TUWien - ASE Summer 2015: Engineering human-based services in elastic systems

Engineering human-based services in
elastic systems
Hong-Linh Truong
Distributed Systems Group,
Vienna University of Technology
truong@dsg.tuwien.ac.at
http://dsg.tuwien.ac.at/staff/truong
1ASE Summer 2015
Advanced Services Engineering,
Summer 2015 – Lecture 9
Advanced Services Engineering,
Summer 2015 – Lecture 9

Outline
 Human service units
 Provisoning and employing human sevice units
– frameworks
 Human service units in Vienna Elastic
Computing Model (VIECOM)
 Evaluating human services
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Scenario
3
Offers services for
handling IoT Data
Offers services for
handling IoT Data
Offers services for big,
data analytics
Offers services for big,
data analytics
Offers services for
complex problem solving
using human experts
Offers services for
complex problem solving
using human experts
IoT Cloud Platform
Data Analytics
Platform
Expert Provisioning
Platform
Sensors
<<send data>>
<<analyze data>> <<notify possible
problem>>
<<control/configure
sensors>>
Predictive maintenance companyPredictive maintenance company
<<monitor>>
Chillers
<<predict and solve
problems>>
<<control
services>>
<<control
algorithms>>
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Near-Realtime
Data Analytics
Offline Data
Analytics CloudLyra
Integrated systems of software, things
and people services
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Sensors
NoSQL BigData
Sensor
data
Gateways
EventHandling Web
ServiceLoad
Balancer
MOM
Sensor
data
Cloud-based M2M Platform
Control Analysis Configuration
control, analyze,deploy
COMOT – Elasticity ManagementPlatform
critical situation msg
Smart
Communication
Collective Provisioning
External
Service
task
forms
elasticitiy control/management msg
critical
situation msg
critical
situation
msg critical situation
msg/task
clasticity control/management msg;
task
HDA-CAS
Human Interface
(Mobile, Mail, Web)
Human-based
Services
execute/manage

Human-based services for solving
complex problems (2)
5
But how to program human-based services and
software-based services together?
But how to program human-based services and
software-based services together?
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Example: some common tasks in
data analytics
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Human activities in Data Analytics
Labeling
Annotating
Cleansing
Evaluating
data/content
Dectecting
patterns
Classifying
objects
Steering
analytics

Human service units in data
analytics -- functions
 Evaluating: is the quality of picture good?
 Classifying: is it a man‘s or a woman‘s picture?
 Decting: any unidentified object in a picture?
 Labeling: adding location information of a picture
 Cleansing: remove duplicated pictures
 Steering: the quality of picture is bad, should we
continue to merge it with others?
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How to model such functions for human units ?
E.g., with WSDL or REST?
How to model such functions for human units ?
E.g., with WSDL or REST?

HUMAN SERVICE UNITS
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Human service units
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Human
service unit
Human
service unit
Functions
Non-
functional
parameters
Service
models
Technical
interfaces
Provisioning
mechanisms
Interaction
models
Human acting as a „service unit“Human acting as a „service unit“

Human service units
10
Modeling type of
units (e.g.,
computation, data,
monitor,) and their
dependencies
Consumption,
ownership, provisioning,
price, etc.
Elastic
Service
Unit
Service
model
Unit
Dependency
Elastic
Capability
Function
The functional
capability of the unit
and interface to
access the function
Capabilities to be elastic
under different
requirements
SoftwareSoftware PeoplePeople
VolunteersProfessionals
ThingThing
Resources
ASE Summer 2015

