Workflow Management Systems

Transcription

1 CS565 - Busiess Process & Workflow Maagemet Systems Workflow Maagemet Systems 1

2 Workflow Maagemet Systems Workflow maagemet is the automated coordiatio, cotrol ad commuicatio of work, both of people ad computers, i the cotext of orgaizatioal processes, through the executio of software i a etwork of computers whose order of executio is cotrolled by a computerized represetatio of the busiess processes Workflow maagemet system: a system that defies, creates ad maages the executio of workflows through the use of software, ruig o oe or more workflow egies, which is able to iterpret the process defiitio, iteract with workflow participats ad, where required, ivoke IT tools ad applicatios [WFM Coalitio] 2

3 Aatomy of Workflow Maagemet Sub-Processes Process Defiitio Which may be Maual Activities Is defied i a (a represetatio of what is iteded to happe) Activities or (which are ot maaged as part of the Workflow system) Composed of Relatioships betwee cocepts Busiess Process Automated Activities (i.e what is iteded to happe ) Durig executio are represeted by Used to maage ad create Work Items Is maaged by Workflow Maagemet System (tasks allocated to a workflow participat) Process Istaces (cotrols automated aspects of the busiess process via) (a represetatio of what is actually happeig) Iclude oe or more Activity Istaces Ad/Or Which iclude Ivoked Applicatios (computer tools/applicatios used to support a activity) 3

4 Workflow Maagemet Issues Busiess Process Aalysis, Modelig & Defiitio Process Desig & Defiitio Process Defiitio Build Time Ru Time Workflow Eactmet Service Process Istatiatio & Cotrol Applicatios & IT Tools Iteractios with Users & Applicatio Tools 4

5 Workflow Maagemet Issues Process Workflow specificatio Workflow Implemetatio =workflow applicatio Busiess Process Modelig/ Reegieerig (BPM/R) Workflow model & specificatio laguage Executable applicatio code Eactmet Service/ Rutime Support 5

6 Coceptual Architecture (system compoets) PM Toolkit process specificatio - process view - org. view process aalysis re-egieerig quality advisig... WF Developmet Toolkit graphical workflow desig testig simulatio aimatio WF Eactmet Service (ru-time system ad tools) schedulig task maager/ iterfaces processig etities moitorig trackig reportig... 6

7 WFMS Features Moitorig, trackig, auditig, reportig Authorizatio; Security Iteroperability Multiple computig platforms ad commuicatios ifrastructures Load balacig Versioig ad life-cycle Scalability: Partly distributed eactmet service (multiple server support); Fully distributed eactmet service Cloud support 7

8 WFMS Features 8

9 Process Aalysis Purpose: To esure that the right people uderstad the ecessary facts about a orgaizatioal process. Objectives: g shared uderstadig g trigger model (evet-drive) How to: gwho to talk to? (roles) g What do you do? (activities) g What prompts you to do it? (triggers) g Follow liks, ad repeat. Usig: iterviews (time cosumig, rich secodary iformatio), meetigs (quick, obscure social process) 9

10 Example: Complait Procedure customer repres ive ispector maager libraria deliver complait reject ack. filig a complait aalyze log coset egotiate solutio summarize ack. approve egotiate satisfactio execute solutio 10

11 Basic Model Compoets Workflow (process) class (schema) to model a() (busiess / orgaizatioal) process Task, activity or step Task coordiatio / likig or Cotrol flow (serial / parallelresyc/list/queues/etwork, rules/triggers, depedecies / coditios) Data flow or sharig (explicit passig, shared data, commo variables) Processig etities: Users --roles ad authorizatio, worklists; Iformatio Systems 11

12 Workflow Modellig Workflows deal with (parts of) busiess processes, also called cases or scearios g e.g., a isurace claim, a loa applicatio Similar cases belog to the same case type Each case has a uique idetity Cases have a limited lifetime: from the poit i time the case was submitted, to the poit its processig has bee completed At ay poit durig its lifetime, a case has a state comprisig: g the values of the relevat attributes g the coditios that have bee fulfilled g the cotet of the case 12

13 Workflow Modellig Workflows are structured i tasks g a task is a logical uit of work g regarded as idivisible or atomic (either executed i full or if its executio is stopped, a rollback to the previous state takes place) Tasks are distiguished ito g maual: performed by humas without IT support g automatic: performed without huma itervetio g semi-automatic: ivolve both humas ad applicatio programs 13

