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Adaptive information systems Prof. Barbara Pernici Department of Electronics and Information Politecnico di Milano April 24, 2007.

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Presentation on theme: "Adaptive information systems Prof. Barbara Pernici Department of Electronics and Information Politecnico di Milano April 24, 2007."— Presentation transcript:

1 Adaptive information systems Prof. Barbara Pernici Department of Electronics and Information Politecnico di Milano April 24, 2007

2 Barbara Pernici, DEI 2 Outline Introduction and Motivations Flexible services Service discovery, negotiation, optimization Self-healing services Flexible service design Discussion

3 Barbara Pernici, DEI 3 Scenarios

4 Barbara Pernici, DEI 4 General Scenario

5 Barbara Pernici, DEI 5 microMAIS

6 Barbara Pernici, DEI 6 Archeological site of Castelseprio

7 Barbara Pernici, DEI 7 Matera et al., 2006 (MAIS project)

8 Barbara Pernici, DEI 8 MultiLezi Mainetti, Sbattella et al, 2006

9 Barbara Pernici, DEI 9 MultiLezi - aacLezi

10 Barbara Pernici, DEI 10 Business processes based on services Send OrderReceive Order Split Order Check Availability On Warehouse Check Availability On Supplier Calculate Cost Supply Check Availability Calculation Split CUSTOMERSHOP WAREHOUSE

11 Barbara Pernici, DEI 11 Mobile Adaptive Information Systems  Mobile devices, varying context PDA’s, smartphones, ….  Wireless networks ad hoc (MANET)  Networked services (SOA) MAIS: Multichannel Adaptive Information Systems Italian Project http://www.mais-project.it

12 Barbara Pernici, DEI 12 Quality of Service in adaptive IS t QoS Accepted quality threshold Quality dimensions

13 Barbara Pernici, DEI 13 Flexible web- service environment Adaptive network Adaptive hw/sw architecture VSDB Web applications Front-end environment Reflective architecture MAIS: Reference Architecture

14 Barbara Pernici, DEI 14 MAIS front-end components MAIS back-end components MAIS Reflective Architecture MAIS Core front-end (traditional client) Web service MAIS-enabled node MAIS front-end components MAIS Reflective Architecture MAIS Core MAIS-enabled node MAIS back-end components MAIS Reflective Architecture MAIS Core MAIS-enabled node network Non MAIS-enabled node MAIS nodes

15 Barbara Pernici, DEI 15 Interdisciplinary research Adaptation to several channels, mobility, context-awareness QoS guarantee Computer science  Information systems  Service engineering  Software engineering  Database technology  Architecture design Telecommunications  Networks  Modems Business Science  User and service profiling  Costs and tariffs evaluation Focus in the talk on: business processes service research middleware

16 Barbara Pernici, DEI 16 Adaptivity in Information systems Research areas Life cycle Levels Mechanisms

17 Barbara Pernici, DEI 17 Lyfe cycle Design time Deployment/configuration time Run time

18 Barbara Pernici, DEI 18 Levels Context independent Context Quality of Service, Quality of Experience

19 Barbara Pernici, DEI 19 Mechanisms Matchmaking Wrapping/mediation Monitoring Adaptation, self-*, Recovery, Management (WS/Business Processes)

20 Barbara Pernici, DEI 20 Research in IS group at Politecnico di Milano

21 Barbara Pernici, DEI 21 Research topics at Politecnico – IS group 1.Adaptive information systems 2.Service design and engineering 3.Cost evaluation Projects: -EU WS-Diamond on Self-healing web services -Italian basic research project: MAIS (Multichannel Adaptive Information Systems) -Other applied research projects: services for virtual enterprises (textile, dangerous goods transportation, services for SMEs)

22 Barbara Pernici, DEI 22 Wrt SOC research roadmap “grand challenges” Service foundations  Dynamic connectivity capabilities, service discovery (Concrete Service Invoker, URBE) Service composition  QoS-aware service composition (optimization algorithms for service selection in processes, negotiation of QoS) Service management  Self-healing services (SH-BPEL) Service design and development  Design principles (user-oriented design)

23 Barbara Pernici, DEI 23 Positioning Research areas  Service, Business Processes Life cycle  Run time (towards design) Levels  User context  QoS Mechanisms  Matchmaking  Wrapping/mediation  Recovery (WS/Business Processes)  Monitoring Life cycle Mechanisms Levels Run time Deploy ment Design matchmaking Wrapping/mediation) Recovery, self* Context QoS No context Moving from run time to deploy/design time research problems monitoring