Forms of human service
 Individual Compute Unit
 An individual is treated like „a processor“ or “functional
unit“. A service can wrap human capabilities to support
the communication and coordination of tasks
 Social Compute Unit
 A set of people and software that are initiated and
provisioned as a service for solving tasks
 Web services interfaces can be built
 Different pricing models and different
quality models
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Human service units – provisioning
mechanisms (1)
 An infrastructure can be introduced for
accessing many ICUs in a crowd
 Allow people to register their service unit capabilities
 Facilitate communication, task bidding, retrieval and
result delivery
 Act like a marketplace: multiple providers and multiple
consumers
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ICU ICU
ICUICU
ICU
ICU ICU
CrowdCrowd

mechanisms (2)
 An „infrastructure-as-a-service“ for ICUs
 Facilitate communication, task retrieval and result
delivery
 Single ICUaaS provider and multiple consumers
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ICU ICU
ICUICU
ICU
ICU ICU
Cloud
provisioning
models ICUICU

mechanisms (3)
 An „infrastructure-as-a-service“ for SCUs
 Facilitate communication, task retrieval and result
delivery
 Single SCUaaS provider and multiple consumers
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SCU SCU
SCUSCU
SCU
SCU SCU
Cloud
provisioning
models SCUSCU

Human service units – technical
interfaces (1)
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People
Web Servicce
(REST/SOAP)
People
Web page
Analytics
Activity
Analytics
Activity

Human service units – technical
interfaces (2)
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Email/SMS/Instant
Messaging
People
Web page
Web Servicce
(REST/SOAP)
Communication
Services
People
Analytics
Activity
Analytics
Activity

Human service units – interaction
model
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ICU/SCU
Task queue
Scheduler
ICU/SCU
Task queue
Scheduler
Analytics
Activity
Analytics
Activity
ICU/SCU
Analytics
Activity

Human service units -- NfPs
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Which are important
considerations when
interpreting non-functional
properties for human service
units?
Which are important
considerations when
interpreting non-functional
properties for human service
units?

Incorporating human units into
complex processes
 How to provision and employ human compute
units?
 How to select human units?
 Where to place human units in data analytics
and why?
 How to monitor and test human units in data
analytics?
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PROVISIONING AND
EMPLOYING HUMAN SERVICE
UNITS-- SOME FRAMEWORKS
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Qurk system architecture (1)
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Source: Adam Marcus, Eugene Wu, David Karger, Samuel Madden, and Robert Miller. 2011. Human-powered sorts and joins. Proc. VLDB
Endow. 5, 1 (September 2011), 13-24.
Endow. 5, 1 (September 2011), 13-24.

Qurk system architecture (2)
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Endow. 5, 1 (September 2011), 13-24.
Endow. 5, 1 (September 2011), 13-24.

Jabberwocky approach (1)
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Source: Salman Ahmad, Alexis Battle, Zahan Malkani, Sepandar D. Kamvar: The jabberwocky programming environment for structured
social computing. UIST 2011: 53-64

Jabberwocky approach (2)
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Automan approach
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Source: Daniel W. Barowy, Charlie Curtsinger, Emery D. Berger, Andrew McGregor: AutoMan: a platform for integrating human-based
and digital computation. OOPSLA 2012: 639-654
Source: Daniel W. Barowy, Charlie Curtsinger, Emery D. Berger, Andrew McGregor: AutoMan: a platform for integrating human-based
and digital computation. OOPSLA 2012: 639-654

SW4H approach (1)
ASE Summer 2015 26
Karastoyanova, Dimka; Dentsas, Dimitrios; Schumm, David; Sonntag, Mirko; Sun, Lina; Vukojevic, Karolina: Service-based Integration of
Human Users in Workflow-driven Scientific Experiments. In: Proceedings of the 8th IEEE International Conference on eScience (eScience
2012
Karastoyanova, Dimka; Dentsas, Dimitrios; Schumm, David; Sonntag, Mirko; Sun, Lina; Vukojevic, Karolina: Service-based Integration of
Human Users in Workflow-driven Scientific Experiments. In: Proceedings of the 8th IEEE International Conference on eScience (eScience
2012