14 Applicatio/Automatic Tasks Applicatio tasks ivolve g g g g g g g scripts for termial emulatio to remote systems Web services applicatio programs/systems providig data maipulatio (filters) predefied iterfaces to legacy applicatio systems stored procedure calls cliet programs or servers ivokig other servers database trasactios 14

15 Workflow Modellig Tasks refer to geeric pieces of work ad ot to performig a particular activity for a specific case Task work item Activity task executio for particular case A process specifies the way i which a particular category of cases should be carried out ad i what order. A process ca be viewed as a procedure for a particular case type. Differet cases ca be hadled usig a sigle process A process is made up of tasks ad coditios ad may iclude sub-processes Complex processes ca be structured hierarchically Each process has a begiig ad a ed which mark the iitiatio ad completio of a case. 15

16 Workflow Modellig Workflow schedulig or routig: basic costructs g sequetial task executio: implies a depedecy betwee tasks that follow oe aother; the result of oe task is iput to the ext g parallel task executio: tasks that eed to be executed simultaeously without the result of oe affectig the other. Parallel tasks are iitiated usig a AND-split ad later resychroized usig a AND-joi g selective routig: choice betwee two or more tasks (depedig upo specific properties of the case). Choice also kow as a OR-split. Alterative paths are reuited usig a OR-joi. g iteratio: performig a particular task a umber of times 16

17 Types of Processig Etities humas (may appear as a GUI; may use documet/image processig systems ad applicatios) script iterpreters ad compilers (for processig scripts ad applicatio programs) (legacy) applicatio systems servers i cliet-server ad trasactio processig systems DBMSs 17

18 Additioal Modellig Features Tasks: o-trasactioal, trasactioal Executio eviromet / ifrastructure / cofiguratio: executio locatio, iterfaces Deadlies Exceptio Hadlig (Error Hadlig, Recovery) specificatio 18

19 Workflow Modellig & Aalysis Workflow eactmet g the eactmet of work items is triggered by resources (huma or automated), a exteral evet or a time sigal Workflow modellig ad aalysis must be carried out formally g forces precise defiitios avoidig ambiguities, ucertaities ad cotradictios (cotrary to may semi-formal diagrammatic techiques) g formalisms ca be used to reaso about processes (e.g., whether a case is successfully completed after a period of time, whether liveess or safety properties are maitaied etc.) 19

20 Workflow (Specificatio) Aalysis A clear theoretical basis ad correctess criteria must be established which eable the rutime system to efficietly reaso about the correctess of a requested chage... Types of Aalysis Validatio - iteractive simulatio (Are we buildig the right product?) Verificatio (establishig correctess of a workflow) - advaced aalysis techiques (Are we buildig the product right?) Performace Aalysis - throughput etc. 20

21 Correctess Criteria Structural properties Cotrol flow, Data flow, Temporal costraits Reachability, Termiatio, Deadlocks, Data icosistecy, Missig iput data Other Workflow characteristics Reassigmet of task to agets Chages i orgaizatioal schema Access to exteral databases 21

22 Formal Basis for Models High level Petri ets State ad Activity charts Temporal logic Process Algebra Graph based models Rules But there are limitatios wrt to what is modeled usig formal models. Ofte limited to workflow maps/graphs, iter-task depedecies. 22

23 Petri Nets a formalism for modelig ad aalyzig workflows g devised by Carl Petri (1962) as a tool for process modelig ad aalysis processes ca be described graphically ad i additio they possess a mathematical foudatio A Petri Net (PN) cosists of places ad trasitios deoted by circles ad rectagles respectively ge.g., the claim processig PN may have the places claim, uder cosideratio ad ready ad the trasitios record, pay ad sed letter places ad trasitios are coected by directed edges (place trasitio, trasitio place, but ot betwee places or trasitios) 23

24 Petri Nets A place p is called a iput place for a trasitio t if there is a edge from p to t A place p is called a output place for a trasitio t if there is a edge from t to p Places may cotai tokes (deoted by black dots) Although the structure of a PN is fixed, the distributio of tokes amog the places may chage The state of a PN is idicated by the distributio of tokes i the places of the et Firig a trasitio results i tokes movig from iput places to output places. 24

25 Petri Nets Example: pay uder cosideratio ready claim record sed letter The state may be represeted as the vector (3,0,0) 25

26 Petri Nets A trasitio may fire if it is eabled, i.e., there exists at least oe toke i each of its iput places Whe a trasitio fires, oe toke is removed from each iput place ad oe toke is added to the output place Tokes are cosumed from iput places ad produced at output places uder cosideratio pay claim record ready sed letter 26

