Model Driven Development of Business Process Monitoring and Control Systems
This paper describes a model-driven approach in monitoring and controlling the behaviour of business processes. The business-level monitoring and control requirements are first described by a series of policies that can be combined together to construct a Directed Acyclic Graph (DAG), which can be regarded as the Platform Independent Model (PIM) for the high level business solution. PIM provides a convenient and clear way for business users to understand, monitor and control the interactions in the target business process. Then the PIM is transformed to an executable representation (Platform Specific Model, PSM), such as BPEL (Business Process Execution Language for Web Service) by decomposing the DAG into several sub-processes and modelling each sub-process as a BPEL process that will be deployed to runtime.

title: Service Selection Algorithms for Composing Complex Services with Multiple QoS Constraints
abstract: One of the promises of the service-oriented architecture (SOA) is that complex services can be composed using individual services. Individual services can be selected and integrated either statically or dynamically based on the service functionalities and performance constraints. For many distributed applications, the runtime performance (e.g. end-to-end delay, cost, reliability and availability) of complex services are very important. In our earlier work, we have studied the service selection problem for complex services with only one QoS constraint. This paper extends the service selection problem to multiple QoS constraints. The problem can be modelled in two ways: the combinatorial model and the graph model. The combinatorial model defines the problem as the multi-dimension multi-choice 0-1 knapsack problem (MMKP). The graph model defines the problem as the multi-constraint optimal path (MCOP) problem. We propose algorithms for both models and study their performances by test cases. We also compare the pros & cons between the two models.

title: Service Selection Algorithms for Web Services with End-to-End QoS Constraints
abstract: Web services are new forms of Internet software that can be universally deployed and invoked using standard protocol. Services from different providers can be integrated to provide composite services. In this paper, we study the end-to-end QoS issues of composite service by utilizing a QoS broker that is responsible for coordinating the individual service component to meet the quality constraint. We design the service selection algorithms used by QoS brokers to meet end-to-end QoS constraints. The objective of the algorithms is to maximize the user-defined utility while meeting the end-to-end delay constraint. We model the problem as the multiple choice knapsack problem (MCKP) and provide efficient solutions. The algorithms are tested for their performance.

title: The Design of QoS Broker Algorithms for QoS-Capable Web Services
abstract: QoS (quality of service) support in Web services is an important issue since it ensures service usability and utility for each client and, in addition, improves server utilization. In this article, we present a QoS-capable Web service architecture, QCWS, by introducing a QoS broker module between service clients and providers (servers). The functions of the QoS broker module include tracking QoS information about servers, making selection decisions for clients, and negotiating with servers to get QoS agreements. We study two resource allocation algorithms (HQ and RQ) used by QoS brokers acting as the front-end of servers. The goals of the algorithms are to maximize the server resource usage while minimizing the QoS instability for each client. The first algorithm, HQ, assigns a homogeneous service level to all clients on the system and adjusts the service level according to the number of active clients. The second algorithm, RQ, assigns different service levels to clients according to their needs. Both algorithms try to minimize the resource reallocations for existing clients. The QoS performance and instability trade-offs are studied by simulation.

title: Service selection algorithms for Web services with end-to-end QoS constraints
abstract: Web services are new forms of Internet software that can be universally deployed and invoked using standard protocols. Services from different providers can be integrated into a composite service regardless of their locations, platforms, and/or execution speeds to implement complex business processes and transactions. In this paper, we study the end-to-end QoS issues of composite services by utilizing a QoS broker that is responsible for selecting and coordinating the individual service component. We design the service selection algorithms used by QoS brokers to construct the optimal composite service. The objective of the algorithms is to maximize the user-defined utility function value while meeting the end-to-end delay constraint. We propose two solution approaches to the service selection problem: the combinatorial approach, by modeling the problem as the Multiple Choice Knapsack Problem (MCKP), and the graph approach, by modeling the problem as the constrained shortest path problem in the graph theory. We study efficient solutions for each approach.

