25,826 research outputs found
Investigation of Air Transportation Technology at Princeton University, 1989-1990
The Air Transportation Technology Program at Princeton University proceeded along six avenues during the past year: microburst hazards to aircraft; machine-intelligent, fault tolerant flight control; computer aided heuristics for piloted flight; stochastic robustness for flight control systems; neural networks for flight control; and computer aided control system design. These topics are briefly discussed, and an annotated bibliography of publications that appeared between January 1989 and June 1990 is given
Enforcing Architectural Styles in Presence of Unexpected Distributed Reconfigurations
Architectural Design Rewriting (ADR, for short) is a rule-based formal
framework for modelling the evolution of architectures of distributed systems.
Rules allow ADR graphs to be refined. After equipping ADR with a simple logic,
we equip rules with pre- and post-conditions; the former constraints the
applicability of the rules while the later specifies properties of the
resulting graphs. We give an algorithm to compute the weakest pre-condition out
of a rule and its post-condition. On top of this algorithm, we design a simple
methodology that allows us to select which rules can be applied at the
architectural level to reconfigure a system so to regain its architectural
style when it becomes compromised by unexpected run-time reconfigurations.Comment: In Proceedings ICE 2012, arXiv:1212.345
A Cyclic Distributed Garbage Collector for Network Objects
This paper presents an algorithm for distributed garbage collection and outlines its implementation within the Network Objects system. The algorithm is based on a reference listing scheme, which is augmented by partial tracing in order to collect distributed garbage cycles. Processes may be dynamically organised into groups, according to appropriate heuristics, to reclaim distributed garbage cycles. The algorithm places no overhead on local collectors and suspends local mutators only briefly. Partial tracing of the distributed graph involves only objects thought to be part of a garbage cycle: no collaboration with other processes is required. The algorithm offers considerable flexibility, allowing expediency and fault-tolerance to be traded against completeness
Robust distributed linear programming
This paper presents a robust, distributed algorithm to solve general linear
programs. The algorithm design builds on the characterization of the solutions
of the linear program as saddle points of a modified Lagrangian function. We
show that the resulting continuous-time saddle-point algorithm is provably
correct but, in general, not distributed because of a global parameter
associated with the nonsmooth exact penalty function employed to encode the
inequality constraints of the linear program. This motivates the design of a
discontinuous saddle-point dynamics that, while enjoying the same convergence
guarantees, is fully distributed and scalable with the dimension of the
solution vector. We also characterize the robustness against disturbances and
link failures of the proposed dynamics. Specifically, we show that it is
integral-input-to-state stable but not input-to-state stable. The latter fact
is a consequence of a more general result, that we also establish, which states
that no algorithmic solution for linear programming is input-to-state stable
when uncertainty in the problem data affects the dynamics as a disturbance. Our
results allow us to establish the resilience of the proposed distributed
dynamics to disturbances of finite variation and recurrently disconnected
communication among the agents. Simulations in an optimal control application
illustrate the results
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