27 Objectives ad Petri Goals Nets Submodel After trasitio record fires uder cosideratio claim record After trasitio pay fires uder cosideratio claim record pay sed letter pay ready ready sed letter 27

28 Petri Nets Whe a trasitio fires, the process shifts from oe state to aother Trasitios represet evet occurreces, operatios, trasformatios etc. ad are the active compoets of a P.N. Places are passive: they caot chage the state of the et; they represet particular coditios Tokes represet objects (physical, iformatioal etc.) More tha oe case ca be i progress simultaeously i a PN A PN ca also be used to describe repetitive processes 28

29 Petri Nets Example: a traffic light process for crossig a street red yr yellow rg gree gy 29

30 Petri Nets Example: two traffic light processes for crossig two 1-way streets g Requiremet: oe of the two must always be red red1 or1 or2 red2 orage1 rg1 X rg2 orage2 gree1 go1 go2 gree2 30

31 Petri Nets Apart from the graphical otatio provided by PNs, oe must be able to determie that the process modeled will operate safely. g we will study aalysis techiques later i the course PNs may become too large ad difficult to use. Several extesios have bee proposed: g Colored Petri Nets g Temporal Petri Nets g Hierarchical Petri Nets collectively referred to as high-level Petri Nets 31

32 The Weakesses of Traditioal Petri Nets Their primary aim is to represet the dyamic aspects of system behavior ad because of this they do ot have aythig other tha very simple capacity to represet etities of the domai of applicatio. Data represetatio is limited to tokes which are idistiguishable from each other. Clearly this is iadequate for represetig IT systems. Source: 32

33 Colored Petri Nets Colored Petri Nets combie the stregth of Petri ets with the stregth of programmig laguages. Petri ets provide the primitives for the descriptio of the sychroisatio of cocurret processes, while programmig laguages provide the primitives for the defiitio of data types ad the maipulatio of data values. 33

34 Colored Petri Nets I classic PN tokes foud i the same place are by defiitio idistiguishable. There is a eed to represet differet aspects or attributes of objects. I colored PN each toke has a value or color. Trasitios that fire produce tokes whose values deped o the values of the tokes cosumed. The umber of tokes produced by a trasitio also depeds o the values of the tokes cosumed. This provides a greater flexibility i represetig differet cases of processes. Like traditioal Petri Nets Colored Petri Nets cosist of Places,Trasitios, coected by Arcs (formig a bi-partite graph). They are a combiatio of text ad graphics. 34

35 Colored Petri Nets g Example: Dealig with techical faults i a product departmet g g faults are categorized if they caot be corrected right away, a repair takes place ad it is tested yieldig three possible results: 1. Fault has bee corrected 2. Further repair is required 3. Faulty compoet must be replaced A toke value represets relevat properties of the fault that eeds to be dealt with ad this value is retaied throughout the tokes trajectory i the et 35

36 Colored Petri Nets fault categorize solved eeds repair repair eeds testig test replace A output place may ot receive a toke: depedig o the trasitio categorize, a fault will be either solved or a repair will be eeded. Trasitio test may produce a toke i oe of 3 possible places 36

37 Colored Petri Nets I colored PN, coditios ca be set for the values of tokes to be cosumed A trasitio is oly eabled if there is a toke at each of its iput places ad the precoditios for firig the trasitio are met Precoditios are logical expressios referrig to the values of tokes ge.g., the trasitio categorize may have the precoditio the value of the toke to be cosumed from the place fault must cotai a valid compoet id g i this case, a fault missig a valid id will ot be categorized (trasitio ot fired; remai i the place fault) 37

38 Colored Petri Nets Precoditios ca also be used to sychroize tokes, i.e., to specify that a trasitio will fire oly if a particular combiatio of tokes ca be cosumed Example: car assembly process productio order chassis egie assemble wheel car whe a trasitio fires the umber of iput tokes must be equal to the umber of icomig arrows a precoditio must specify that tokes ca oly be cosumed i a certai combiatio (ad ot at radom) 38

39 Colored Petri Nets The examples show that ot all the required iformatio ca be represeted graphically. For each trasitio, we eed to specify: g the precoditio for firig the trasitio (if oe exists) g the umber of tokes produced i each output place whe the trasitio fires g the values of the tokes produced This iformatio ca be specified as text (pseudo-code) or as a subroutie i a programmig laguage or as a formal specificatio 39

