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![Orchestrate sensor web
services
[Globiza09,Amundson06,Guinard10]
Expose Sensors as Web
Services
[Spiess06, Spiess07,Karnouskos10]
Extend process language
for sensors
[Meyer11,Sperner11]
Process based code
generation
[Caracas11a,Caracas11b]
RELATED WORK](https://image.slidesharecdn.com/stefano-thesisnoanim-160414080515/85/PhD-thesis-24-320.jpg)
![EVALUATION
OVERALL MODELLING
DEPLOYMENT IN CADIZ, SPAIN
Euro(K)
0
50
100
150
200
Wired traditional System WSN Only makeSense
0%
20%
40%
60%
80%
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Success Rates per Task (All Users, All Ta
[d5.4 makesense project]](https://image.slidesharecdn.com/stefano-thesisnoanim-160414080515/85/PhD-thesis-36-320.jpg)
![CROWDSOURCING
Crowd task
Task description
Workers
Task instances
Crowdsourcer Crowdsources or platform Worker(s)
Workers to be
rewarded ( )
Crowdsourcer or platform
Task
publication
Worker
pre-selection
Task
execution
Validation &
rewarding
“the practice of outsourcing a work to an undefined and large
network of people via an open call for contribution” [howe]](https://image.slidesharecdn.com/stefano-thesisnoanim-160414080515/85/PhD-thesis-39-320.jpg)
![BP & HUMANS
RELATED WORK
PARALLEL
COMPUTING
Crowdforge [Kittur11]
Turkomatic [Kulkarni 12]
Jabberwocky [Ahmad11]
[Brambilla11,Brambilla12,Schall2012,Skopik2011..]
PROCESS
COMPOSITION
CrowdWeaver [Kittur12]
CrowdLang [Minder11]
PROCEDURAL
PROGRAMMING
Turkit [Little10]
Automan [Barowy 11]](https://image.slidesharecdn.com/stefano-thesisnoanim-160414080515/85/PhD-thesis-45-320.jpg)
Uploaded byStefano Tranquillini
PhD thesis
The document discusses advancements in process modeling languages intended for distributed processes involving user interfaces, wireless sensor networks (WSNs), and crowdsourcing systems. Key goals include creating orchestration mechanisms for these processes, developing a unified modeling approach, and addressing challenges in integrating and executing applications across various platforms. Contributions include extensions to existing process languages and tools for design, deployment, and execution of complex actor-driven applications.
PhD thesis
- 1. Stefano Tranquillini MODELS ANDSYSTEMS FOR MANAGING SENSOR AND CROWD-ORIENTED PROCESSES ICT Phd School, University of Trento. 25.3.2014
- 2. GOAL Extend process modellinglanguages to support the design and execution of extended processes. Distributed. Need for orchestration. Internal logic. Process driven logics New type of actors. New type of applications. Lack of integration and unification. UIs WSN CROWD Process languages
- 3. GENERAL CONTRIBUTIONS Process languageextensions (for UIs, WSN, Crowd) Design tools. Runtime environments. Architecture and approach. Case studies.
- 4.
- 5. DISTRIBUTED UI ORCHESTRATION Mashup-likeapplications that require multiple pages, multiple users, and process support WORKFLOW MANAGEMENT SYSTEMS Support office automation processes Automatic generation of form-based user interfaces (UIs) WEB SERVICE ORCHESTRATIONS Integration at the application level No UI support at all WEB MASHUPS Integration at data, application, and UI level very simple applications (single page) STATE OF THE ART
- 6. GOAL To coordinate distributedUIs and WS by using a process logic to specify the orchestration of different UIs that are deployed and executed in a distributed fashion
- 7. GOAL To coordinate distributedUIs and WS by using a process logic to specify the orchestration of different UIs that are deployed and executed in a distributed fashion op dr wsdr opws
- 8. RESEARCH CHALLENGES Understanding howto componentize UIs and compose them into web applications Defining a logic that is able to orchestrate both UIs and web services Providing a language and tool for specifying distributed UI compositions Developing a runtime environment that is able to execute distributed UI and service compositions
- 9. BPEL4UI Process Activity Container Activity Catch Message Exchange Correlation Set Variable Partner Link Page Name Description TemplateURL UIEngineName isStartPage Actor Name PlaceHolder Name UI Component Name UI Type WSDL-UI Property Name Value Type Partner Link Type fault handlers accessible to contains rendered in has described by 0..N 1..1 0..N 1..1 1..N 1..1 1..1 1..1 0..N 1..1 0..N described by 0..N 1..1 0..N 0..N 0..N 0..N 1..N 0..N
- 10. Intra Page Distributed Web service DESIGN drdr dr op ws
- 11.
