5,126 research outputs found
Towards Streaming Evaluation of Queries with Correlation in Complex Event Processing
Complex event processing (CEP) has gained a lot of attention for evaluating complex patterns over high-throughput data streams. Recently, new algorithms for the evaluation of CEP patterns have emerged with strong guarantees of efficiency, i.e. constant update-time per tuple and constant-delay enumeration. Unfortunately, these techniques are restricted for patterns with local filters, limiting the possibility of using joins for correlating the data of events that are far apart.
In this paper, we embark on the search for efficient evaluation algorithms of CEP patterns with joins. We start by formalizing the so-called partition-by operator, a standard operator in data stream management systems to correlate contiguous events on streams. Although this operator is a restricted version of a join query, we show that partition-by (without iteration) is equally expressive as hierarchical queries, the biggest class of full conjunctive queries that can be evaluated with constant update-time and constant-delay enumeration over streams. To evaluate queries with partition-by we introduce an automata model, called chain complex event automata (chain-CEA), an extension of complex event automata that can compare data values by using equalities and disequalities. We show that this model admits determinization and is expressive enough to capture queries with partition-by. More importantly, we provide an algorithm with constant update time and constant delay enumeration for evaluating any query definable by chain-CEA, showing that all CEP queries with partition-by can be evaluated with these strong guarantees of efficiency
Constant-Delay Enumeration for Nondeterministic Document Spanners
We consider the information extraction framework known as document spanners,
and study the problem of efficiently computing the results of the extraction
from an input document, where the extraction task is described as a sequential
variable-set automaton (VA). We pose this problem in the setting of enumeration
algorithms, where we can first run a preprocessing phase and must then produce
the results with a small delay between any two consecutive results. Our goal is
to have an algorithm which is tractable in combined complexity, i.e., in the
sizes of the input document and the VA; while ensuring the best possible data
complexity bounds in the input document size, i.e., constant delay in the
document size. Several recent works at PODS'18 proposed such algorithms but
with linear delay in the document size or with an exponential dependency in
size of the (generally nondeterministic) input VA. In particular, Florenzano et
al. suggest that our desired runtime guarantees cannot be met for general
sequential VAs. We refute this and show that, given a nondeterministic
sequential VA and an input document, we can enumerate the mappings of the VA on
the document with the following bounds: the preprocessing is linear in the
document size and polynomial in the size of the VA, and the delay is
independent of the document and polynomial in the size of the VA. The resulting
algorithm thus achieves tractability in combined complexity and the best
possible data complexity bounds. Moreover, it is rather easy to describe, in
particular for the restricted case of so-called extended VAs. Finally, we
evaluate our algorithm empirically using a prototype implementation.Comment: 29 pages. Extended version of arXiv:1807.09320. Integrates all
corrections following reviewer feedback. Outside of some minor formatting
differences and tweaks, this paper is the same as the paper to appear in the
ACM TODS journa
A stroboscopic averaging algorithm for highly oscillatory delay problems
We propose and analyze a heterogenous multiscale method for the efficient
integration of constant-delay differential equations subject to fast periodic
forcing. The stroboscopic averaging method (SAM) suggested here may provide
approximations with \(\mathcal{O}(H^2+1/\Omega^2)\) errors with a
computational effort that grows like \(H^{-1}\) (the inverse of the
stepsize), uniformly in the forcing frequency Omega
Unfaithful Glitch Propagation in Existing Binary Circuit Models
We show that no existing continuous-time, binary value-domain model for
digital circuits is able to correctly capture glitch propagation. Prominent
examples of such models are based on pure delay channels (P), inertial delay
channels (I), or the elaborate PID channels proposed by Bellido-D\'iaz et al.
We accomplish our goal by considering the solvability/non-solvability border of
a simple problem called Short-Pulse Filtration (SPF), which is closely related
to arbitration and synchronization. On one hand, we prove that SPF is solvable
in bounded time in any such model that provides channels with non-constant
delay, like I and PID. This is in opposition to the impossibility of solving
bounded SPF in real (physical) circuit models. On the other hand, for binary
circuit models with constant-delay channels, we prove that SPF cannot be solved
even in unbounded time; again in opposition to physical circuit models.
Consequently, indeed none of the binary value-domain models proposed so far
(and that we are aware of) faithfully captures glitch propagation of real
circuits. We finally show that these modeling mismatches do not hold for the
weaker eventual SPF problem.Comment: 23 pages, 15 figure
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