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teaching:mfe:is [2016/04/13 17:27]
msakr [Assessing Existing Communication Protocols In The Context Of DAAS]
teaching:mfe:is [2019/05/13 11:30]
mahmsakr [Mobility data exchange standards]
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-====== MFE 2016-2017 : Web and Information Systems ======+====== MFE 2019-2020 : Web and Information Systems ======
  
 ===== Introduction ===== ===== Introduction =====
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 ===== 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 [[https://​research.euranova.eu/​wp-content/​uploads/​proposals-thesis-2019.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.
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   * 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.+===== Dynamic Query Processing on GPU Accelerators =====
  
-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.+This master thesis is put forward in the context ​of the DFAQ Research Project: "​Dyanmic Processing of Frequently Asked Queries",​ funded by the Wiener-Anspach foundation.
  
-**Validation of the approach** Validation of the proposed interpreter/​compiler should be done on two levels: +Within this project, our lab is hence developing novel ways for processing ​"fast Big Data", i.e., processing of analytical queries where the underlying data is constantly ​being updated. The analytics problems envisioned cover wide areas of computer science and include database aggregate ​queries, probabilistic inference, matrix chain computation, and building statistical models.
-  * 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 +The objective ​of this master thesis ​is to build upon the novel dynamic ​processing ​algorithms being developed in the lab, and complement these algorithms by proposing dynamic ​evaluation ​algorithms that execute on modern GPU architecturesthereby exploiting their massive parallel processing capabilities.
-  * 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 compilerand analysis of the results.+
  
-**Interested?​** +Since our current development is done in the Scala programming language, prospective students should either know Scala, or being willing to learn it within the context of the master thesis.
-  * Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]]+
  
-**Status**: available 
  
 +**Validation of the approach** Validation of master thesis'​ work should be done on two levels:
 +  * a theoretical level; by proposing and discussing alternative ways to do incremental computation on GPU architectures,​ and comparing these from a theoretical complexity viewpoint
 +  * an experimental level; by proposing a benchmark collection of CEP queries that can be used to test the obtained versions of the interpreter/​compiler,​ and report on the experimentally observed performance on this benchmark.
  
-===== 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 graphin 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 problemwe 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.+**Deliverables** ​of the master thesis project 
 +  * An overview ​of query processing on GPUs 
 +  * A definition of the analytics queries under consideration 
 +  * A description of different possible dynamic evaluation algorithms for the analytical queries on GPU architectures. 
 +  * theoretical comparison ​of these possibilities 
 +  * The implementaiton of the evaluation algorithm(s) (as an interpreter/​compiler) 
 +  * A benchmark set of queries and associated data sets for the experimental validation 
 +  * An experimental validation ​of the compilerand analysis ​of the results.
  
-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]]+**Interested?​** Contact :  [[svsummer@ulb.ac.be|Stijn Vansummeren]] 
  
 **Status**: available **Status**: available
  
-===== A Scala-based runtime and compiler for Distributed Datalog ​=====+===== Multi-query Optimization in Spark =====
  
-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 applicationsmost notably on the webas well as do inference on the semantic webThe goal of this thesis is to engineer ​basic **distributed ​datalog system**, i.e., system that is capable of compiling & running ​distributed datalog queriesThe system should be implemented in the Scala programming language. Learning Scala is part of the master thesis project.+Distributed computing platforms such as Hadoop and Spark focus on addressing the following challenges ​in large systems: (1) latency(2) scalabilityand (3) fault toleranceDedicating computing resources for each application executed by Spark can lead to a waste of resources. Unified ​distributed ​file systems such as Alluxio has provided ​platform for computing results among simultaneously ​running ​applicationsHowever, it is up to the developers to decide on what to share.
  
-The system should: +The objective of this master thesis is to optimize various applications running on a Spark platformoptimize their execution plans by autonomously finding sharing opportunities,​ namely finding ​the RDDs that can be shared among these applications,​ and computing these shared plans once instead of multiple times for each query.
-  * 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 ​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, ...)+**Deliverables** ​of the master thesis project 
 +  ​An overview of the Apache Spark architecture. 
 +  ​Develop ​performance model for queries ​executed by Spark. 
 +  * An implementation ​that optimizes queries executed by Spark and identify sharing opportunities. 
 +  * An experimental validation ​of the developed ​system.
  
-**Required reading**:​ +**Interested?​** Contact :  [[svsummer@ulb.ac.be|Stijn Vansummeren]]
-  * 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 **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.
  
