[1] QoS aggregation for Web service composition using workflow patterns (EDOC, 2004)
这篇论文的笔记点这里.
[2] QoS Aggregation in Web Service Compositions(EEE, 2005)
Michael C. Jaeger, Gregor Rojec-Goldmann, Gero M?, "QoS Aggregation in Web Service Compositions," eee, pp.181-185, 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05), 2005
与EDOC04的区别, 增加了monitoring部分. 通过monitoring获得历史数据, 可以更加精确地估计aggregated QoS of the composition, 对于conditional branches, 可以获得actual distribution.
(S3)提到了Dependency Domain对于估算Reliability的影响.
[3] QoS-aware Composition of Web Services: A Look at Selection Algorithms (ICWS poster, 2005)
Michael C. Jaeger, Gero Muhl, Sebastian Golze, "QoS-Aware Composition of Web Services: A Look at Selection Algorithms," icws, pp.807-808, IEEE International Conference on Web Services (ICWS'05), 2005
service selection in a composition 可以被建模为:
(1) 0/1-Knapsack Problem
(2) Multi-Mode RCPSP(resource constraint project scheduling problem): which has non-regular objectives, specific precedence relation, and no preemption allowed
介绍和比较了4种服务选择的算法
Greedy Selection, Discarding Subsets, Bottom-Up Approximation, Pattern-wise Selection
[4] QoS-aware Composition of Web Services: An Evaluation of Selection Algorithms (OTM, 2005)
Michael C. Jaeger, Gero Mühl, Sebastian Golze: QoS-Aware Composition of Web Services: An Evaluation of Selection Algorithms. OTM Conferences (1) 2005: 646-661
这篇是ICWS poster 05的详细版本
[5] Simulation of Algorithms for the Selection of Web Services for Compositions (TES, 2005)
Michael C. Jaeger, Gregor Rojec-Goldmann: SENECA - Simulation of Algorithms for the Selection of Web Services for Compositions. TES 2005: 84-97
提到了6种服务选择的方法并进行了比较：
Constraint Selection
Bottom-Up Approach
Global Selection
Discarding Subsets
Greedy Selection
Pattern-based Selection
使用了Simple Additive Weighting (SAW) Multiple Criteria Decision Making (MCDM)方法来对多属性的web 服务进行打分
(S3)里提到了模拟的QoS的值，可供参考; 实验参数: 工作流中的任务数为10~25个.
[6] Model-Driven Methodology for Building QoS-Optimised Web Service Compositions (DAIS, 2005)
Roy Grønmo, Michael C. Jaeger: Model-Driven Methodology for Building QoS-Optimised Web Service Compositions. DAIS 2005: 68-82
使用UML来对web service composition建模, model-driven.
(S4)提到了对于并发结构的优化时的一种情况: ws1很快, 所有ws1的备选服务要快于运行速度最快的ws2, 显然, 在选取ws1时, 应该要选择最便宜的服务. 因为运行时间是由ws2来决定的.
解决方法: recursively递归到一个基本结构(比如并发的), 然后群举这个结构所有的Candidate service组合, 得到最优的解, 这样来完成service selection
[7] Improving the QoS of WS compositions based on redundant services (NWESP, 2005)
Michael C. Jaeger and Hendrik Ladner. Improving the QoS of WS Compositions based on Redundant Services. In: Proceedings of the 2005 International Conference on Next Generation Web Services Practices (NWeSP'05), pages 189--194, Seoul, South-Korea, August 2005. IEEE CS Press.
本文简单讨论了使用冗余服务来提高组合服务的QoS(response time, reliability). (S3)讨论了如何找到组合服务中需要改进的weak point, 提出了brute-fource search和pattern-based search(文中讲的不清楚)两种方法. (S4)讨论了使用类似N-Version programming的方法来提高组合服务的QoS.
[8] Modelling of Service Compositions: Relations to Business Process and Workflow Modelling (ICSOC Workshop, 2006)
Michael C. Jaeger: Modelling of Service Compositions: Relations to Business Process and Workflow Modelling. ICSOC Workshops 2006: 141-153
本文要解决两个问题：
(1) what are the differences between business processes and workflow control flow languages
(2) why service compositions are used in this field
[9] QoS-based selection of services: The implementation of a genetic algorithm (KiVS workshop, 2007)
Jaeger, M. C. and M¨uhl, G. 2007. QoS-based selection of services: The implementation of a genetic algorithm. In KiVS 2007 Workshop: Service-Oriented Architectures und Service-Oriented Computing (SOA/SOC), Bern, Switzerland. 359–370.
提出了一个遗传算法进行基于QoS的服务选择, 并和SENECA算法进行了比较.
调查了各种参数对算法的影响; 实现了一个模拟环境, 可以随机产生problem instance.