24 Barbara Pernici, DEI 24 Adaptive Services in PAWS Processes with Adaptive Web Services Service model Registry and matchmaking Optimization with QoS constraints QoS negotiation and contracting Service adaptation and invocation Service Repair Self-Healing services

25 Barbara Pernici, DEI 25 E-service model Abstract service Flexible service Concrete service

26 Barbara Pernici, DEI 26 Concrete Service Invoker - Scenario MAIS Client Concrete Service Invoker Platform Invoker MAIS Reflective Architecture FlightService Lufthansa Alitalia MAIS Front- End Concrete Service Invoker Location = Italy Location = Germany Wrapper V. De Antonellis, M. Melchiori, L. De Santis, M. Mecella, E. Mussi, B. Pernici, P. Plebani. (2006). A layered architecture for flexible e-service invocation”, Software & Practice Experience. vol. 36(2), C. Cappiello, M. Comuzzi, E. Mussi, B. Pernici: Context Management for Adaptive Information Systems. Electr. Notes Theor. Comput. Sci. 146(1): (2006)

27 Barbara Pernici, DEI 27 Receive find-travel Receive book-travel Travel-Service book-travel find-travel pay-travel Receive pay-travel Service interface model (+ Port types) behavior QoS

28 Barbara Pernici, DEI 28 QoS model Multiattribute User/provider preferences (weights) Dimensions definition  Names, ranges Community defined dimensions Carlo Marchetti, Barbara Pernici, Pierluigi Plebani: A quality model for multichannel adaptive information. WWW 2004 C. Cappiello, B. Pernici, P. Plebani. “Quality-agnostic or quality-aware semantic service descriptions?”. W3C Workhsop on Semantic Web Service Framework, Innsbruck, June 2005Quality-agnostic or quality-aware semantic service descriptions? request QiQi

29 Barbara Pernici, DEI 29 Service discovery Selection criteria User context and preferences Fitness of functionality QoS constraints

30 Barbara Pernici, DEI 30 Abstract Service level QoS E-service ontology De Antonellis et al, Inf. Sys., 2006

31 Barbara Pernici, DEI 31 URBE URBE = Uddi Registry By Example UDDI Service discovery is driven by:  Keyword-based query  Pre-defined taxonomies browsing URBE extends UDDI also supporting a content based query  Client submits a WSDL  UDDI returns a list of similar Web services D. Bianchini, V. De Antonellis, M. Melchiori, B. Pernici, P. Plebani. (2006). Ontology based methodology for e-service discovery. Information Systems, vol. 31(4-5)

32 Barbara Pernici, DEI 32 Web service Similarity URBE considers both “structural” and “semantic” similarity Semantic similarity discover relationships among terms  Using domain specific term ontology  Using generic term ontology, i.e. Wordnet Structural similarity  Is calculated by analyzing terms in WSDL at different levels: portType, operation, and message part names  More terms at the same level are related more similar are the Web services

33 Barbara Pernici, DEI 33 Matching: further aspects and future work Functional  Classification of services according to reference abstract services (clustering) QoS  Weighted user preferences Hierarchical analytical processing M.G. Fugini, P. Plebani, F. Ramoni, ICSOC 2006  Quality of Experience (in context) As perceived by user in the execution context, not as published in registry Semantic annotations  Semantic plugin to increase recall  Design of semantic annotations Process matching

34 Barbara Pernici, DEI 34 Concrete Service Invoker – Wrapper Generation Wrapper FlightService WSDL Alitalia WSDL Similarity Engine Similarity Evaluation

35 Barbara Pernici, DEI 35 Wrapper generation Semi-automatic construction Similarity of parameters and operations  Thesaurus (terms, simple semantic annotations)  Reference services Transformation of parameters structure and names  Restructuring  String concatenation Designer support to extract semantics derived from user interface (web page)  Structural analysis of page  Thesaurus Research towards wrapper and mediation engines Enrico Mussi PhD Thesis, Politecnico di Milano, 2007

36 Barbara Pernici, DEI 36 Quality constraints (hard and global): cost <1000 train.reservation.cost<600 Invoke hotel.reservation Invoke train.reservation Preferred: - ACMEHotels - ItalianHotels Negotiate: - lowest price - offer request Invoke flight.reservation not latelate Probability=0.8 Probability=0.2 Service composition