-=====Publishing and Using Spatio-temporal Data on the Semantic Web=====+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]]
  
-[[http://​www.w3c.org/​|RDF]] is the [[http://​www.w3c.org/​|W3C]] proposed framework for representing information +**Status**available
-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===== =====Extending SPARQL for Spatio-temporal Data Support=====
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    * Contact: [[ezimanyi@ulb.ac.be|Esteban Zimányi]]    * Contact: [[ezimanyi@ulb.ac.be|Esteban Zimányi]]
  
-=====Efficient Management of (Sub-)structure ​ Similarity Search Over Large Graph Databases. =====  
  
-The problem of (sub-)structure similarity search over graph data has recently drawn significant research interest due to its importance in many application areas such as in Bio-informaticsChem-informaticsSocial NetworkSoftware EngineeringWorld Wide WebPattern Recognitionetc ​Consider,​ for example, the area of drug designefficient techniques ​are required to query and analyze huge data sets of chemical molecules thus shortening ​the discovery cycle in drug design ​and other scientific activities+====== MFE 2019-2020 : Spatiotemporal Databases ====== 
 +Moving object databases ​(MODare database systems that can store and manage moving object ​data. A moving object is a value that changes over time. It can be spatial (e.g.a car driving on the road network), or non-spatial (e.g.the temperature in Brussels). Using a variety of sensorsthe changing values of moving objects can be recorded in digital formats. A MODthenhelps storing and querying such data. A couple of prototypes have also been proposedsome of which are still active in terms of new releasesYeta mainstream system is by far still missing. Existing prototypes are merely research. By mainstream we mean that the development builds on widely accepted toolsthat are actively being maintained ​and developed. A mainstream system would exploit the functionality ​of these tools, and would maximize ​the reuse of their ecosystems. As a result, it becomes more closer to end users, ​and easily adopted in the industry.
  
-Graph edit distance ​is widely accepted as similarity measure ​of labeled graphs due to its ability to cope with any kind of graph structures ​and labeling schemes Todaygraph edit similarity plays significant role in managing graph data , and is employed in variety of analysis tasks such as graph classification ​and clusteringobject recognition in computer visionetc+In our group, we are building MobilityDB, a mainstream MOD. It builds on PostGIS, which is a spatial database extension ​of PostgreSQL. MobilityDB extends the type system ​of PostgreSQL ​and PostGIS with ADTs for representing moving object dataIt defines, for instancethe tfloat for representing ​time dependant float, and the tgeompoint for representing ​time dependant geometry point. MobilityDB types are well integrated into the platform, to achieve maximal reusability,​ hence a mainstream development. For instance, the tfloat builds on the PostgreSQL double precision type, and the tgeompoint build on the PostGIS geometry(point) type. Similarly MobilityDB builds on existing operationsindexingand optimization framework.
  
-In this master thesis project, ​ due to the hardness ​of graph edit distance ​(computing graph edit distance is known to be NP-hard problem), the student ​ will investigate the current approaches that deals with problem complexity while searching for similar (sub-)structures. ​ At the end, the student should be able to empirically analyze and contrast some of the interesting approaches +This is all made accessible via the SQL query interface. Currently MobilityDB is quite rich in terms of types and functions. It can answer sophisticated queries in SQL. The first beta version has been released as open source April 2019 (https://​github.com/​ULB-CoDE-WIT/​MobilityDB).
  
-=====A Generic Similarity Measure For Symbolic Trajectories===== +The following thesis ideas contribute to different parts of MobilityDBThey all constitute innovative developmentmixing both research ​and developmentThey hence will help developing ​the student skills ​in
-Moving object databases (MOD) are database systems that can store and manage moving object data. A moving object is a value that changes over time. It can be spatial (e.g., a car driving on the road network), or non-spatial (e.g., the temperature in Brussels). Using a variety ​of sensors, the changing values of moving objects can be recorded in digital formatsA MODthen, helps storing ​and querying such dataThere are two types of MOD. The first is the trajectory database, that manages the history of movement. The second type, in contrast, manages ​the stream of current movement ​and the prediction ​of the near futureThis thesis belongs to the first type (trajectory ​databases). The research ​in this area mainly goes around proposing data persistency models and query operations for trajectory data+  * Understanding ​the theory ​and the implementation ​of moving object databases. 
 +  * Understanding ​the architecture of extensible ​databasesin this case PostgreSQL. 
 +  * Writing open source software.
  
-A sub-topic of MOD is the study of semantic trajectories. It is motivated by the fact that the semantic of the movement is lost during the observation process. You GPS logger, for instance, would record a sequence of (lon, lat, time) that describe your trajectory. It won't, however, store the purpose of your trip (work, leisure, …), the transportation mode (car, bus, on foot, …), and other semantics of your trip. Research works have accordingly emerged to extract semantics from the trajectory raw data, and to provide database persistency to semantic trajectories. ​ 
  