- 12.
- 13.
- 14. ARCHITECTURE UI engine client(web browser)UI engine client (web browser) BPEL4UI editor BPEL4UI Compiler BPEL engine UI engine server UI engine client (web browser) BPEL4UI BPEL SOAP web services Application developer Design time Deployment time Runtime HTML templates Users Layout and UI logic generator BPEL generator Comm. services generator Layout configurator UI partner link configurator UI page UI page
- 15. RESULTS patent EXPLOITATION PAPERS Distributed orchestrationof user interfaces. Information Systems 2012, Elsevier journal, Special Issue on BPM’10 Best Papers People to Services to UI: Distributed Orchestration of User Interfaces BPM’10 MarcoFlow: Modeling, Deploying and Running Distributed User Interface Orchestrations. BPM’10 DEMO
- 16. LESSONS LEARNED UI canbe orchestrated with a process language. Need for extensions (same abstraction). Design / Deploy / Execute is effective for new actors. IDEA: SAME APPROACH FOR WSN AND CROWD
- 17.
- 18. WSN Room: MOON CO2 Ventilation Temp Presence Few tomany Sensors & Actuators Autonomous Distributed Gateway WSNs are stand-alone systems, coded by highly skilled programmers “Networks of sensors and actuators able to interact with the physical environment”
- 19. SCENARIO ©"Graphitech" Temp CO2 Ventilation Presence Room: MOON CO2 Temp Presence Ventilation Humidity Room:MARS Process engine +-+ +-+ Reporting Management +-+ Booking 04 '12 APRIL '12 Secretary Convention Center Building Convention Center Information System
- 20. GOAL To support thecreation and execution of applications whose logic spans across the process and the network of sensors.
- 21. GOAL ©"Graphitech" Temp CO2 Ventilation Presence Room: MOON CO2 Temp Presence Ventilation Humidity Room:MARS Process engine +-+ +-+ Reporting Management +-+ Booking 04 '12 APRIL '12 Secretary bp wsn bp bp wsn bp To support the creation and execution of applications whose logic spans across the process and the network of sensors.
- 22. GOAL ©"Graphitech" Temp CO2 Ventilation Presence Room: MOON CO2 Temp Presence Ventilation Humidity Room:MARS Process engine +-+ +-+ Reporting Management +-+ Booking 04 '12 APRIL '12 Secretary bp wsn bp bp wsn bp To support the creation and execution of applications whose logic spans across the process and the network of sensors.
- 23. CHALLENGES Provide easy accessto WSN capabilities. Provide a set of modeling concepts to enable the specification of sensor network functionality Provide a unified modeling for WSN applications and the process. Create a tool and a language for the creation of process- driven WSN applications. Enable the hybrid execution.
- 24. Orchestrate sensor web services [Globiza09,Amundson06,Guinard10] ExposeSensors as Web Services [Spiess06, Spiess07,Karnouskos10] Extend process language for sensors [Meyer11,Sperner11] Process based code generation [Caracas11a,Caracas11b] RELATED WORK
- 25. IDEA Different types: splitthe design WSN + BP Deployment: create code for wsn + runnable process Execution We extend BPMN: BPMN4WSN WSN logic composition DESIGN FOR WSN Specific Constructs for internal WSN logic CO2 Temp Presence Ventilation Humidity Room: MARS wsn Process engine bp CO2 Temp Presence Ventilation Humidity Room: MARS wsn?
- 26. WSN MODELING Node WSN Operation Has WSN Task Represents Sense ActuateAggregate EoI Location Thing Has Covered by BPMN4WSN CO2 Ventilation AVG instanceof instanceof instanceof WSN Logic construct Has target Tell Report Collect Local WSN logic composition tell action report action local actioncollective action
- 27.
- 28. WSN INTERNAL LOGIC Room:Moon Read CO2 tell action report action collective action tell action report action collective action tell action report action collective action ?
- 29. WSN INTERNAL LOGIC Report:Stream Local: Read CO2 report action Read CO Room: Moon Read CO2 2 local action
- 30.
- 31. PROTOTYPE *in collaboration withSAP * report action local action
- 32. DESIGN Code executed bythe gateway.
- 33. SCRIPT TASK: SUBPROCESS CheckCO2 CO2Sensing (static:.., dynamic:..) Targeting (static and dynamic)
- 34.
- 35. ARCHITECTURE BPMN4WSN editor Process andWSN Logic compositions Application developer Design time WSN Logic Composition Process System developer System description BPMN4WSN Compiler Process engine Communication proxy Deployment time Runtime Process analysis End point generation Binary code Executable process WSNs Proxy configuration Binary code generation
- 36. EVALUATION OVERALL MODELLING DEPLOYMENT INCADIZ, SPAIN Euro(K) 0 50 100 150 200 Wired traditional System WSN Only makeSense 0% 20% 40% 60% 80% 100% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Success Rates per Task (All Users, All Ta [d5.4 makesense project]
- 37. RESULTS EXPLOITATION PUBLICATIONS makeSense: Real-worldBusiness Processes through Wireless Sensor Networks Conet 2013 Process-Based Design and Integration of Wireless Sensor Network Applications BPM2012 Towards business processes orchestrating the physical enterprise with wireless sensor networks ICSE2012 From Business Process Specifications to Sensor Network Deployments EWSN2012 makeSense: Easy Programming of Integrated Wireless Sensor Networks. EWSN2011
- 38.
- 39. CROWDSOURCING Crowd task Task description Workers Taskinstances Crowdsourcer Crowdsources or platform Worker(s) Workers to be rewarded ( ) Crowdsourcer or platform Task publication Worker pre-selection Task execution Validation & rewarding “the practice of outsourcing a work to an undefined and large network of people via an open call for contribution” [howe]
- 40.
- 41. CROWDSOURCING PROCESSES “the structuringof multiple crowd task and task instances" Not natively supported by current crowdsourcing processes. Load data ChooseN Assess quality Random3 Naive1 Assess quality Find best
- 42. CROWDSOURCING TACTICS Crowdsourcing Platformsimplement only one. bid tag picture MARKETPLACE design logo CONTEST code app AUCTION
- 43. GOAL To enable thecreation and execution of crowdsourcing processes and of custom crowdsourcing tactics. Load data ChooseN Assess quality Random3 Naive1 Assess quality Find best
- 44. RESEARCH CHALLENGES Understand howto specify tasks for the crowd and how these tasks can be combined into a process logic. Define modeling constructs for defining and configuring tasks executed by the crowd and to manage data. Define a modeling language that is able to orchestrate the crowd and other participants, such as web services. Provide a tool that enables the creation of crowd processes. Create a runtime environment.
