Hybrid Multiresolution Simulation & Model Checking: Network-On-Chip Systems

abstract: Designers employ a variety of modeling theories and methodologies to create functional models of discrete network systems. These dynamical models are evaluated using verification and validation techniques throughout incremental design stages. Models created for these systems should directly represent their growing complexity with respect to composition and heterogeneity. Similar to software engineering practices, incremental model design is required for complex system design. As a result, models at early increments are significantly simpler relative to real systems. While experimenting (verification or validation) on models at early increments are computationally less demanding, the results of these experiments are less trustworthy and less rewarding. At any increment of design, a set of tools and technique are required for controlling the complexity of models and experimentation. A complex system such as Network-on-Chip (NoC) may benefit from incremental design stages. Current design methods for NoC rely on multiple models developed using various modeling frameworks. It is useful to develop frameworks that can formalize the relationships among these models. Fine-grain models are derived using their coarse-grain counterparts. Moreover, validation and verification capability at various design stages enabled through disciplined model conversion is very beneficial. In this research, Multiresolution Modeling (MRM) is used for system level design of NoC. MRM aids in creating a family of models at different levels of scale and complexity with well-formed relationships. In addition, a variant of the Discrete Event System Specification (DEVS) formalism is proposed which supports model checking. Hierarchical models of Network-on-Chip components may be created at different resolutions while each model can be validated using discrete-event simulation and verified via state exploration. System property expressions are defined in the DEVS language and developed as Transducers which can be applied seamlessly for model checking and simulation purposes. Multiresolution Modeling with verification and validation capabilities of this framework complement one another. MRM manages the scale and complexity of models which in turn can reduces V&V time and effort and conversely the V&V helps ensure correctness of models at multiple resolutions. This framework is realized through extending the DEVS-Suite simulator and its applicability demonstrated for exemplar NoC models.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Decentralized Multi-Robot Social Navigation in Constrained Environments via Game-Theoretic Control Barrier Functions

We present an approach to ensure safe and deadlock-free navigation for decentralized multi-robot systems operating in constrained environments, including doorways and intersections. Although many solutions have been proposed to ensure safety, preventing deadlocks in a decentralized fashion with global consensus remains an open problem. We first formalize the objective as a non-cooperative, non-communicative, partially observable multi-robot navigation problem in constrained spaces with multiple conflicting agents, which we term as social mini-games. Our approach to ensuring safety and liveness rests on two novel insights: (i) deadlock resolution is equivalent to deriving a mixed-Nash equilibrium solution to a social mini-game and (ii) this mixed-Nash strategy can be interpreted as an analogue to control barrier functions (CBFs), that can then be integrated with standard CBFs, inheriting their safety guarantees. Together, the standard CBF along with the mixed-Nash CBF analogue preserves both safety and liveness. We evaluate our proposed game-theoretic navigation algorithm in simulation as well on physical robots using F1/10 robots, a Clearpath Jackal, as well as a Boston Dynamics Spot in a doorway, corridor intersection, roundabout, and hallway scenario. We show that (i) our approach results in safer and more efficient navigation compared to local planners based on geometrical constraints, optimization, multi-agent reinforcement learning, and auctions, (ii) our deadlock resolution strategy is the smoothest in terms of smallest average change in velocity and path deviation, and most efficient in terms of makespan (iii) our approach yields a flow rate of 2.8 - 3.3 (ms)^{-1 which is comparable to flow rate in human navigation at 4 (ms)^{-1}.Comment: arXiv admin note: text overlap with arXiv:2306.0881

Modeling sequential resource allocation systems using Extended Finite Automata

Deadlock avoidance for resource allocation systems (RAS) is a well-established problem in the Discrete Event System (DES) literature. This paper is mainly concerned with modeling the class of Conjunctive / Disjunctive sequential resource allocation systems (C/D RAS) as finite automata extended with variables. The proposed modeling approach allows for modeling multiple instance execution, routing flexibility and failure handling. With an appropriate model of the system, a symbolic approach is then used to synthesize the optimal supervisor, in the least restrictive sense. Furthermore, a set of compact logical formulae can be extracted and attached to the original model, which results in a modular and comprehensible representation of the supervisor

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