SW4H approach (2)
 Similar concepts in
collaborative working
environments but
integrated into
workflows
 Do not discuss about
where and how to
select human units
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Karastoyanova, Dimka; Dentsas, Dimitrios; Schumm,
David; Sonntag, Mirko; Sun, Lina; Vukojevic, Karolina:
Service-based Integration of Human Users in Workflow-
driven Scientific Experiments. In: Proceedings of the 8th
IEEE International Conference on eScience (eScience
2012
Karastoyanova, Dimka; Dentsas, Dimitrios; Schumm,
David; Sonntag, Mirko; Sun, Lina; Vukojevic, Karolina:
Service-based Integration of Human Users in Workflow-
driven Scientific Experiments. In: Proceedings of the 8th
IEEE International Conference on eScience (eScience
2012

HUMAN SERVICE UNITS IN
VIENNA ELASTIC COMPUTING
MODEL
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VieCOM -- incorporate humans into a
programming paradigm (1)
• Abstracting human compute units as program elements
• Extending programming languages to support human
compute units
• Data/control flows via extensible APIs
Programming
languages
• Shared memory (e.g., human –software – human),
message passing (human-to-human), artifact-centric,
etc., via APIs working atop the compute unit abstraction
layer
Multiple
programming
models
• Computing capability /profile management: human
computing power, reputation and incentive models
• Monitoring and enforcing incentives/rewards, quality of
results, availability
• Communication between human-middleware, among
Individual Compute Units (SCU)/Social Compute Units
(SCU) for exchanging artifacts and comprehensing l tasks
Execution
environment
29 http://dsg.tuwien.ac.at/research/viecomASE Summer 2015

VieCOM-- incorporate humans into a
programming paradigm (2)
Volunteers ProfessionalsTeamIndividual
Service-based Middleware
CommunicationCommunicationMonitoringMonitoring
Capability/Profile
Management
Capability/Profile
Management
Provisioning/Negotiation/Execution APIProvisioning/Negotiation/Execution API
Abstraction of Human-based Compute Units
SCU
SC
U
SC
U SCU SCU
Program languages and programming models
Program
elements
Software
Compute
Units
program human actions
and dependencies
program incentive condition
and rewarding action
program result evaluation
method
Human-to-middleware
interfaces:
•visualization of collective tasks
•embedding of common forms
•mobile app
30ASE Summer 2015

Cloud of hybrid service units
Cloud of HBS: A cloud of HBS includes HBS that can be
provisioned, deployed, and utilized on-demand based on
different pricing and incentive models.
Cloud of HBS: A cloud of HBS includes HBS that can be
provisioned, deployed, and utilized on-demand based on
different pricing and incentive models.
Cloud of hybrid services: A cloud of hybrid services
includes SBS and HBS that can be provisioned, deployed
and utilized on-demand based on different pricing and
incentive models.
Cloud of hybrid services: A cloud of hybrid services
includes SBS and HBS that can be provisioned, deployed
and utilized on-demand based on different pricing and
incentive models.
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Hybrid compute unit design –
fundamental elements
32ASE Summer 2015
Hong-Linh Truong, Hoa Khanh Dam, Aditya Ghose, Schahram Dustdar "Augmenting Complex Problem Solving with
Hybrid Compute Units",9th International Workshop on Engineering Service-Oriented Application (WESOA's 2013), In
conjunction with ICSOC 2013, Dec 2, 2013, Berlin, Germany, (c)Springer-Verlag
Hong-Linh Truong, Hoa Khanh Dam, Aditya Ghose, Schahram Dustdar "Augmenting Complex Problem Solving with
Hybrid Compute Units",9th International Workshop on Engineering Service-Oriented Application (WESOA's 2013), In
conjunction with ICSOC 2013, Dec 2, 2013, Berlin, Germany, (c)Springer-Verlag

