Mdeling,Service Planning And Service Composition In Knowledge-intensive Collaborative Workflows

Business Process Management (BPM) has gradually been incorporated into the core strategic objectives of enterprises according to a research report of Gartner in2009. BPM is facing an unprecedented development opportunity. However, with the increasing knowledge collaboration and innovation activities of enterprises and organizations in the knowledge-based economy environment, traditional workflow management theories, methods and tools are facing enormous challenges.Innovation activities of enterprises in the context of the knowledge-based economy involve complex content-oriented, knowledge-intensive collaboration processes of multi-role, cross-organizational knowledge-based cooperation. Cross-organizational knowledge-intensive workflows are combination of the traditional workflow management system and knowledge management system. They not only support and manage the complex business collaboration relations, but also control and coordinate the whole lifecycle of knowledge including its creation, transferring and updating.Most workflow model and management system is designed to support management of mature products manufacturing process with fixed business objectives and unchangeable realization path, mainly focusing on the automation of activities of sequential, parallel and semi-automatic structure. Traditional workflow model is difficult to cope with complex cross-organizational, multi-role, and knowledge-intensive tasks’modeling and management. The main issues to be resolved include dynamic allocation of roles, tasks and resources in a collaborative process model which combines knowledge resource modeling and workflow process modeling, as well as knowledge-based collaborative lifecycle management.Traditional E-Learning system focuses on the construction of course resources and its representation techniques based on multimedia technologies on the internet, supporting teaching, learning and evaluation activities. These systems ignore the process management and monitoring of learning activities and multi-entity collaboration and knowledge-oriented cooperation. Workflow technologies are introduced into development of E-Learning system, make use of existing IT infrastructure of enterprises and organizations, and integrate the learning process into the enterprise workflows. Commercial workflow management software and traditional workflow modeling techniques are building upon the static structure of process, and its formal description is accurate and easy to implement and manage, but inevitably make process "rigid" which is difficult to be changed flexibly. It is hard to realize context-aware adaptive learning and knowledge recommendation mechanism in the stage of knowledge sharing and dynamic creation of tasks.To solve these issues the combination of modeling, management and collaboration of learning resources and learning processes is a must by using new technologies and new modeling techniques which can help to support reuse and accumulation of knowledge resources, to meet the knowledge needs of members of businesses and organizations, to providing personalized, context-aware knowledge filtering, pushing or recommendation mechanisms and to support creative knowledge based collaborative learning.Semantic web and ontology based modeling technology can be used to annotate and semantically model knowledge resources, build a unified, abstract and high level ontology based knowledge base. By using semantic query and reasoning technology, personalized user-oriented knowledge can be extracted from the ontology based knowledge base according to context information in dynamic learning environment.In content-oriented knowledge-intensive collaborative complex applications, specific business operations of enterprises and organizations will change oftenly because the user needs and business goals inside and outside the collaborative relationship of enterprises and organizations are highly viable. Process designers can not pre-define all aspects of a process model given a static process template of fixed structure. With changing user needs and business objectives, original static process template may not be applicable in a new situation.Automatic service planning in workflow is to automatically generate services execution sequence by using artificial intelligence planning techniques suited for changeable structure and patterns in workflow, create object-driven sub process instances on demand and traditional workflow can be used to control fixed activities at high level.Planning graph, HTN and their extensions or combinations are widely used in the field of automatic service planning. However, these methods focus on realization and application of service composition planing and optimization of the planning algorithm at low level, do not take into account the user needs and business objectives in the service planning at high level. Composition services which meet user needs and business objectives can not only rely on the field of artificial intelligence planning but also need more and specific research on related areas and technologies.In cross-organizational multi-entity collaboration workflows, service nodes composition problem not only involve the logical sequence relations (structural characteristics) of the flow among service nodes, but also relate to existing service node selection and optimization of the huge number of candidate services. Workflow instance to be instantiated by the workflow engine after modeling and verification needs to be bind to concrete service node object (task execution entity) based on business constraints and resource constraints to meet the functional requirements. But how to