1. C OORDINATING SERVICES FOR ACCESSING AND PROCESSING DATA IN DYNAMIC ENVIRONMENTS http://optimacs.imag.fr

2. D YNAMIC ENVIRONMENT 2  Consists of services, servers and devices that can be static or nomad  Data producers provide data  on demand (e.g., online applications, Web-hosted DBMS)  continuously – streams-- (e.g., messaging systems, mobile devices)  Data are hidden behind services  export API through heterogeneous networks  provide functions for retrieving and processing data “modern data and services intensive systems” deployed in dynamic environments

3. Give me five cinemas with available seats, located less than 3 Km from my current position and that are showing 3 – 5 stars movies released within the last 10 days Q UERYING IN DYNAMIC ENVIRONMENTS  Is spatio-temporal or not  Consumes on demand data or streams from static or nomad data services  Is evaluated continuously and in batch 3

4. V ISION : SERVICE COORDINATION FOR OPTIMALLY QUERYING DATA 4 geoLocate()dist([(x 1,y 1,z 1), (x 2,y 2,z 2 )],3) getfilms(3-5, 10) onScreen(film) showLocation() Give me five cinemas with available seats, located less than 3 Km from my current position and that are showing 3 – 5 stars movies released within the last 10 days ⋈ ⋈ filter(list, 5) GetMy Location GetMy Location Look4films filter(list,10 days) OnScreen Correlate Compute Distance Compute Distance Locate Theatres Locate Theatres Temporal Filter Temporal Filter Generate Map Generate Map Filter

5. geoLocate() dist([(x 1,y 1,z 1), (x 2,y 2,z 2 )],3) getfilms(3-5, 10) onScreen(film) showLocation() ⋈ ⋈ filter(list, 5) filter(list,10 days) V ISION : SERVICE COORDINATION FOR OPTIMALLY QUERYING DATA 5 OnScreen GetMy Location GetMy Location Look4films Correlate Compute Distance Compute Distance Locate Theatres Locate Theatres Temporal Filter Temporal Filter Generate Map Generate Map Filter

6. A SPECTS TO CONSIDER 6  Data providers are services  Export an API and are accessible through a lookup service  Few information about data produced: pivot data model for exchanging data  Autonomy  QoS properties: pertinence (semantic, geographic, temporal, provenance)  Data consumers  Express their data requirements (language)  Consume data continuously or on demand  Nomad/static  Execution context  Ubiquitous  Dynamic: resources availability change all the time  Heterogeneous devices: different physical and computing capacities

7. Services coordination for evaluating hybrid queries  Combine service composition and query evaluation  Optimize hybrid queries according to quality of service criteria  Propose a testbed for validating query evaluation based on service coordination within « real » dynamic environments No off-the-shelf DBMS for evaluating different types of queries C HALLENGES 7

8. O BJECTIVES 8 Efficient and adaptable evaluation of hybrid queries in service oriented environments  Propose an adaptable hybrid query evaluation process and associated mechanisms  Propose QoS based optimization techniques for hybrid queries  Design and implement a benchmark and testbed for dynamic environments

9. Q UERY WORKFLOW  Expressed in a CQL-Like declarative language  Implemented by a service coordination: query workflow 9 IAAS SAAS PAAS Computing services Computing services Storage services Data services π π σ σ ⋈ ⋈ σ σ

10. I MPLEMENTATION ISSUES 10 IAAS PAAS SAAS Scheduler 〈 outTuple(s) 〉 inputOp 1 () CQL-Like expression workflow activity C OMPUTING SERVICES D ATA SERVICES D EVICES D ATASPACE M OBILE Q H YPATIA

11. W HAT ’ S NEXT ? 11  Optimization approach: multi-objective combinatory problem  Problem expression on an inference engine  State of the art of workflow optimization  QoS measures computing and definition of multi-dimensional cost functions  Observation and QoS measures computing mechanism  Extension of the testbed D ATASPACE  Testing of hybrid query evaluation with QoS  Benchmark definition for measuring large scale hybrid query evaluation  Extend and validate scenarios  Validate the benchmark

12. http://optimacs.imag.fr C OORDINATING SERVICES FOR ACCESSING AND PROCESSING DATA IN DYNAMIC ENVIRONMENTS 12 Gracias

13. D ATA SERVICES 13  Discrete data or continuous data providers  Export API and properties  Methods are tagged with the result production rate profile@facebook coordinates@latitude profile: email  person Suscribe: email  coordinates(email,coor)

14. C OMPUTING SERVICES  Simple: only one service method call executed within the activity  Composite: multiple service methods calls in activities organized as a workflow 14 Similarity Wordnet Aggregation Caching HT Search engine