Hybrid compute unit design --
Relationships
33
Relationship Type HBS SBS TBS HCU
Similarity Yes Yes Yes Yes
Composition Yes Yes Yes Yes
Data Dependency Yes Yes Yes Yes
Control Dependency Yes Yes Yes Yes
Location Dependency Yes Yes Yes Yes
Forwarding Yes Yes No Yes
Delegation Yes Yes No Yes
Social Relation Yes No No Yes
Elasticity Yes Yes No Yes
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Hybrid compute units
34
Hybrid compute unit (HCU): a set of service units
includes software-based services, human-based
services and things-based services that can be
provisioned, deployed and utilized as a collective
on-demand based on different quality, pricing and
incentive models.
Hybrid compute unit (HCU): a set of service units
includes software-based services, human-based
services and things-based services that can be
provisioned, deployed and utilized as a collective
on-demand based on different quality, pricing and
incentive models.
ASE Summer 2015

 Extensible architecture
 Adapters for: email,
Dropbox, REST,
Android
 Integrated with
WP4,6,8;
API access for WP5,2
 Open source and
documentation:
 https://github.com/tuwi
endsg/SmartCom
ASE Summer 2015 35
P. Zeppezauer, O. Scekic, H.-L. Truong and S. Dustdar, "Virtualizing Communication for Hybrid and Diversity-Aware Collective Adaptive Systems,"
10th International Workshop on Engineering Service-Oriented Applications (WESOA'14@ICSOC), Paris, 2014.
Zeppezauer, Virtualizing Communication for Hybrid and Diversity-aware Collective Adaptive Systems, Master thesis, Dec 2014.
P. Zeppezauer, O. Scekic, H.-L. Truong and S. Dustdar, "Virtualizing Communication for Hybrid and Diversity-Aware Collective Adaptive Systems,"
10th International Workshop on Engineering Service-Oriented Applications (WESOA'14@ICSOC), Paris, 2014.
Zeppezauer, Virtualizing Communication for Hybrid and Diversity-aware Collective Adaptive Systems, Master thesis, Dec 2014.
Highlights: Virtualizing Communication

Specifying and controling elasticity
of human-based services
What if we need to
invoke a human?
#predictive maintanance analyzing chiller measurement
#SYBL.ServiceUnitLevel
Mon1 MONITORING accuracy = Quality.Accuracy
Cons1 CONSTRAINT accuracy < 0.7
Str1 STRATEGY CASE Violated(Cons1):
Notify(Incident.DEFAULT, ServiceUnitType.HBS)
#predictive maintanance analyzing chiller measurement
#SYBL.ServiceUnitLevel
Mon1 MONITORING accuracy = Quality.Accuracy
Cons1 CONSTRAINT accuracy < 0.7
Str1 STRATEGY CASE Violated(Cons1):
Notify(Incident.DEFAULT, ServiceUnitType.HBS)
ASE Summer 2015 36

Utilizing hybrid services for
evolving/dependent task graphs
Hong-Linh Truong, Schahram
Dustdar, Kamal Bhattacharya
"Programming Hybrid Services
in the Cloud", 10th International
Conference on Service-oriented
Computing (ICSOC 2012),
November 12-16, 2012, Shanghai,
China. Best Paper Award.
Hong-Linh Truong, Schahram
Dustdar, Kamal Bhattacharya
"Programming Hybrid Services
in the Cloud", 10th International
Conference on Service-oriented
Computing (ICSOC 2012),
November 12-16, 2012, Shanghai,
China. Best Paper Award.
ASE Summer 2015 37

Elastic SCU provisioning atop ICUs
Elastic profile
SCU (pre-)runtime/static formation
Cloud APIs
Muhammad Z.C. Candra, Hong-Linh Truong, and Schahram
Dustdar, Provisioning Quality-aware Social Compute Units in
the Cloud, ICSOC 2013.
Muhammad Z.C. Candra, Hong-Linh Truong, and Schahram
Dustdar, Provisioning Quality-aware Social Compute Units in
the Cloud, ICSOC 2013.
Algorithms
 Ant Colony
Optimization
variants
 FCFS
 Greedy
SCU
extension/reduction
 Task reassignment
based on trust, cost,
availability
Mirela Riveni, Hong-Linh Truong, and Schahram
Dustdar, On the Elasticity of Social Compute Units,
CAISE 2014
Mirela Riveni, Hong-Linh Truong, and Schahram
Dustdar, On the Elasticity of Social Compute Units,
CAISE 2014
ASE Summer 2015 38