- 45. BP & HUMANS RELATEDWORK PARALLEL COMPUTING Crowdforge [Kittur11] Turkomatic [Kulkarni 12] Jabberwocky [Ahmad11] [Brambilla11,Brambilla12,Schall2012,Skopik2011..] PROCESS COMPOSITION CrowdWeaver [Kittur12] CrowdLang [Minder11] PROCEDURAL PROGRAMMING Turkit [Little10] Automan [Barowy 11]
- 46. IDEA Combine process modellingand crowd tasks CROWDSOURCING PROCESSES We extend BPMN BPMN4Crowd CROWD TASK Specific constructs for crowd tasks Specify constructs and modeling paradigms of tactics CROWDSOURCING TACTICS Unified modelling paradigm. Deployment and execution Receive Result Validate Result Reward UserAssign taskCreate task Load data ChooseN Assess quality Random3 Naive1 Assess quality Find best Naive1
- 47. ARCHITECTURE services Crowd Computer BPMN Engine App,User and process data BPMN Process CroCo Crowd Human actors Crowd Process Compiler and Deployer Crowdsourcer BPMN4Crowd editor Web Editor Task pages search execute invoke do do Execute Crowdsourcer Design time Deployment time Runtime Task web pages
- 48. BPMN4CROWDProcess CrowdTask Tactic CrowdTask internal configurations Receive Result Validate Result Reward UserAssign task Vote Vote Vote Agreement + Createtask Load data ChooseN Assess quality Random3 Naive1 Assess quality Find best
- 49. MODELING PROCESSESProcess CrowdTask Tactic CrowdTask internal configurations Receive Result Validate Result Reward UserAssigntask Vote Vote Vote Agreement + Create task Load data ChooseN Assess quality Random3 Naive1 Assess quality Find best
- 50. BPMN4CROWD CROWDTASK Specific for theCrowd. Additional parameters: Description: In this task you have to identify .. User interface: http://ec2-aws.5234… Number of instances: 5 Deadline: 1M 0w 0d 0h 0m Validation: expert Reward: 0.5 $ Reward strategy: pay valid Naive1
- 51. BPMN4CROWD DATA OBJECT set ofsets Naive1
- 52. DATA TRANSFORMATION SPLIT DATASET Split Data Set MERGE DATA SET Merge Data Set INPUT OUTPUT TASK
- 53. DATA TRANSFORMATION SPLIT DATA STRUCTURE JOINDATA STRUCTURE Join Data Strucutre Split Data Strucutre INPUT OUTPUT TASK
- 54. DATA TRANSFORMATION FILTER DATA FilterData INPUT OUTPUT TASK
- 55.
- 56. MODELING TACTICSProcess CrowdTask Tactic CrowdTask internal configurations Receive Result Validate Result Reward UserAssigntask Vote Vote Vote Agreement + Create task Load data ChooseN Assess quality Random3 Naive1 Assess quality Find best
- 57. CROWDCOMPUTER Crowd engineTask manager Rewardmanager Crowd manager Plugin manager API interface Metadata Web services Payment services Crowd computer Quality manager Crowd Task definitionCrowdCS Platform Crowd Computer Specific task for the CroCo
- 58. TACTICS CrowdComputer Receive Result Retrive Task Definition Validate Result Reward User Assign Instance Set Instanceas expired Set remaining Instance as expired Create an Instance Worker task.read task.createInstance task.assignInstance (Crowd.preselect) task.storeResult task.updateInstance(expired) reward.give task.updateRemainingInstances(expired) task.stop task.start task.stopInstance quality.validate MARKETPLACE
- 59. TACTICS CONTEST Worker Retrive Task Definition Decide winner(s) Reward User(s)CollectResults CrowdComputer task.read task.start task.stopreward.givequality.validate Recive Result Check Preselection Set Instance as expired Remove the instance Collect Results Create an Instance task.createInstance task.assignInstance (Crowd.preselect) task.deleteInstance task.updateInstance(expired) task.storeResult task.update(contestStop)task.update(contestStart)
- 60. TACTICS AUCTIONCrowdComputer Receive Result Retrive Task Definition SetTask as expired Review Result Reward User Set Task as expired WorkerCrowd Check Bids task.read task.start task.updateInstance(expired) reward.givequality.validate task.storeResult task.stop Create Instance User.bid < Task.bid_level True Check Bids Check Preselection task.assignInstance Assign Instance Crowd.preselect task.createInstance
- 61. TACTICS MAILINGLIST Assign instance to User CreateInstance Receive Result Validate Result Reward User Set Instance as expired Collect Results Assign Tasks task.createInstance task.assignInstance task.storeResult reward.give task.updateRemainingInstances(expired) quality.validate CrowdComputer Assign Tasks Retrive Task Definition Set remaining Instance as expired Retrieve User List Worker Collect Results task.read task.start crowd.getList task.updateRemainingInstances(expired) task.stop
- 62. CONFIGURING TACTICS Process CrowdTask Tactic CrowdTask internal configurations Receive Result Validate Result Reward UserAssigntask Vote Vote Vote Agreement + Create task Load data ChooseN Assess quality Random3 Naive1 Assess quality Find best
- 63. TACTIC CONFIGURATIONS Expert Evaluate (expert) Accept Reject yes human task quality.update(no) quality.update(no) GoldData Accept Reject Check Gold data questions % correct answers > threshold machine task quality.update(yes) quality.update(no) Agreement Validate w3 Validate w2 Check Result (w1) Check Result (w2) Check Result (w3) w1.validation = w2.validation quality.update(w3.answer) quality.update(w2.answer) crowd task Collect Votes validation with avg Compute average crowd task machine task quality.update(avg) Vote
- 64. CONFIGURING TACTICS REWARD CANBE CONFIGURED Process CrowdTask Tactic CrowdTask internal configurations Receive Result Validate Result Reward UserAssign task Vote Vote Vote Agreement + Create task Load data ChooseN Assess quality Random3 Naive1 Assess quality Find best
- 65.