37 Barbara Pernici, DEI 37 Optimization problem Multi-attribute -> Simple Additive Weighting (SAW)  Scoring function, scaling, weighting Transformation to a linear model, with binary variables Multiple-choice Multiple-dimension Knapsack (MMKP) Solution:  decomposition (execution paths, extension of Zeng et al. 2004), Admissible solution  Cycles – peeling vs unfolding  Reoptimization  Negotiation if unfeasible Danilo Ardagna, Barbara Pernici: IEEE Trans. Sw. Eng., July 2007

38 Barbara Pernici, DEI 38 Other issues to be investigated Advanced optimization:  Stateful services Reoptimization  Reoptimization rules WS on local grids  Broker  Business processes D. Ardagna, G. Giunta, N. Ingraffia, R. Mirandola, B. Pernici, QoS- driven Web Service Selection in Autonomic Grid Environments, (GADA'06), Montpellier, France, 2006

39 Barbara Pernici, DEI 39 Negotiation  A) Identify an admissible solution When service selection in optimization fails  B) Negotiation to set up a contract for service provisioning (QoS) With each selected service

40 Barbara Pernici, DEI 40 Negotiation - Introduction Automated negotiation  Negotiation is faster when performed by software agents  The number of potential partners naturally grows  Remove emotional and psychological tricks First approaches in the field of multi-agent computing  Planning problems  Economic transactions (dynamic pricing, e-auctions) Lack of comprehensive approaches in SOA context  Algorithm and strategies already defined  Web Service based infrastructures for automated negotiation

41 Barbara Pernici, DEI 41 Negotiation for web service selection Our approach automatic negotiation (user and provider profiles) multiattribute (QoS dimensions) WS infrastructure (negotiation service) Two steps  Multi-party negotiation to select the best available service  Direct bilateral negotiation Marco Comuzzi, Barbara Pernici: An Architecture for Flexible Web Service QoS Negotiation. EDOC 2005 Marco Comuzzi, Barbara Pernici: Negotiation Support for Web Service Selection. TES 2004 Marco Comuzzi, PhD Thesis, Politecnico di Milano, 2007

42 Barbara Pernici, DEI 42 Future work: Web services contracting Contract specification (WSLA language, WS-Agreement)  Describe service elements touched by the contract (portTypes, operations,…)  Report guarantees (SLOs), recovery actions, penalties,…  Identify monitoring third parties Multi-party interaction

43 Barbara Pernici, DEI 43 Flexible services (towards self*) Dynamic service selection and invocation Service Repair Service self-healing

44 Barbara Pernici, DEI 44 WS-Diamond Web Services DIAgnosability, MONitoring and Diagnosis (EU FET STREP Project 2005-2008) http://wsdiamond.di.unito.it/ Self-healing Web service environment Ws-Diamond (UE Project) enabling to:  detect anomalous situations (network/hardware failures, Web Service failures, application failures)  diagnose faults from the analysis of detected failures  select the most suitable recovery action  perform the selected recovery actions to reconfigure the network of services Ws-Diamond aims at supporting both choreographed and orchestrated Web service environments

45 Barbara Pernici, DEI 45 Exceptions and self-healing

46 Barbara Pernici, DEI 46 Ws-Diamond: Nodes

47 Barbara Pernici, DEI 47 Ws-Diamond: A Diamond-Enabled Node Recovery Selector Diagnoser Web Service Management Interface Fault Notification Repair Actions Symptoms Event Logs Other Alarms S. Modafferi, E. Mussi, B. Pernici, SH-BPEL - A Self-Healing plug-in for Ws-BPEL engines, Middleware for Service Oriented Computing (MW4SOC) Workshop, November, 2006, Melbourne, Australia

48 Barbara Pernici, DEI 48 WS-Diamond and Choreography Recovery Selector Diagnoser Web Service Management Interface Recovery Selector Diagnoser Web Service Management Interface Recovery Selector Diagnoser Web Service Management Interface

49 Barbara Pernici, DEI 49 Orchestration, Diagnosis, and Recovery Recovery Selector Diagnoser WS-BPEL Management Interface Web Service 1 Web Service 2 Web Service N Symptoms Event Logs Fault Notification Event Logs Other Alarms Repair Actions SH-BPEL

50 Barbara Pernici, DEI 50 Ws-Diamond and Orchestration Recovery Selector Diagnoser WS-BPEL Management Interface Web Service 1 Web Service 2 Web Service N (Infrastructure-level recovery actions) Process-level recovery actions

51 Barbara Pernici, DEI 51 SH-BPEL: The Process Manager Management Engine Management Interface BPEL Interface Mediator Web Service Invoker Substitution Manager Web Service Retriever Mediation Service Process Manager