40 Places Places are specified with the followig iscriptios: gname (for idetificatio). gcolor set (specifyig the type of tokes which may reside o the place). giitial markig (multi-set of toke colors) 40

41 Trasitios Each trasitio has the followig iscriptios: g Name (for idetificatio). g Guard (boolea expressio cotaiig some of the variables). 41

42 Arcs Each arc has the followig iscriptios: g Arc expressio (cotaiig some of the variables). Whe the arc expressio is evaluated it yields a multiset of toke colors. 42

43 Example 43

44 Markig Place P2 is empty. The markig at P1 cosists of 2 tokes of type iteger whose value is 3 ad 2 tokes of type iteger whose value is 8. O T1 is the guard X > 5. This is a barrier to T1 happeig, i that T1 will oly pass if the assigmet to X uder the occurrece i questio is greater tha 5. As we will see these guards o trasitios will play a importat part i represetig the barriers to the performace of activities. 44

45 The Arc Expressio O the arc betwee P1 ad T1 is the atomic expressio cosistig of a variable X to which may be boud oe of the iput tokes i P1. Such a bidig is called a occurrece. The expressio o the output arc from T1 to P2 represets the state chage which takes place across trasitio T1. I this example it embodies a icremet of 1 o the variable X 45

46 Guards o the expressio The expressio X > 5 at trasitio T1 is kow as a guard ad must be satisfied by the icomig toke values. If the icomig tokes do ot satisfy the guard the the trasitio caot happe. I the case X has value 8 which is > 5, the trasitio ca take place 46

47 Example 47

48 Example after firig trasitio 48

49 Occurrece The passage of tokes across trasitios from place to place through this process of bidig, satisfyig guards ad modifyig data is called a occurrece. The occurrece will be blocked if the guard is ot satisfied by the icomig tokes. So if a iput toke with value 5 was boud to X the the trasitio could ot occur. The guard is a barrier to the trasitio happeig. 49

50 Temporally-exteded Petri Nets Ofte, there is a eed to specify expected process completio time ad other iformatio related to the timig of trasitios i a PN Classic PN do ot allow modelig time. I temporally-exteded PN, tokes have a timestamp i additio to a value. The timestamp represets the time from which the toke is available for cosumptio. Trasitio eablig time: earliest momet at which all its iput places cotai sufficiet available tokes. Tokes are cosumed i a first-i-first-out fashio. The trasitio with the earliest eablig time fires first. If more tha oe have the same eablig time, oe is chose radomly 50

51 Temporally-exteded Petri Nets Firig of a trasitio may affect the eablig time of other trasitios Produced tokes have timestamp equal to or greater tha the trasitio firig time There may be a delay that depeds o the trasitio ad the the values of the tokes cosumed The delay may be costat (could be 0) or may be decided radomly Trasitio firig is take to be istataeous 51

52 Temporally-exteded Petri Nets Example: sychroized traffic lights 0 red1 30 yr1 0 0 yr red2 yellow1 rg gree1 gy1 0 X rg2 gy yellow2 gree2 rg1 eablig time=0=rg2 eablig time If rg1 is chose a toke will be produced at gree1 with delay 25, at yellow1 with delay 30 ad at red1 ad X with delay 60; rg2 will fire 52

53 Hierarchical Petri Nets Classic, colored or temporally-exteded PN have a flat structure resultig i a sigle, possibly extesive ad complex et. Ofte processes are structured hierarchically, ad ca be modeled by etworks cotaiig sub-etworks (subprocesses) This provides the ability to refie processes rather tha regard them as o-decomposable. Graphically, o-atomic sub-processes are represeted as doubly-arrowed rectagles 53

54 Objectives Hierarchical ad Goals Petri Submodel Nets fault categorize solved reeds repair repair reeds testig test replace start tr trace ch chage e ed free 54

55 Hierarchical Petri Nets PNs ca be structured hierarchically usig a bottom-up or topdow approach g g Top-dow decompositio starts with high-level processes that are gradually decomposed ito sub-processes; at the lowest level, processes cosist oly of trasitios ad places Bottom-up sythesis starts with elemetary compoets that are combied ito larger processes Complex processes are rarely o-hierarchical, hece a divide ad coquer strategy is eeded. Reuse of (sub-) processes is also possible (e.g., whe a recurrig process is icluded) 55

56 Refereces Workflow Maagemet: Models, methods ad systems by va der Aalst ad va Hee Workflow Maagemet Coalitio ( ) Coloured Petri Nets ( ) Tutorial: ) Aimated examples: