This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
|
teaching:mfe:is [2016/04/01 16:30] svsummer |
teaching:mfe:is [2018/04/23 09:55] svsummer [Master Thesis in Collaboration with Euranova] |
||
|---|---|---|---|
| Line 1: | Line 1: | ||
| - | ====== MFE 2016-2017 : Web and Information Systems ====== | + | ====== MFE 2017-2018 : Web and Information Systems ====== |
| ===== Introduction ===== | ===== Introduction ===== | ||
| Line 18: | Line 18: | ||
| ===== Master Thesis in Collaboration with Euranova ===== | ===== Master Thesis in Collaboration with Euranova ===== | ||
| - | Our laboratory performs collaborative research with Euranova R&D (http://euranova.eu/). The list of subjects proposed for this year by Euranova can be found | + | Our laboratory performs collaborative research with Euranova R&D (http://euranova.eu/). The list of subjects proposed for this year by Euranova can be found {{:teaching:mfe:euranova_masterthesis_2017.pdf|here}}. |
| - | {{:teaching:mfe:master_thesis_euranova_2015.pdf|here}} | + | |
| These subject include topics on distributed graph processing, processing big data using Map/Reduce, cloud computing, and social networks. | These subject include topics on distributed graph processing, processing big data using Map/Reduce, cloud computing, and social networks. | ||
| Line 25: | Line 25: | ||
| * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]] | * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]] | ||
| - | ===== Complex Event Processing in Apache Spark and Apache Storm ===== | ||
| - | |||
| - | The master thesis is put forward in the context of the SPICES "Scalable Processing and mIning of Complex Events for Security-analytics" research project, funded by Innoviris. | ||
| - | |||
| - | Within this project, our lab is developping a declarative language for Complex Event Processing (CEP for short). The goal in Complex Event Processing is to derive pre-defined patterns in a stream of raw events. Raw events are typically sensor readings (such as "password incorrect for user X trying to log in on machine Y" or "file transfer from machine X to machine Y"). The goal of CEP is then to correlate these events into complex events. For example, repeated failed login attempts by X to Y should trigger a complex event "password cracking warning" that refers to all failed login attempts. | ||
| - | |||
| - | The objective of this master thesis is to build an interpreter/compiler for this declarative CEP language that targets the distributed computing frameworks Apache Spark and/or Apache Storm as backends. Getting aquaintend with these technologies is part of the master thesis objective. | ||
| - | |||
| - | **Validation of the approach** Validation of the proposed interpreter/compiler should be done on two levels: | ||
| - | * a theoretical level; by comparing the generated Spark/Storm processors to a processor based on "Incremental computation" that is being developped at the lab | ||
| - | * an experimental level; by proposing a benchmark collection of CEP queries that can be used to test the obtained interpreter/compiler, and report on the experimentally observed performance on this benchmark. | ||
| - | |||
| - | **Deliverables** of the master thesis project | ||
| - | * An overview of the processing models of Spark and Storm | ||
| - | * A definition of the declarative CEP language under consideration | ||
| - | * A description of the interpretation/compilation algorithm | ||
| - | * A theoretical comparison of this algorithm wrt an incremental evaluation algorithm. | ||
| - | * The interpreter/compiler itself (software artifact) | ||
| - | * A benchmark set of CEP queries and associated data sets for the experimental validation | ||
| - | * An experimental validation of the compiler, and analysis of the results. | ||
| - | |||
| - | **Interested?** | ||
| - | * Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]] | ||
| - | |||
| - | **Status**: available | ||
| - | |||
| - | |||
| - | ===== Graph Indexing for Fast Subgraph Isomorphism Testing ===== | ||
| - | |||
| - | There is an increasing amount of scientific data, mostly from the bio-medical sciences, that can be represented as collections of graphs (chemical molecules, gene interaction networks, ...). A crucial operation when searching in this data is that of subgraph isomorphism testing: given a pattern P that one is interested in (also a graph) in and a collection D of graphs (e.g., chemical molecules), find all graphs in G that have P as a subgraph. Unfortunately, the subgraph isomorphism problem is computationally intractable. In ongoing research, to enable tractable processing of this problem, we aim to reduce the number of candidate graphs in D to which a subgraph isomorphism test needs to be executed. Specifically, we index the graphs in the collection D by means of decomposing them into graphs for which subgraph isomorphism *is* tractable. An associated algorithm that filters graphs that certainly cannot match P can then formulated based on ideas from information retrieval. | ||
| - | |||
| - | In this master thesis project, the student will emperically validate on real-world datasets the extent to which graphs can be decomposed into graphs for which subgraph isomorphism is tractable, and run experiments to validate the effectiveness of the proposed method in terms of filtering power. | ||
| - | |||
