5,213 research outputs found
A TEMPORAL RELATIONAL ALGEBRA AS A BASIS FOR TEMPORAL RELATIONAL COMPLETENESS
We define a temporal algebra that is applicable to any
temporal relational data model supporting discrete linear
bounded time. This algebra has the five basic
relational algebra operators extended to the temporal
domain and an operator of linear recursion. We
show that this algebra has the expressive power of a
safe temporal calculus based on the predicate temporal
logic with the until and since temporal operators.
In [CrC189], a historical calculus was proposed as a
basis for historical relational completeness. We propose
the temporal algebra defined in this paper and
the equivalent temporal calculus as an alternative basis
for temporal relational completeness.Information Systems Working Papers Serie
Temporal Stream Algebra
Data stream management systems (DSMS) so far focus on
event queries and hardly consider combined queries to both
data from event streams and from a database. However,
applications like emergency management require combined
data stream and database queries. Further requirements are
the simultaneous use of multiple timestamps after different
time lines and semantics, expressive temporal relations between multiple time-stamps and
exible negation, grouping
and aggregation which can be controlled, i. e. started and
stopped, by events and are not limited to fixed-size time
windows. Current DSMS hardly address these requirements.
This article proposes Temporal Stream Algebra (TSA) so
as to meet the afore mentioned requirements. Temporal
streams are a common abstraction of data streams and data-
base relations; the operators of TSA are generalizations of
the usual operators of Relational Algebra. A in-depth 'analysis of temporal relations guarantees that valid TSA expressions are non-blocking, i. e. can be evaluated incrementally.
In this respect TSA differs significantly from previous algebraic approaches which use specialized operators to prevent
blocking expressions on a "syntactical" level
Analysing Temporal Relations – Beyond Windows, Frames and Predicates
This article proposes an approach to rely on the standard
operators of relational algebra (including grouping and ag-
gregation) for processing complex event without requiring
window specifications. In this way the approach can pro-
cess complex event queries of the kind encountered in appli-
cations such as emergency management in metro networks.
This article presents Temporal Stream Algebra (TSA) which
combines the operators of relational algebra with an analy-
sis of temporal relations at compile time. This analysis de-
termines which relational algebra queries can be evaluated
against data streams, i. e. the analysis is able to distinguish
valid from invalid stream queries. Furthermore the analysis
derives functions similar to the pass, propagation and keep
invariants in Tucker's et al. \Exploiting Punctuation Seman-
tics in Continuous Data Streams". These functions enable
the incremental evaluation of TSA queries, the propagation
of punctuations, and garbage collection. The evaluation of
TSA queries combines bulk-wise and out-of-order processing
which makes it tolerant to workload bursts as they typically
occur in emergency management. The approach has been
conceived for efficiently processing complex event queries on
top of a relational database system. It has been deployed
and tested on MonetDB
ON COMPLETENESS OF HISTORICAL RELATIONAL QUERY LANGUAGES
Numerous proposals for extending the relational data model to incorporate the temporal
dimension of data have appeared in the past several years. These proposals have differed
considerably in the way that the temporal dimension has been incorporated both into the
structure of the extended relations of these temporal models, and consequently into the
extended relational algebra or calculus that they define. Because of these differences it has
been difficult to compare the proposed models and to make judgments as to which of them
might in some sense be equivalent or even better. In this paper we define the notions of
temporally grouped and temporally ungrouped historical data models and propose
two notions of historical relational completeness, analogous to Codd's notion of relational
completeness, one for each type of model. We show that the temporally ungrouped
models are less powerful than the grouped models, but demonstrate a technique for extending
the ungrouped models with a grouping mechanism to capture the additional semantic
power of temporal grouping. For the ungrouped models we define three different languages,
a temporal logic, a logic with explicit reference to time, and a temporal algebra, and show
that under certain assumptions all three are equivalent in power. For the grouped models
we define a many-sorted logic with variables over ordinary values, historical values, and
times. Finally, we demonstrate the equivalence of this grouped calculus and the ungrouped
calculus extended with the proposed grouping mechanism. We believe the classification of
historical data models into grouped and ungrouped provides a useful framework for the
comparison of models in the literature, and furthermore the exposition of equivalent languages
for each type provides reasonable standards for common, and minimal, notions of
historical relational completeness.Information Systems Working Papers Serie
ON COMPLETENESS OF HISTORICAL RELATIONAL DATA MODELS
Several proposals for extending the relational data model to incorporate the
temporal dimension of data have appeared in the past several years. These
proposals have differed considerably in the way that the temporal dimension
has been incorporated both into the structure of the extended relations that
are defined as part of these extended model, and into the operations of the
extended relational algebra or calculus component of the models. Because
of these differences it has been difficult to compare the proposed models and
to make judgements as to which of them is "better" or indeed, the "best."