choose and compose these candidate service objects with same functionality but different QoS (Quality of Service) to make optimized compostion process instance is the key problem to research on.Innovation of this thesis mainly including:Firstly, a hierarchical colored Petri-net based Resource-oriented Collaborative Workflow model (ROCWF), its resource control model (Task Resource Multi-role Collaboration Model, TRRC) and the joint modeling method are proposed which support roles, tasks and resources association and perception. In order to reduce the complexity of modeling and verification, process validation task is divided into backbone process validation and tasks verification of sub-process, corresponding color-set definitions and validation rules are given. A dynamic task scheduling algorithm and corresponding hierarchical colored Petri-net model supporting role and resource awareness are designed. The thesis also analyzed and discussed the implicit parallel process execution in multi-thread task workflow. A virtual resource abstraction layer is introduced to put structured, semi-structured and unstructured resources and metadata resources into a unified management perspective, then a metadata-driven workflow’s process instance and task instance level resources collaboration and management mechanisms are designed and implemented. By using Java reflection mechanism and XStream, an Enterprise Service Bus and dynamic service agent design pattern based service interface is implemented to simplify asynchronous service integration inside or outside of the system.Semantic web and ontology modeling and semantic annotation of learning resources is used within the E-Learning system, proposed a recommendation method based on the learner’s cognitive model and preferences to provide personalized content in workflow. Two common learning cognitive types and the corresponding specific cognitive process models are proposed including preference-oriented learning processes and topic-oriented learning process. In learning resources library, the learning content domain model is defined including semantic annotations of learning content, learning preferences, learning topics, and learning cognitive processes. User context and process context is used to construct semantic query on knowledge base and generate personalized recommended learning content in three dimensions of the cognitive processes, preferences and topics.Secondly, a goal-driven, content-oriented collaboration extended model and method (GCCHTN) of hierarchical task network planning is proposed and implemented which can be used to support automatic service planning in knowledge-oriented collaborative workflows. The HTN operators are designed based on generic and reusable principles to cope with the mapping relationships of the hierarchical objectives, contents and tasks according to their formal model of the problem definition and semantic relations. The algorithm is designed to conduct content and task decomposition based on principles about how to achieve the goal of the task, perform the task to achieve the goal, what is the relationship of the content to the task and how the task generate the content designed algorithm. At runtime it supports dynamic, on-demand HTN task network decomposition. Composite task can be dynamically generated according to different environmental parameters and requirements, so as to overcome the shortcomings of traditional HTN and SHOP2which need to explicitly pre-define Method and Operator. The core of planning method is "task implementation method", which provides extension points used to embed custom static and dynamic specific methods and operators.Finally, in cross-organizational knowledge-oriented collaborative multi-entity workflow, this thesis introduces the quality of information and collaborative degree in its QoS computation model. Triangular fuzzy numbers are used to describe the uncertainty of QoS attributes, and an improved fuzzy analytic hierarchy process is applied to the calculation of QoS to construct fuzzy QoS weights integrated with user preferences, these strategies can reduce the amount of human task and improve the evaluation accuracy. Based on service providers’relations of the service objects, a calculation method of the composition process collaboration degree is proposed to avoid difficulty and infeasibility of traditional computation method. The collaboration degree of binding compositon process instance can be obtained by combining the service providers collaboration weight matrix of the binding process instance with the service node emergence probability.In the research of optimization algorithm of automatic service composition, this thesis proposed an improved genetic algorithm which is composed of single point uniform distribution mutation strategy, crossover, mutation and2-tournament selection strategy, maximum dimension multi-point crossover strategy, and short-term memory injection strategy. An improved clonal selection algorithm is proposed as well by using uniform distribution mutation strategy, short-term memory injection and maximum dimension multi-point crossover strategy. The improved clonal selection algorithm is used to improve the immune memory clonal programming algorithm.Based on the improved immune memory clonal programming algorithm, a hybrid clonal strategy and selective parallel cooperation based short-term memory injection clonal selection algorithm (ParaCoSIMCSA) is proposed. ParaCoSIMCSA algorithm not only can be configured easily, with high parallel efficiency and ease of use, but also combines the advantages of polyclonal and monoclonal, with better ability to jump out of local minima, so it appears to be a stable and robust discrete optimization algorithm.