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AnLiu IDAR07 nocomment

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Published on October 12, 2007

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Ensuring Consistent Termination of Composite Web Services:  Ensuring Consistent Termination of Composite Web Services An Liu1,2,3 and Qing Li2,3 1 Department of Computer Science and Technology University of Science & Technology of China (USTC), Hefei, China  2 Joint Research Lab of Excellence CityU-USTC Advanced Research Institute, Suzhou, China  3 Department of Computer Science City University of Hong Kong (CityU), Hong Kong, China liuan@ustc.edu itqli@cityu.edu.hk Outline:  Outline Problem Statement and Background Problem Modeling and Methodology Framework Conclusion and Future Work Web Services Composition:  Web Services Composition Client App Travel Agent Timeline Web Services Flight Taxi Hotel Reliable Composition Needs Transactional Support! ACID Transaction Insufficient:  ACID Transaction Insufficient Composite web services Last for hours or days Work in an open environment Cross administrative boundaries ACID transaction is insufficient Trust and timeliness no longer apply Compensation-based transaction No common transaction semantics Some Representative Related Work:  Some Representative Related Work Transaction semantics declaration Mikalsen et al. (2002): declare transaction semantics at operation level and transactional property at service level Transactional property (TP) deduction Vidyasankar and Vossen (2004): deduct TP of composite services from TP of component services Different Atomicity Requirements Fauvet et al. (2005): support flexible atomicity through TP-based service selection Bhiri et al. (2005): verify Accepted-Termination-States (ATS) based atomicity by some transactional rules Montagut and Molva (2006): support ATS-based atomicity through TP-based service selection and automatic coordination State of the Art:  State of the Art Current research has Defined TP of web services Guaranteed Reliable Service Composition in the context of heterogeneous TP Autonomy of services was overlooked Compensation has temporal and cost constraints (Benatallah et al. 2004) e.g., deadline of hotel reservation cancellation Problem Statement:  Problem Statement How to get reliable composition when both autonomy and heterogeneity are considered? Given The control flow of a composite service Component services with heterogeneous TP Temporal constraints of compensation How to get reliable composition where the composite service will terminate in a consistent state? Outline:  Outline Problem Statement and Background Problem Modeling and Methodology Framework Conclusion and Future Work Definitions:  Definitions Transactional Property (TP) of web services Compensatable (c): normal operation (on) and compensation operation (oc) Retriable (r): Only normal operation Pivot (p): Only normal operation Temporal property of operations Execution time (tx): e.g., 5 seconds Available time (ta): e.g., [9am, 5pm] Deadline: Maximal Compensatable Time (MCT) For compensation op, ta=[t, t+MCT] Definitions (cont.):  Definitions (cont.) Service s: 5-tuple(tp, on, oc, t, sta) tp{r, c, rc, p} on & oc : normal and compensation operation t = (ts, te): starting and ending time sta{initial, active, completed, aborted, failed, cancelled, compensated}: current state Process: G(Vt, Vo, E) Vo : set of control flow op. (cfo), where cfo{AND-split, AND-join, XOR-split, XOR-join, OR-split, OR-join, start-loop, end-loop} G(Vs, Vo, E): an instance of process G(Vt, Vo, E) Consistent Termination Condition:  Consistent Termination Condition A composite service sc will always terminate in a consistent state if the consistent termination condition (CTC) holds: vi.tp{c, rc}, sc.t.te  vi.oc.ta for vi  Vs in G Example: sc, s1s2 if s1.on.tx=2 & s1.oc.MCT=5 & s2.on.tx=4 then s1.oc.ta=[2,7], sc.t.te=6 CTC Verification:  CTC Verification Precondition: global view of a composite service: control flow, transactional and temporal property Method: simple calculation Problem: NOT easy to get a global view Dynamic selection Multi-level composition Methodology:  Methodology Assumptions A1: only elementary component services A2: static service selection A3: only compensatable component services A4: only AND-split and AND-join operators Outline:  Outline Problem Statement and Background Problem Modeling and Methodology Framework Conclusion and Future Work Framework Overview :  Framework Overview CTC Verification Examples:  CTC Verification Examples A B C D [10,30] 10 [11,31] 11 10 10 [16,28] 10 16 10 [8,16] [11,31] 17 11 [8,16] [10,18] 12 [12,20] 12 16 [16,28] 18 [18,30] [2,17] [2,17] 16 [16,28] 9 [9,17] [10,30] 10 11 [11,31] [11,19] 11 11 17 [17,29] Scheduling Algorithms:  Scheduling Algorithms Motivation: different scheduling algorithms lead to different results of CTC verification, which decide whether to abort the service or not Objective: design a scheduling algorithm which can decrease the possibility of service abortion Some algorithms Immediate scheduling Minimal delay scheduling Maximal delay scheduling Average delay scheduling …, optimal scheduling algorithm? Dynamic Monitoring :  Dynamic Monitoring Inaccurate Global View:  Inaccurate Global View Problems Uncertainty of Execution Time (UET) Information Missing (IM) IM1: execution time of normal operation is unknown IM2: available time of compensation operation is unknown Solution UET Scheduling algorithms Dynamic monitoring mechanism IM1: UET variation (increased execution time) IM2: Dynamic monitoring mechanism Removing Assumptions:  Removing Assumptions A4 (only AND-split and AND-join operators) Loop: UET variation XOR/OR: pseudo AND operator A3 (only compensatable component services) Retriable: safely ignored Pivot: process graph division A2 (static service selection) IM1 & IM2 A1 (only elementary component services) IM1 & IM2 Time Complexity:  Time Complexity CTC verification: O(n+e) Dynamic monitoring: O(n2+ne) Total time complexity: O(n2+ne) Outline:  Outline Problem Statement and Background Problem Modeling and Methodology Framework Conclusion and Future Work Conclusion and Future Work:  Conclusion and Future Work A framework Assists selection of services based on transactional and temporal property Ensures consistent termination under constrained compensation Some next steps Minimal-Abort-Possibility scheduling algorithms Cost constraints Integration with web services execution engine

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