-Recently, Ralf Güting et al. published a model called “symbolic trajectories”,​ which can be viewed as a representation of semantic trajectories:​ +=====JDBC driver for Trajectories===== 
-Ralf Hartmut Güting, Fabio Valdés, and Maria Luisa Damiani. 2015. Symbolic Trajectories. ACM Trans. Spatial Algorithms Syst. 12, Article 7 (July 2015), 51 pages. +An important, and still missingpiece of MobilityDB ​is Java JDBC driverthat will allow Java programs to establish connections with MobilityDB, and store and retrieve dataThis thesis is about developing such driverAs all other components ​of PostgreSQLits JDBC driver is also extensibleThis documentation gives good explanation ​of the driver ​and the way it can be extended: 
-A symbolic trajectory ​is a very simple structure composed of a sequence of pairs (time intervallabel). Soit is a time dependent label, where every label can tell something about the semantics of the moving object during its associated time interval. We think this model is promising because of its simplicity ​and genericness   +https://​jdbc.postgresql.org/​documentation/​head/​index.html 
- +It is also helpful ​to look at the driver ​extension ​for PostGIS: 
-The goal of this thesis is to implement ​similarity operator for symbolic trajectoriesThere are three dimensions ​of similarity in symbolic trajectories:​ temporal similarityvalue similarity, and semantic similaritySuch an operator should be flexible to express arbitrary combinations of them. It should accept ​pair of semantic trajectories ​and return a numerical value that can be used for clustering or ranking objects based on their similaritySymbolic trajectories are similar to time series, except that labels are annotated by time intervals, rather than time pointsWe think that the techniques of time series similarity can be adopted for symbolic trajectoriesThis thesis should assess that, and implement a similarity measure based on time series similarity. The implementation ​is required ​to be done as an extension ​to PostGIS. We have already implemented some temporal types and operations on top of PostGIS, where you can start from.  +https://​github.com/​postgis/​postgis-java
- +
-  +
-**Deliverables** of the master thesis project +
-  * Reporting on the state of art of semantic trajectory similarity measures. +
-  * Reporting on the state of art in time series similarity measures. +
-  * Assessing the application of time series similarity to symbolic trajectories. +
-  * Implementing symbolic trajectories on top of PostGIS. +
-  * Implementation and evaluating the proposed symbolic trajectory similarity operator  ​+
  
 +As MobilityDB build on top of PostGIS, the Java driver will need to do the same, and build on top of the PostGIS driver. Mainly the driver will need to provide Java classes to represent all the types of MobilityDB, and access the basic properties.  ​
  
 **Interested?​** **Interested?​**
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 **Status**: available **Status**: available
  
-=====Assessing Existing Communication Protocols In The Context Of DaaS =====  +=====Mobility data exchange standards===== 
-Data-as-a-Service (DAAS) is an emerging cloud model. The main offering of DaaS is to allow data producers/​owners ​to publish data services on the cloudThe idea of publishing ​data via a service interface is not newSOA protocols have enabled this long agoYetthese protocols were not developed with the cloud and the big data in mind. This is probably why the term DAAS has emergedIt marks the need for protocols and tools that enable big data exchange+Data exchange standards ​allow different software systems ​to integrate together. Such standards are essential in the domain of mobilityConsider for example the case of public transportation. Different vehicles (tram, metro, bus) come from different vendors, and are hence equipped with different location tracking sensors. The tracking software behind these vehicle use different ​data formatsThese software systems need to push real time information to different appsTo support the passengersfor example, there must be a mobile or a Web app to check the vehicle schedules ​and to calculate routes. This information shall also be open to other transport service providers and to routing appsThis is how google maps, for instance, is able to provide end to end route plans that span different means of transport  ​
  
-DAAS services need to exchange large amounts ​of data. Large here refers ​to large message sizelarge message count, or a combination of bothRESTful services, ​for instancecommunicate over HTTPwhich is not a good choice for communicating large messages/filesSOAP services are not bound to HTTPbut they introduce another overhead of requiring messages to be strictly formatted in XMLThis is why researchers started to reconsider older protocols like the BitTorrentand suggesting extension to existing protocols like the SOAP with Attachments+The goal of this thesis is to survey the available mobility data exchange standardsand to implement in MobilityDB import/​export functions for the relevant onesExamples ​for these standards are: 
 +  * GTFS statichttps://​developers.google.com/​transit/​gtfs/​ 
 +  * GTFS realtimehttps://developers.google.com/​transit/​gtfs-realtime/​ 
 +  * NeTEx statichttp://​netex-cen.eu/ 
 +  * SIRIhttp://www.transmodel-cen.eu/​standards/​siri/ ​  
 +  * More standards can be found on http://​www.transmodel-cen.eu/​category/​standards/​
  
-The topic of this thesis is to perform a comprehensive survey on the protocols data exchange, and assess their suitability for DAAS. A quantitative comparison of protocols need to be done, considering at least these two dimensions: (1) the protocol: SOAP, REST, BitTorrent, etc, and (2) the message: short inline, long inline, file. The assessment should be in terms of reliability,​ performance,​ and security. 
  
-**Deliverables** of the master thesis project 
-  * A report that reviews the state of art communication protocols. 
-  * Propose a tool for DAAS developers to choose the best protocol/s based on their application needs. Such a tool might also provide means of automatically switching between protocols on certain thresholds. 
-  * Experiments to assess the suitability of protocols for DAAS, and to compare between them. These experiments need to be repeatable, so that others can use them on their own datasets and configurations.  ​ 
  
 **Interested?​** **Interested?​**
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 **Status**: available **Status**: available
 +
 
teaching/mfe/is.txt · Last modified: 2020/09/29 17:03 by mahmsakr