16,771 research outputs found
Nonlinear Matroid Optimization and Experimental Design
We study the problem of optimizing nonlinear objective functions over
matroids presented by oracles or explicitly. Such functions can be interpreted
as the balancing of multi-criteria optimization. We provide a combinatorial
polynomial time algorithm for arbitrary oracle-presented matroids, that makes
repeated use of matroid intersection, and an algebraic algorithm for vectorial
matroids.
Our work is partly motivated by applications to minimum-aberration
model-fitting in experimental design in statistics, which we discuss and
demonstrate in detail
Transient Reward Approximation for Continuous-Time Markov Chains
We are interested in the analysis of very large continuous-time Markov chains
(CTMCs) with many distinct rates. Such models arise naturally in the context of
reliability analysis, e.g., of computer network performability analysis, of
power grids, of computer virus vulnerability, and in the study of crowd
dynamics. We use abstraction techniques together with novel algorithms for the
computation of bounds on the expected final and accumulated rewards in
continuous-time Markov decision processes (CTMDPs). These ingredients are
combined in a partly symbolic and partly explicit (symblicit) analysis
approach. In particular, we circumvent the use of multi-terminal decision
diagrams, because the latter do not work well if facing a large number of
different rates. We demonstrate the practical applicability and efficiency of
the approach on two case studies.Comment: Accepted for publication in IEEE Transactions on Reliabilit
Lukasiewicz mu-Calculus
We consider state-based systems modelled as coalgebras whose type incorporates branching, and show that by suitably adapting the definition of coalgebraic bisimulation, one obtains a general and uniform account of the linear-time behaviour of a state in such a coalgebra. By moving away from a boolean universe of truth values, our approach can measure the extent to which a state in a system with branching is able to exhibit a particular linear-time behaviour. This instantiates to measuring the probability of a specific behaviour occurring in a probabilistic system, or measuring the minimal cost of exhibiting a specific behaviour in the case of weighted computations
A Dual-Engine for Early Analysis of Critical Systems
This paper presents a framework for modeling, simulating, and checking
properties of critical systems based on the Alloy language -- a declarative,
first-order, relational logic with a built-in transitive closure operator. The
paper introduces a new dual-analysis engine that is capable of providing both
counterexamples and proofs. Counterexamples are found fully automatically using
an SMT solver, which provides a better support for numerical expressions than
the existing Alloy Analyzer. Proofs, however, cannot always be found
automatically since the Alloy language is undecidable. Our engine offers an
economical approach by first trying to prove properties using a
fully-automatic, SMT-based analysis, and switches to an interactive theorem
prover only if the first attempt fails. This paper also reports on applying our
framework to Microsoft's COM standard and the mark-and-sweep garbage collection
algorithm.Comment: Workshop on Dependable Software for Critical Infrastructures (DSCI),
Berlin 201
Randomized Two-Process Wait-Free Test-and-Set
We present the first explicit, and currently simplest, randomized algorithm
for 2-process wait-free test-and-set. It is implemented with two 4-valued
single writer single reader atomic variables. A test-and-set takes at most 11
expected elementary steps, while a reset takes exactly 1 elementary step. Based
on a finite-state analysis, the proofs of correctness and expected length are
compressed into one table.Comment: 9 pages, 4 figures, LaTeX source; Submitte
Safe Schedulability of Bounded-Rate Multi-Mode Systems
Bounded-rate multi-mode systems (BMMS) are hybrid systems that can switch
freely among a finite set of modes, and whose dynamics is specified by a finite
number of real-valued variables with mode-dependent rates that can vary within
given bounded sets. The schedulability problem for BMMS is defined as an
infinite-round game between two players---the scheduler and the
environment---where in each round the scheduler proposes a time and a mode
while the environment chooses an allowable rate for that mode, and the state of
the system changes linearly in the direction of the rate vector. The goal of
the scheduler is to keep the state of the system within a pre-specified safe
set using a non-Zeno schedule, while the goal of the environment is the
opposite. Green scheduling under uncertainty is a paradigmatic example of BMMS
where a winning strategy of the scheduler corresponds to a robust
energy-optimal policy. We present an algorithm to decide whether the scheduler
has a winning strategy from an arbitrary starting state, and give an algorithm
to compute such a winning strategy, if it exists. We show that the
schedulability problem for BMMS is co-NP complete in general, but for two
variables it is in PTIME. We also study the discrete schedulability problem
where the environment has only finitely many choices of rate vectors in each
mode and the scheduler can make decisions only at multiples of a given clock
period, and show it to be EXPTIME-complete.Comment: Technical report for a paper presented at HSCC 201
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