52 Barbara Pernici, DEI 52 Case 1: Customer Fault Send OrderReceive Order Split Order Check Availability On Warehouse Check Availability On Supplier Calculate Cost Supply Check Availability Calculation Split CUSTOMERSHOP WAREHOUSE The CUSTOMER is declared faulty The Recovery Selector stops the SHOP The CUSTOMER is repaired The Recovery Selector sets the order variable of SHOP inserting the correct value The Recovery Selector resumes the SHOP process from the receive order activity

53 Barbara Pernici, DEI 53 Case 2: Shop Fault Send OrderReceive Order Split Order Check Availability On Warehouse Check Availability On Supplier Calculate Cost Supply Check Availability Calculation Split CUSTOMERSHOP WAREHOUSE The SHOP is declared faulty The Recovery Selector stops the SHOP and the WAREHOUSE The split activity is repaired The Recovery Selector retries the split activity The Recovery Selector retries all the activities up to the calculate cost activity and then resumes the process

54 Barbara Pernici, DEI 54 Case 3: Warehouse Fault Send OrderReceive Order Split Order Check Availability On Warehouse Check Availability On Supplier Calculate Cost Supply Check Availability Calculation Service Split Service CUSTOMERSHOP WAREHOUSE The WAREHOUSE is declared faulty The Recovery Selector stops the SHOP and the WAREHOUSE The Recovery Selector substitutes the WAREHOUSE The Recovery Selector redoes the check availability activity The Recovery Selector redoes all the activities up to the calculate cost activity and then resumes the process

55 Barbara Pernici, DEI 55 Demo Structure (Case 1 and Case 3) WS-BPEL Management Interface WAREHOUSE 1 SH-BPEL WSDL 1 ≠ WSDL 2 SHOP Client SH-BPEL Administrator WSDM Subscription Invocation Notification Repair WAREHOUSE 2 Stop Resume

56 Barbara Pernici, DEI 56 Web Service Substitution: Mediator execution Mediation Service External Data Retriever Translation Engine Input message (Warehouse 1 WSDL) Input message (Warehouse 2 WSDL) Output message (Warehouse 1 WSDL) Output message (Warehouse 2 WSDL)

57 Barbara Pernici, DEI 57 Future Work Introduce Semantics to  Enhance recovery actions  Enhance service mediation Define patterns and strategies to recover from common faulty situations Repair choreographed processes: many autonomous interacting processes

58 Barbara Pernici, DEI 58 Methodology for designing self-healing services Design a process on which diagnosis can be performed and repair actions applied Point of view of repair  Make process more reliable/repairable  Evaluate improvement of process and costs  Define management actions for process Pre-defined (safe points, changeable variables, replication, …) Run time (e.g. dynamic invocation/substitution, reallocation, adjustment of QoS with negotiation…) Support to diagnoser

59 Barbara Pernici, DEI 59 Design for adaptivity Benatallah, Casati, Modafferi, Pernici, MOBIS, 2005

60 Barbara Pernici, DEI 60 Our focus on data quality Focus on process design (orchestrated) Faults  Typing errors  Wrong databases/information systems  Misalignment of data  Unavailable information services (permanent/temporary) Multiple perspectives  User, provider(s)

61 Barbara Pernici, DEI 61 Process Analysis In the process analysis, it is important to identify:  Relevant processes  Actors within their roles and their requirements In this phase we analyze actors perspectives… what are the relevant aspects for the actors involved in the process? The most important contributions for diagnosis are:  Identification of the user class that is mostly damaged for a specific fault occured in the process.  Identification of the most important dimension in each step of the process Cappiello and Pernici, ER workshops, 2006

62 Barbara Pernici, DEI 62 Process Design Reparaibility and diagnosability of a process can be enabled in its design:  Initial flow modification: Exceptions, support to pre-defined repair actions Service Redundancy  Insertion of quality monitoring block

63 Barbara Pernici, DEI 63 Design of run time actions “configuration” of process execution engine + provide run time mgmt actions Run time actions we can consider:  the failed service: re-invocation, re-negotiation of QoS parameters, re-allocation of the service resources  The need for a registry, for a QoS annotation  Other services: workaround  The need for maintaining information about relationships among services

64 Barbara Pernici, DEI 64 Concluding remarks General trends  Information systems as composition of interacting services (design time or run time)  Each service can be complex  Open world Need for research work on design of adaptive IS  Flexible components characterization  Service management: self-healing Repairability Diagnosability  Economic issues  Trust, responsibility

65 Barbara Pernici, DEI 65 Thank you! Further references www.elet.polimi.it/people/pernici QUESTIONS?


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