| - | **Interested?** Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]] | ||
| - | |||
| - | **Status**: available | ||
| - | |||
| - | ===== A Scala-based runtime and compiler for Distributed Datalog ===== | ||
| - | |||
| - | Datalog is a fundamental query language in datamanagement based on logic programming. It essentially extends select-from-where SQL queries with recursion. There is a recent trend in data management research to use datalog to specify distributed applications, most notably on the web, as well as do inference on the semantic web. The goal of this thesis is to engineer a basic **distributed datalog system**, i.e., a system that is capable of compiling & running distributed datalog queries. The system should be implemented in the Scala programming language. Learning Scala is part of the master thesis project. | ||
| - | |||
| - | The system should: | ||
| - | * incorporate recently proposed worst-case join algorithms (i.e., the [[http://arxiv.org/abs/1210.0481|leapfrog trie join]]) | ||
| - | * employ known local datalog optimizations (such as magic sets and QSQ) | ||
| - | |||
| - | **Validation of the approach** The thesis should propose a benchmark collection of datalog queries and associated data workloads that be used to test the obtained system, and measure key performance characteristics (elasticity of the system; memory frootprint; overall running time, ...) | ||
| - | |||
| - | **Required reading**: | ||
| - | * Datalog and Recursive Query Processing - Foundations and trends in query processing. | ||
| - | * LogicBlox, Platform and Language: A Tutorial (Todd J. Green, Molham Aref, and Grigoris Karvounarakis) | ||
| - | * Dedalus: Datalog in Time and Space (Peter Alvaro, William R. Marczak, Neil Conway, Joseph M. Hellerstein, David Maier, and Russell Sears) | ||
| - | * Declarative Networking (Loo et al). For the distributed evaluation strategy. | ||
| - | * Parallel processing of recursive queries in distributed architectures (VLDB 1989) | ||
| - | * Evaluating recursive queries in distributed databases (IEEE trans knowledge and data engieneering, 1993) | ||
| - | |||
| - | **Deliverables**: | ||
| - | * Semantics of datalog; overview of known optimization strategies (document) | ||
| - | * Description of the leapfrog trie join (document) | ||
| - | * Datalog system (software artifact) | ||
| - | * Experimental analysis of developped system on a number of use cases (document) | ||
| - | |||
| - | **Interested?** | ||
| - | * Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]] | ||
| - | |||
| - | **Status**: available | ||
| - | |||
| - | |||
| - | |||
| - | =====Publishing and Using Spatio-temporal Data on the Semantic Web===== | ||
| - | |||
| - | |||
| - | [[http://www.w3c.org/|RDF]] is the [[http://www.w3c.org/|W3C]] proposed framework for representing information | ||
| - | in the Web. Basically, information in RDF is represented as a set of triples of the form (subject,predicate,object). RDF syntax is based on directed labeled graphs, where URIs are used as node labels and edge labels. The [[http://linkeddata.org/|Linked Open Data]] (LOD) initiative is aimed at extending the Web by means of publishing various open datasets as RDF, setting RDF links between data items from different data sources. Many companies and government agencies are moving towards publishing data following the LOD initiative. | ||
| - | In order to do this, the original data must be transformed into Linked Open Data. Although most of these data are alphanumerical, most of the time they contained a spatial or spatio-temporal component, that must also be transformed. This can be exploited | ||
| - | by application providers, that can build attractive and useful applications, in particular, for devices like mobile phones, tablets, etc. | ||
| - | |||
| - | The goals of this thesis are: (1) study the existing proposals for mapping spatio-temporal data into LOD; (2) apply this mapping to a real-world case study (as was the case for the [[http://www.oscb.be/|Open Semantic Cloud for Brussels]] project; (3) Based on the produced mapping, and using existing applications like the [[http://linkedgeodata.org/|Linked Geo Data project]], build applications that make use of LOD for example, to find out which cultural events are taking place at a given time at a given location. | ||
| - | |||
| - | |||
| - | * Contact: [[ezimanyi@ulb.ac.be|Esteban Zimányi]] | ||
| - | |||
| - | =====Extending SPARQL for Spatio-temporal Data Support===== | ||
| - | |||
| - | [[http://www.w3.org/TR/rdf-sparql-query/|SPARQL]] is the W3C standard language to query RDF data over the semantic web. Although syntactically similar to SQL, SPARQL is based on graph matching. In addition, SPARQL is aimed, basically, to query alphanumerical data. | ||
| - | Therefore, a proposal to extend SPARQL to support spatial data, called [[http://www.opengeospatial.org/projects/groups/geosparqlswg/|GeoSPARQL]], has been presented to the Open Geospatial Consortium. | ||
| - | |||
| - | In this thesis we propose to (1) perform an analysis of the current proposal for GeoSPARQL; (2) a study of current implementations of SPARQL that support spatial data; (3) implement simple extensions for SPARQL to support spatial data, and use these language in real-world use cases. | ||
| - | |||
| - | * Contact: [[ezimanyi@ulb.ac.be|Esteban Zimányi]] | ||
| - | |||