title: Modeling and Measuring Privacy Risks in QoS Web Services
abstract: The privacy issue for QoS Web services is considered. As more Web services are constructed and deployed, many of our personal needs may be served by more than one service providers regardless of their platforms and implementation technologies. Service selection is performed by comparing the QoS attributes of all candidate services. Releasing private data without due control may raise the risk of allowing potential adversaries to collect, reveal or utilize one's data in undesirable ways. We propose a QoS model that quantifies a user's privacy risk in order to make the service selection process manageable. The privacy risk is derived using the percentage of the private data set to be released, and user-defined context-oriented weights that quantify the potential damage of privacy leaking in a specific context. We have included privacy risk cost as one of the QoS parameters by extending the end-to-end QoS composition algorithms developed previously

title: Policy migration for sensitive credentials in trust negotiation
abstract: Trust negotiation is an approach to establishing trust between strangers through the bilateral, iterative disclosure of digital credentials. Under automated trust negotiation, access control policies are associated with sensitive credentials to control under what circumstances those credentials can be disclosed. Ideally, the information in a user's sensitive credential should not be known by others unless the corresponding policy is satisfied. However, the original model for user interaction in trust negotiation has pitfalls which can be easily exploited to infer one's private information, even if access control policies are strictly enforced. To preserve one's privacy, a more flexible interaction model for trust negotiation is required. On the other hand, it is also desirable for two parties to be able to establish trust whenever possible. There is potentially a conflict between privacy preservation and the assurance of a successful trust negotiation. In this paper, we identify the situation where sensitive information can be inferred through observing one's behavior in trust negotiation. Then we propose policy migration as one approach to preventing such inference. Compared to previously proposed approaches, policy migration has a low management overhead, and provides a nice balance between inference prevention and guarantees of success in trust establishment. We also discuss the limitations of policy migration, and possible directions for more comprehensive solutions.

title: Index-based approximate XML joins
abstract: XML data integration tools are facing a variety of challenges for their efficient and effective operation. Among these is the requirement to handle a variety of inconsistencies or mistakes present in the data sets. We study the problem of integrating XML data sources through index assisted join operations, using notions of approximate match in the structure and content of XML documents as the join predicate. We show how a well known and widely deployed index structure, namely the R-tree, can be adopted to improve the performance of such operations. We propose novel search and join algorithms for R-trees adopted to index XML document collections. We also propose novel optimization objectives for R-tree construction, making R-trees better suited for this application.

title: Tracking appearances with occlusions
abstract: Occlusion is a difficult problem for appearance-based target tracking, especially when we need to track multiple targets simultaneously and maintain the target identities during tracking. To cope with the occlusion problem explicitly, this paper proposes a dynamic Bayesian network, which accommodates an extra hidden process for occlusion and stipulates the conditions on which the image observation likelihood is calculated. The statistical inference of such a hidden process can reveal the occlusion relations among different targets, which makes the tracker more robust against partial even complete occlusions. In addition, considering the fact that target appearances change with views, another generative model for multiple view representation is proposed by adding a switching variable to select from different view templates. The integration of the occlusion model and multiple view model results in a complex dynamic Bayesian network, where extra hidden processes describe the switch of targets' templates, the targets' dynamics, and the occlusions among different targets. The tracking and inferring algorithms are implemented by the sampling-based sequential Monte Carlo strategies. Our experiments show the effectiveness of the proposed probabilistic models and the algorithms.

title: A field model for human detection and tracking
abstract: The large shape variability and partial occlusions challenge most object detection and tracking methods for nonrigid targets such as pedestrians. This paper presents a new approach based on a two-layer statistical field model that characterizes the prior of the complex shape variations as a Boltzmann distribution and embeds this prior and the complex image likelihood into a Markov field. A probabilistic variational analysis of this model reveals a set of fixed-point equations characterizing the equilibrium of the field. It leads to computationally efficient methods for calculating the image likelihood and for training the model. Based on that, effective algorithms for detecting nonrigid objects are developed. This new approach has several advantages. First, it is intrinsically suitable for capturing local nonrigidity. In addition, due to the distributed likelihood, this approach is robust to partial occlusions. Moreover, the two-layer structure provides large flexibility of modeling the image observations, which makes the new method robust to clutters. Extensive experiments demonstrate its effectiveness.

title: An identifiability-based access control model for privacy protection in open systems
abstract: We argue that in open systems one's private information disclosure needs to be dynamically controlled based on both its sensitivity and the possibility that a user's identity is revealed. Then we propose an identifiability-based access control scheme, which not only properly control usrers' private information, but also increase users' access to web services.