33,425 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
Frequency-modulated continuous-wave LiDAR compressive depth-mapping
We present an inexpensive architecture for converting a frequency-modulated
continuous-wave LiDAR system into a compressive-sensing based depth-mapping
camera. Instead of raster scanning to obtain depth-maps, compressive sensing is
used to significantly reduce the number of measurements. Ideally, our approach
requires two difference detectors. % but can operate with only one at the cost
of doubling the number of measurments. Due to the large flux entering the
detectors, the signal amplification from heterodyne detection, and the effects
of background subtraction from compressive sensing, the system can obtain
higher signal-to-noise ratios over detector-array based schemes while scanning
a scene faster than is possible through raster-scanning. %Moreover, we show how
a single total-variation minimization and two fast least-squares minimizations,
instead of a single complex nonlinear minimization, can efficiently recover
high-resolution depth-maps with minimal computational overhead. Moreover, by
efficiently storing only data points from measurements of an
pixel scene, we can easily extract depths by solving only two linear equations
with efficient convex-optimization methods
Secure Multiparty Sessions with Topics
Multiparty session calculi have been recently equipped with security
requirements, in order to guarantee properties such as access control and leak
freedom. However, the proposed security requirements seem to be overly
restrictive in some cases. In particular, a party is not allowed to communicate
any kind of public information after receiving a secret information. This does
not seem justified in case the two pieces of information are totally unrelated.
The aim of the present paper is to overcome this restriction, by designing a
type discipline for a simple multiparty session calculus, which classifies
messages according to their topics and allows unrestricted sequencing of
messages on independent topics.Comment: In Proceedings PLACES 2016, arXiv:1606.0540
Relative Expressive Power of Navigational Querying on Graphs
Motivated by both established and new applications, we study navigational
query languages for graphs (binary relations). The simplest language has only
the two operators union and composition, together with the identity relation.
We make more powerful languages by adding any of the following operators:
intersection; set difference; projection; coprojection; converse; and the
diversity relation. All these operators map binary relations to binary
relations. We compare the expressive power of all resulting languages. We do
this not only for general path queries (queries where the result may be any
binary relation) but also for boolean or yes/no queries (expressed by the
nonemptiness of an expression). For both cases, we present the complete Hasse
diagram of relative expressiveness. In particular the Hasse diagram for boolean
queries contains some nontrivial separations and a few surprising collapses.Comment: An extended abstract announcing the results of this paper was
presented at the 14th International Conference on Database Theory, Uppsala,
Sweden, March 201
Type-elimination-based reasoning for the description logic SHIQbs using decision diagrams and disjunctive datalog
We propose a novel, type-elimination-based method for reasoning in the
description logic SHIQbs including DL-safe rules. To this end, we first
establish a knowledge compilation method converting the terminological part of
an ALCIb knowledge base into an ordered binary decision diagram (OBDD) which
represents a canonical model. This OBDD can in turn be transformed into
disjunctive Datalog and merged with the assertional part of the knowledge base
in order to perform combined reasoning. In order to leverage our technique for
full SHIQbs, we provide a stepwise reduction from SHIQbs to ALCIb that
preserves satisfiability and entailment of positive and negative ground facts.
The proposed technique is shown to be worst case optimal w.r.t. combined and
data complexity and easily admits extensions with ground conjunctive queries.Comment: 38 pages, 3 figures, camera ready version of paper accepted for
publication in Logical Methods in Computer Scienc
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