collective adaptation in process-based systems

Service Oriented Applica0ons (SOA) Unit

Collective Adaptation in Process-based Systems

Antonio Bucchiarone, C. Mezzina, M. Pistore, H. Raik, and G. Valetto

SASO 2014 8-12 September 2014, London, UK

Fondazione Bruno Kessler, Trento – Italy [email protected]

SASO 2014 Collective Adaptation in Process-based Systems 2

Collec0ve Adap0ve Systems

Diversity and Autonomicity En00es with diverse goals, preferences and autonomous decision making. Collec4veness and Conflicts §  Collabora0on between en00es to fulfill goals. §  Conflic0ng goals of en00es at different levels. Dynamicity §  System load: number of en00es and their goals. §  Context of en00es: u0lity may depend on context. Adaptability and Evolu4on. §  Mul0ple solu0ons with different u0lity to accomplish goal §  Maximize u0lity for given preferences and context. §  U0lity of solu0on for a given context can be learned.


Key Concepts

En4ty §  Represents a physical or virtual

organiza0onal unit. §  Comprises of a set of goals [1] and cells

[2]. §  Associated with preferences, u0lity

func0ons and context. Cell §  Described as a process consis0ng of

abstract and concrete ac0vi0es. §  Specialized by replacing abstract

ac0vi0es with abstract or concrete ac0vi0es.

Cell A B C

Goal 1

Cell

D B G

Goal 2 En0ty

I J H

E

F

OR

Specializa0on of abstract ac0vity G

[1] Antonio Bucchiarone, Claudio Antares Mezzina, Heorhi Raik. A Goal Model for Collec.ve Adap.ve Systems. In FoCAS@SASO 2014, London, UK. [2] V. Andrikopoulos, A. Bucchiarone, S. Saez, D. Karastoyanova C. Mezzina: Towards Modeling and Execu.on of Collec.ve Adap.ve Systems. ICSOC Workshops 2013: 69-‐81


Key Concepts

Ensemble §  Associated with a goal. §  Composi0on of specialized cells

w.r.t. goal and context. §  Cells collaborate to achieve

ensemble goal. Cell

D E

Cell

D B

C

Cell

E F G

Ensemble

Goal

“Emergent aggrega.on of autonomous and self-‐adap.ve process-‐based elements”


Problem Descrip0on

1 2 6

3

5

4

7 8 9 Train Sta0on

A

B

Travel to A

Travel to A

Travel to B

Travel to B

Travel to Train Sta0on

Arrive by Train and travel to B


Problem Descrip0on

1 2 6

3

5

4

7 8 9 Train Sta0on

A

B

Travel to A

Travel to A

Travel to B

Travel to B



Car accident on the bridge, the bridge is blocked. The first intui0ve solu0on is to change the route and con0nue…


Problem Descrip0on

1 2 6

3

5

4

7 8 9 Train Sta0on

A

B

Travel to A

Travel to A

Travel to B

Travel to B



15 minutes delay


Problem Descrip0on

1 2 6

3

5

4

7 8 9 Train Sta0on

A

B

Travel to A

Travel to A

Travel to B

Travel to B



15 minutes delay

a)  5,6,7 risk to be late for the train b)  The bus cannot resolve the situa.on autonomously


Problem Description

1 2 6

3

5

4

7 8 9 Train Sta0on

A

B

Travel to A

Travel to A

Travel to B

Travel to B



The Flexi Bus Company tries to find a solu0on itself, e.g. there is another route that can deviate to collect 5,6,7 introducing a delay of 10 minutes. a)  The delay is fine for 5,6,7 but not for 8,9 b)  The Flexi Bus Company cannot resolve the situa.on autonomously


Requirements

§  Each CAS par0cipant cannot adapt its behavior in complete isola0on

§  Each adapta0on may nega0vely affect the goals of other par0cipants (i.e., conflic4ng goals)

§  Each adapta0on can compromise the whole collabora0on

1.   Every adapta.on must be resolved at the scale of the whole Ensemble.

2.   Adapta.ons may need to be simultaneously applied to the behavior of mul.ple par.cipants

3.   Adapta.ons must respect the specific condi.ons that par.cipa.on to the Ensemble imposes.


Entities in a Collective Adaptive System

§  A CAS is modeled as a set of en00es (i.e., flexibus route manager, passengers, buses, etc..).

§  En00es can join and exit the applica0on dynamically. §  An En0ty lifecycle consists in execu0ng its process (i.e., cell)

over 0me and exploi0ng fragments of surrounding en00es.

