Browsing by Author "Peter Wurman, Committee Member"

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Commitment-Based Business Process Modelling and Enactment
(2005-04-03) Wan, Feng; Robert St. Amant, Committee Member; Peter Wurman, Committee Member; Munindar P. Singh, Committee Chair; James Lester, Committee Member
Business process management faces challenges in dealing with business abnormalities and ever-changing business requirements. Traditional business process management approaches evolved from software engineering and workflow management where activities, messages and control logic are given prominence. The resulting models specify low-level details of execution and coordination. However, difficulties arise when modelling long-lived business transactions involving information updates and execution exceptions. To handle such situations, current approaches implement excessive activities without suitable abstractions, thereby arbitrarily fragmenting the business requirements. We propose a commitment-based approach for business process modelling that formulates business processes as multiagent systems. Organizational structure and its effect on interactions are described using commitments and causality. Agents act as process executors and maintain the commitments made to each other. Updates and exceptions yield commitment operations under which processes are updated and reexecuted. Our approach brings commitment semantics into business modelling and enables agent collaboration for business process enactment. We derive commitment protocols from agent conversations and generate agent execution models. We also formalize our approach using the Π-calculus and prove its correctness. To demonstrate the practical use of our approach, we formalize multiparty agreements with commitments and present algorithms on how to detect agreement conflicts and build satisfiable commitment sets.
Fault Tolerance and Reliability in Scientific Workflows
(2005-05-31) Mouallem, Pierre; Peter Wurman, Committee Member; Munindar Singh, Committee Member; Mladen Vouk, Committee Chair
The emerging technologies of web services, agents and service-oriented workflows will enable scientific projects and experiments to be conducted on a larger scale than ever before. Data used and produced in such projects and experiments become increasingly complex and heterogeneous. Thus the need for a tool (or a set of tools) to efficiently design, manage and maintain problem solving flows (scientific workflows) using various components. The DOE Scientific Data Management (SDM) initiative aims to develop a framework that helps scientists to manage data in distributed and collaborative environments. It also provides tools that help them create and manage scientific workflows that use network-based (web) services, agent technologies and semantic mediation techniques. The current SDM's framework is known as SPA/Kepler and is Ptolemy II based. One of the vulnerabilities of service dependent workflows is that they require that the web services they use to be available whenever the workflow is run. If key web services are not available, the workflow cannot finish successfully. At that point a scientist using such as service would have to wait for it to be restored, This, of course, impacts workflows reliability and availability, and may be sufficient for an end-user to stop using workflows that use those services.. The work reported here uses the SPA/Kepler framework to explore the issue of reliability of service-based scientific workflows. For example, a workflow that invokes 3 services in a series may have .an acceptably high overall failure probability. This thesis explores the issues related to improvement of the overall workflow reliability using fault tolerance. Specifically, the work focuses on failure-masking and fail-over through redundancy, and in the context of individual services, rather than on provision of checkpointing and recovery.. Analyses show that even a relatively simple redundancy based fault-tolerance approach, such as duplication of key services, can provide an order of magnitude or better reliability. In the context of an actual implementation, one option is to find locations of alternative (functionally equivalent) services during workflow design, and then use that information at run-time if the primary service fails. A more practical method is to publish the list of services used by the workflow to a UDDI type service and have a way of dynamically matching needed services with functionally equivalent ones if a fail-over is required. A prototype solution of the latter, based on a commercially available brokering service, was developed for one of the SDM pilot workflows to show its viability. It is discussed in detail.
Interest-Matching Comparisons using CP-nets
(2007-04-03) Wicker, Andrew White; Jon Doyle, Committee Chair; Robert St. Amant, Committee Member; Peter Wurman, Committee Member
The formation of internet-based social networks has revived research on traditional social network models as well as interest-matching, or match-making, systems. In order to automate or augment the process of interest-matching, we follow the trend of qualitative decision theory by using qualitative preference information to represent a user's interests. In particular, a common form of preference statements for humans is used as the motivating factor in the formalization of ceteris paribus preference semantics. This type of preference information led to the development of conditional preference networks (CP-nets). This thesis presents a method for the comparison of CP-net preference orderings which allows one to determine a shared interest level between agents. Empirical results suggest that distance measure for preference orderings represented as CP-nets is an effective method for determining shared interest levels. Furthermore, it is shown that differences in the CP-net structure correspond to differences in the shared interest levels which are consistent with intuition. A generalized Kemeny and Snell axiomatic approach for distance measure of strict partial orderings is used as the foundation on which the interest-matching comparisons are based.
Utility Guided Pattern Mining
(2004-02-26) Jagannath, Sandhya; Peng Ning, Committee Member; Peter Wurman, Committee Member; Jon Doyle, Committee Chair
This work is an initial exploration of the use of the decision-theoretic concept of utility to guide pattern mining. We present the use of utility functions as against thresholds and constraints as the mechanism to express user preferences and formulate several pattern mining problems that use utility functions. Utility guided pattern mining provides the twin benefits of capturing user preferences precisely using utility functions and of expressing user focus by choosing an appropriate utility guided pattern mining problem. It addresses the drawbacks of threshold guided pattern mining, the specification of threshold and the assumption of a fixed level of interest. We examine the problem of mining patterns with the best utility values in detail. We examine monotonicity properties of utility functions and the composition of utility functions from sub-utility functions as mechanisms to prune the search space. We also present a top-down approach for generating projected databases from FP-Trees, which is an order of magnitude faster than methods proposed in the literature.
Visualization for Combinatorial Auctions
(2006-07-07) Hsiao, Ping-Lin; Christopher G. Healey, Committee Chair; Peter Wurman, Committee Member; Alan L. Tharp, Committee Member
Visualization converts raw data into meaningful graphical images that allow users to rapidly identify and explore values, trends, and patterns in their datasets. Visualization techniques often apply spatial relationships to abstract data to represent the relationships between data elements in a meaningful way. Our specific interest in this thesis is visualizing combinatorial datasets that contain all subsets of a collection of base elements. The combinatorial datasets we study encapsulate results from combinatorial auctions where multiple items are sold simultaneously to multiple bidders. Different bidding strategies and the relationships between them are revealed in our visualizations. We propose a new 2D scheme for concisely visualizing combinatorial datasets. The visualization displays concentric rings composed of arcs, with each base element subset mapped to a single arc. Equal sized subsets are placed on a common ring. The outermost ring contains subsets of size one. Interior rings contain larger subsets. The rings are positioned to try to overlap common base elements as much as possible. This allows viewers to search a local region of the visualization to study the behavior of a given base element (i.e., a given item offered within the combinatorial auction). Additional visual features, including motion, color, and texture are applied to represent auction attributes like the identity of a bidder, which bids win in a particular stage of the auction, and so on. Our visualizations provide viewers with an efficient and effective way to observe how an auction progresses.