Selecting human units
 Do not select at all
 Let human units bid the tasks
 E.g., in crowdsourcing platforms
 Static/fix mapping
 E.g., using static information for human-task mapping
 Simple selection techniques
 Using the requirement of the task to find the suitable
human units based on their capabilities
 Complex selection techniques
 Utilizing complex dependency graphs to find suitable
human units
ASE Summer 2015 39

Selecting SCU based on task
graphs
40
SCU Formation
Algorithms
Business As
Usual
Corrective
Action
HBS
Constraints
Hong Linh Truong, Schahram Dustdar, Kamal Bhattacharya: Programming Hybrid Services in the Cloud. ICSOC 2012: 96-110Hong Linh Truong, Schahram Dustdar, Kamal Bhattacharya: Programming Hybrid Services in the Cloud. ICSOC 2012: 96-110
ASE Summer 2015

Placement techniques for human
units
 Usually at design time the developer/designer decides
 Where to put human units
 Where some triggers should be put in order to invoke
human units if needed
 At runtime
 Find suitable human units
 Invoke human units
 Placement of human units
 Application-specific
 Needs automatic algorithms and supporting tools
ASE Summer 2015 41

Configuring iSCU
 Establish „connectedness“ based on compliance
constraints and network topology
 Addional cost might occur!
 Program SBS and HBS for the iSCU to have a
complete working environment.
 Different connectedness
 E.g., ring-based, star-based, and master-slave
topologies
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Towards programming framework
for HCU
43
Coordination and
Composition Models
Coordination and
Composition Models
[ICSOC12]
ASE Summer 2015

EVALUATING HUMAN
SERVICES
ASE Summer 2015 44

Turkalytics
 Develop „Interaction
Model“ for human
activities
 Monitor and analyze
metrics, e.g.,
performance and
location
ASE Summer 2015 45
Paul Heymann and Hector Garcia-Molina. 2011. Turkalytics: analytics for human computation. In Proceedings of the 20th international
conference on World wide web (WWW '11). ACM, New York, NY, USA, 477-486. DOI=10.1145/1963405.1963473
http://doi.acm.org/10.1145/1963405.1963473
http://doi.acm.org/10.1145/1963405.1963473

Turkalytics
 Track client
detail at client
side (in browser)
 Store tracked
information in a
log server
 Analyze events
ASE Summer 2015 46
http://doi.acm.org/10.1145/1963405.1963473
http://doi.acm.org/10.1145/1963405.1963473

VieCOM
 SCU execution model and lifecycle
management
 Metrics for ICUs and SCUs
Mirela Riveni, Hong-Linh Truong, and Schahram Dustdar, On the Elasticity of Social Compute
Units, CAISE 2014
Mirela Riveni, Hong-Linh Truong, and Schahram Dustdar, On the Elasticity of Social Compute
Units, CAISE 2014
ASE Summer 2015 47

Exercises
 Read mentioned papers
 Analyze pros and cons of existing frameworks
for data analytics
 Survey existing algorithms for matching human
units to data analytics tasks
 Examine requirements for locating places for
human units and implement some algorithms
 Examine monitoring techniques for cloud of
human compute units
ASE Summer 2015 48

49
Thanks for
your attention
Hong-Linh Truong
Distributed Systems Group
Vienna University of Technology
truong@dsg.tuwien.ac.at
http://dsg.tuwien.ac.at/staff/truong
ASE Summer 2015

TUWien - ASE Summer 2015: Engineering human-based services in elastic systems

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