- 66. services Crowd Computer BPMN Engine App,User and process data BPMN Process CroCo Crowd Human actors Crowd Process Compiler and Deployer Crowdsourcer BPMN4Crowd editor Web Editor Task pages search execute invoke do do Execute Crowdsourcer Design time Deployment time Runtime Task web pages DESIGN A B C
- 67. services Crowd Computer BPMN Engine App,User and process data BPMN Process CroCo Crowd Human actors Crowd Process Compiler and Deployer Crowdsourcer BPMN4Crowd editor Web Editor Task pages search execute invoke do do Execute Crowdsourcer Design time Deployment time Runtime Task web pages COMPILE & EXECUTE A B C
- 68. services Crowd Computer BPMN Engine App,User and process data BPMN Process CroCo Crowd Human actors Crowd Process Compiler and Deployer Crowdsourcer BPMN4Crowd editor Web Editor Task pages search execute invoke do do Execute Crowdsourcer Design time Deployment time Runtime Task web pages COMPILE & EXECUTE
- 69.
- 70. RESULTS EXPLOITATION PUBLICATIONS Business Processesfor the Crowd Computer BPMS2 2013 Modeling and Enacting Flexible Crowdsourcing Processes To be submitted to TWEB WWW.CROWDCOMPUTER.ORG
- 71.
- 72. BEFORE Develop the logicof the applications Create a platform that is able to support the execution Deploy and generate the code and the communication channels ! High-level modeling languages Architecture that supports the design, deployment, and execution of extended processes Automated system for the code generation and deployment of processes and of the actor logic. ! ! we simplified the creation of process-driven application logic but the intrinsic complexity of the new actors cannot be completely eliminated Process-driven logics, hence process languages. Focus on process modellers & skilled developers. Domain-specific components as the core. LESSON LEARNED & LIMITATIONS AFTER
- 73. FUTURE WORK WSN Multiple processes Easecomposition of WSN CROWD Creation of task UIs Support for platforms Extend the languages for new requirements Further user studies Release and improve the code and toolchains CONTRIBUTIONS Modeling languages to design distributed UI, sensor, and crowd-oriented processes. We contributed with a set of extensions for existing process languages, components to abstract the actors’ capabilities, and with tools that support the design, deployment and execution.
- 74. WWW.CROWDCOMPUTER.ORG Business Processes forthe Crowd Computer BPMS2 2013 Modeling and Enacting Flexible Crowdsourcing Processes To be submitted to TWEB makeSense: Real-world Business Processes through Wireless Sensor Networks Conet 2013 Process-Based Design and Integration of Wireless Sensor Network Applications BPM2012 Towards business processes orchestrating the physical enterprise with wireless sensor networks ICSE2012 From Business Process Specifications to Sensor Network Deployments EWSN2012 makeSense: Easy Programming of Integrated Wireless Sensor Networks. EWSN2011 Distributed orchestration of user interfaces. Information Systems 2012, Elsevier journal, Special Issue on BPM’10 Best Papers People to Services to UI: Distributed Orchestration of User Interfaces BPM’10 MarcoFlow: Modeling, Deploying and Running Distributed User Interface Orchestrations. BPM’10 DEMO Stefano Everythingshouldbemadeassimpleaspossible,but nosimpler.(A.E.) THANKS ANY QUESTIONS?
- 76.