deadline periodic tasks are scheduled using a fixed priority algorithm is presented and is proved to be optimal in the sense that it provides the shortest a Periodic response time among all possible a periodic service methods.
Abstract: A novel algorithm for servicing soft deadline aperiodic tasks in a real-time system in which hard deadline periodic tasks are scheduled using a fixed priority algorithm is presented. This algorithm is proved to be optimal in the sense that it provides the shortest aperiodic response time among all possible aperiodic service methods. Simulation studies show that it offers substantial performance improvements over current approaches, including the sporadic server algorithm. Moreover, standard queuing formulas can be used to predict aperiodic response times over a wide range of conditions. The algorithm can be extended to schedule hard deadline aperiodics and to efficiently reclaim unused periodic service time when periodic tasks have stochastic execution times. >
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