In this paper we propose a notion of historical relational completeness,
analogous to Codd's notion of relational completeness, and examine several
historical relational proposals in light of this standard.Information Systems Working Papers Serie
On Completeness of Historical Relational Query Languages
Numerous proposals for extending the relational data model to incorporate the temporal
dimension of data have appeared in the past several years. These proposals have differed
considerably in the way that the temporal dimension has been incorporated both into the
structure of the extended relations of these temporal models, and consequently into the
extended relational algebra or calculus that they define. Because of these differences it
has been difficult to compare the proposed models and to make judgments as to which of
them might in some sense be equivalent or even better. In this paper we define the notions of
temporally grouped and temporally ungrouped historical data models and propose two
notions of historical reIationa1 completeness, analogous to Codd's notion of relational
completeness, one for each type of model. We show that the temporally ungrouped models
are less expressive than the grouped models, but demonstrate a technique for extending the
ungrouped models with a grouping mechanism to capture the additional semantic power
of temporal grouping. For the ungrouped models we define three different languages, a
temporal logic, a logic with explicit reference to time, and a temporal algebra, and show
that under certain assumptions all three are equivalent in power. For the grouped models
we define a many-sorted logic with variables over ordinary values, historical values, and
times. Finally, we demonstrate the equivalence of this grouped calculus and the ungrouped
calculus extended with a grouping mechanism. We believe the classification of historical
data models into grouped and ungrouped provides a useful framework for the comparison
of models in the literature, and furthermore the exposition of equivalent languages for each
type provides reasonable standards for common, and minimal, notions of historical relational
completeness.Information Systems Working Papers Serie
Completeness of Flat Coalgebraic Fixpoint Logics
Modal fixpoint logics traditionally play a central role in computer science,
in particular in artificial intelligence and concurrency. The mu-calculus and
its relatives are among the most expressive logics of this type. However,
popular fixpoint logics tend to trade expressivity for simplicity and
readability, and in fact often live within the single variable fragment of the
mu-calculus. The family of such flat fixpoint logics includes, e.g., LTL, CTL,
and the logic of common knowledge. Extending this notion to the generic
semantic framework of coalgebraic logic enables covering a wide range of logics
beyond the standard mu-calculus including, e.g., flat fragments of the graded
mu-calculus and the alternating-time mu-calculus (such as alternating-time
temporal logic ATL), as well as probabilistic and monotone fixpoint logics. We
give a generic proof of completeness of the Kozen-Park axiomatization for such
flat coalgebraic fixpoint logics.Comment: Short version appeared in Proc. 21st International Conference on
Concurrency Theory, CONCUR 2010, Vol. 6269 of Lecture Notes in Computer
Science, Springer, 2010, pp. 524-53
Query processing in temporal object-oriented databases
This PhD thesis is concerned with historical data management in the context of objectoriented
databases. An extensible approach has been explored to processing temporal object queries within a uniform query framework. By the uniform framework, we mean
temporal queries can be processed within the existing object-oriented framework that is extended from relational framework, by extending the existing query processing
techniques and strategies developed for OODBs and RDBs.
The unified model of OODBs and RDBs in UmSQL/X has been adopted as a basis for this purpose. A temporal object data model is thereby defined by incorporating a time
dimension into this unified model of OODBs and RDBs to form temporal relational-like cubes but with the addition of aggregation and inheritance hierarchies. A query algebra,
that accesses objects through these associations of aggregation, inheritance and timereference, is then defined as a general query model /language. Due to the extensive
features of our data model and reducibility of the algebra, a layered structure of query processor is presented that provides a uniforrn framework for processing temporal object
queries. Within the uniform framework, query transformation is carried out based on a set of transformation rules identified that includes the known relational and object rules plus those pertaining to the time dimension. To evaluate a temporal query involving a path with timereference, a strategy of decomposition is proposed. That is, evaluation of an enhanced path, which is defined to extend a path with time-reference, is decomposed by initially dividing the path into two sub-paths: one containing the time-stamped class that can be optimized by
making use of the ordering information of temporal data and another an ordinary sub-path (without time-stamped classes) which can be further decomposed and evaluated using
different algorithms. The intermediate results of traversing the two sub-paths are then joined together to create the query output. Algorithms for processing the decomposed query components, i. e., time-related operation algorithms, four join algorithms (nested-loop forward join, sort-merge forward join, nested-loop reverse join and sort-merge reverse join) and their modifications, have been presented with cost analysis and implemented with stream processing techniques using C++. Simulation results are also provided. Both cost analysis and simulation show the effects of time on the query processing algorithms: the join time cost is linearly increased with the expansion in the number of time-epochs (time-dimension in the case of a regular TS). It is also shown that using heuristics that make use of time information can lead to a significant time cost saving. Query processing with incomplete temporal data has also been discussed
Applying Formal Methods to Networking: Theory, Techniques and Applications
Despite its great importance, modern network infrastructure is remarkable for
the lack of rigor in its engineering. The Internet which began as a research
experiment was never designed to handle the users and applications it hosts
today. The lack of formalization of the Internet architecture meant limited
abstractions and modularity, especially for the control and management planes,
thus requiring for every new need a new protocol built from scratch. This led
to an unwieldy ossified Internet architecture resistant to any attempts at
formal verification, and an Internet culture where expediency and pragmatism
are favored over formal correctness. Fortunately, recent work in the space of
clean slate Internet design---especially, the software defined networking (SDN)
paradigm---offers the Internet community another chance to develop the right
kind of architecture and abstractions. This has also led to a great resurgence
in interest of applying formal methods to specification, verification, and
synthesis of networking protocols and applications. In this paper, we present a
self-contained tutorial of the formidable amount of work that has been done in
formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial
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