1,122 research outputs found
Parallel discrete event simulation: A shared memory approach
With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential simulation of most queueing network models
The combinatorics of resource sharing
We discuss general models of resource-sharing computations, with emphasis on
the combinatorial structures and concepts that underlie the various deadlock
models that have been proposed, the design of algorithms and deadlock-handling
policies, and concurrency issues. These structures are mostly graph-theoretic
in nature, or partially ordered sets for the establishment of priorities among
processes and acquisition orders on resources. We also discuss graph-coloring
concepts as they relate to resource sharing.Comment: R. Correa et alii (eds.), Models for Parallel and Distributed
Computation, pp. 27-52. Kluwer Academic Publishers, Dordrecht, The
Netherlands, 200
Multi-Robot Local Motion Planning Using Dynamic Optimization Fabrics
In this paper, we address the problem of real-time motion planning for
multiple robotic manipulators that operate in close proximity. We build upon
the concept of dynamic fabrics and extend them to multi-robot systems, referred
to as Multi-Robot Dynamic Fabrics (MRDF). This geometric method enables a very
high planning frequency for high-dimensional systems at the expense of being
reactive and prone to deadlocks. To detect and resolve deadlocks, we propose
Rollout Fabrics where MRDF are forward simulated in a decentralized manner. We
validate the methods in simulated close-proximity pick-and-place scenarios with
multiple manipulators, showing high success rates and real-time performance.Comment: 6 pages + 1 page references, 2 tables, 4 figures, preprint version to
accepted paper to IEEE International Symposium on Multi-Robot & Multi-Agent
Systems, Boston, 202
Deadlock Prevention Policy with Behavioral Optimality or Suboptimality Achieved by the Redundancy Identification of Constraints and the Rearrangement of Monitors
This work develops an iterative deadlock prevention method for a special class of Petri nets that can well model a variety of flexible manufacturing systems. A deadlock detection technique, called mixed integer programming (MIP), is used to find a strict minimal siphon (SMS) in a plant model without a complete enumeration of siphons. The policy consists of two phases. At the first phase, SMSs are obtained by MIP technique iteratively and monitors are added to the complementary sets of the SMSs. For the possible existence of new siphons generated after the first phase, we add monitors with their output arcs first pointed to source transitions at the second phase to avoid new siphons generating and then rearrange the output arcs step by step on condition that liveness is preserved. In addition, an algorithm is proposed to remove the redundant constraints of the MIP problem in this paper. The policy improves the behavioral permissiveness of the resulting net and greatly enhances the structural simplicity of the supervisor. Theoretical analysis and experimental results verify the effectiveness of the proposed method
- …