Fragments

Process

Domain Objects

Fragments

Process

Domain Objects

Fragments

Process

Domain Objects

Domain Model

Entity A Entity B Entity C


Domain Model

§  Defined through a set of domain objects, each capturing a par0cular aspect of the system and its evolu0on (modeled as state transi0on systems)

§  Shared representa0on of the system opera0on environment used to express goals, precondi3ons and effects on fragments and processes

§  Domain objects evolve as an effect of fragment ac0vity execu0on (normal behavior) or as a result of exogenous changes (improbable behavior)


Domain Model

None

Booked

Cancelled

book

cancel

Booking None

Paid

Nonref Refunded

pay

refund

fix

Payment Updated

notUpdated

change

I4neraryStatus

commit

Passenger

None

Assigned

assign

I4nerayStatus

notUpdated

update

AtStop

Driving

start stop

Ok

Nok

damage

repair

Status

FlexiBus

Posi4on


Processes and Fragments

Antonio Bucchiarone, Annapaola Marconi, Marco Pistore, Heorhi Raik: Dynamic Adapta3on of Fragment-‐Based and Context-‐Aware Business Processes. ICWS 2012: 33-‐41

register vehicle

get i0nerary

go to next stop

leave/collect passengers X X

G1 G2 P3 G3 P4 G4

+ Precondi0on/Effects used for -‐ detec0ng run-‐0me viola0ons -‐ automa0c reasoning for adapta0on

None

assign

I4nerayStatus

notUpdated

update

Assigned

AtStop

Driving

start stop

Posi4on

+ Abstract ac0vi0es / Goals used for -‐ run-‐0me context-‐aware service composi0on

gps request

gps response

follow direc0ons

E1


Collective Adaptation Rules

§  We introduce a mechanism for sharing cri0cal changes between the domain models of various en00es to spread the awareness.

§  We implement this mechanism as a set of collec0ve adapta0on rules that encode casual rela0ons between different domain events.

§  Rules as an integral part of ensemble and provided by the ensemble designer

triggering Events that are triggered



∃FB.ItineraryStatus.update→∀Passenger.ItinerayStatus.change

None

Assigned

assign

I0nerayStatus

notUpdated

update

Updated

change

I0neraryStatus

commit

notUpdated



notUpdated

∃Passenger.Booking.cancel→∃FB.ItinerayStatus.change∧∀Passenger.ItineraryStatus.change

None

Booked

book

cancel

Booking

Updated

change

I4neraryStatus

commit

None

Assigned

assign

I4nerayStatus

notUpdated

update

Cancelled


Collective Adaptation: An Example


Ensemble Activity

§  Ensemble as a number of roles that can be played by par0cipants and a set of collec4ve adapta4on rules regula0ng signalling between roles.

§  Collabora4on within an ensemble must be considered as only one of the tasks that belong to the en0ty process.

§  We extend our process model with a new type of ac0vity called ensemble activity

§  It is refined and executed in compliance with the ensemble tules

book seat pay trip go to stop take bus go to des0na0on

Task 1 Task 2 (play passenger in route)

Task 3


Implementation

Adapta4on Manager

Process Engine

Domain Manager

En0ty Model

Port

Communica0on Module

CA Rules

§  Process Engine to run en0ty process and monitor viola0ons. §  Adapta4on Manager to find a solu0on to each adapta0on

problem by automa0cally composing available fragments. §  The adapta0on manager transforms an adapta0on problem

into AI planning problem [3]

§  Domain Manager o  maintains the domain model and current state of an en0ty

o  checks if any rules in the Collec0ve Adap0ve Rules of the ensemble must be applied

[3] H. Raik, A. Bucchiarone, N. Khurshid, A. Marconi, and M. Pistore. Astro-‐captevo: Dynamic context-‐aware adapta.on for service-‐based systems. In SERVICES, pages 385–392, 2012.


Implementation

§  The signaling propaga4on occurs through a publish/subscribe bus.

§  Each en0ty has a communica3on module which manages its Port and governs all exchanges with the Communica3on Manager bus as well as the Fragment Repository

Adapta4on Manager

Process Engine

Domain Manager

Communica0on Manager (P/S)

En0ty Model

Adapta4on Manager

Process Engine

Domain Manager

En0ty Model

Fragments Repository

Port Port

Communica0on Module Communica0on Module

CA Rules

CA Rules


Conclusions

§  A conceptualiza0on that enables the collec0ve adapta0on of ensembles composed of process-‐based en00es.

§  We have outlined an architecture that supports the enactment of such collec0ve adapta0on.

Open Points: §  Booom-‐up crea0on of Ensembles (i.e., emergent Behavior)

§  Hierarchical Ensembles: mul0ple CASs come into a collabora0on in a larger ensemble (i.e., system of systems, socio-‐technical systems, etc..)

Service Oriented Applica0ons (SOA) Unit

Collective Adaptation in Process-based Systems

Antonio Bucchiarone, C. Mezzina, M. Pistore, H. Raik, and G. Valetto

SASO 2014 8-12 September 2014, London, UK

Fondazione Bruno Kessler, Trento – Italy [email protected]

collective adaptation in process-based systems

Presentations & Public Speaking