14899060
Automatic model-based service hosting environment migration
The proper operation of Service-Oriented Architecture (SOA) depends on underlying system services of operating systems, so efficient and effective migration of Service Hosting Environment is critical to cope with intrinsic-changed nature of SOA. However, due to the large amount of configuration items, complicated mapping and complex dependency relationship among system services, migrating into a new Service Hosting Environment satisfying the operation requirement of SOA becomes an error-prone and time-consuming task. The SCM project in IBM develops a novel approach to migrate Service Hosting Environment shaped in Unix-like systems. Firstly, this approach builds a set of configuration models to describe various system services. Then based on models, it presents knowledge based mapping to translate system service configurations between Service Hosting Environments. Finally, it designs a dependency hierarchy deducting algorithm to compute the dependency relationship among system services for migration traceability and error determination. A SCM prototype has performed well on largely reducing time, labor and errors in real migration cases.
15246145
A comprehensive semantic-based resource allocation framework for workflow management systems
Resource allocation that targets to assign the appropriate resource to the dynamically generated work item has always been a critical issue in the workflow management system research. However, today's workflow systems almost still depend on the static literal-based matchmaking mechanism to support the resource allocation, which would suffer greatly from the diversity and mutability of resources in current open and dynamic network environment. In this paper, we propose a comprehensive semantic-based resource allocation framework to enhance the matchmaking process. The essential contributions of this framework are: firstly, an OWL ontology is provided to describe available resources based on their semantic information. Secondly, based on the ontology, effective semantic reasoning techniques are used to select the eligible resource candidates. Thirdly, a bidding approach is adopted to further optimize the resource selection according to runtime conditions such as duration, cost and etc., which would typically overcome the inaccurate assignment based on pure static information in previous study.
8395605
FLTL-MC: Online High Level Program Analysis for Web Services
Although Java- or .NET- centric technologies are the most commonly used in Web services, they are by no means the only ones in practice. This paper proposes an online finite model checking tool FLTL-MC to check the high level safety and liveness properties in complex distributed web service systems, which can offer both a richer and more natural way to search errors. Liveness properties can specify desirable system behaviors which must be satisfied eventually, but are not always satisfied. Existing software model checkers cannot verify liveness in real code because doing so requires finding an infinite execution that does not satisfy aliveness property. In our proposed model, we adopt the finite linear temporal logic to specify the semantics of the online model checking, use binary instrumentation to obtain the distribute states and apply the FLTL-MC engine to dynamically verify the finite linear temporal logic properties in Web service systems. At last, we investigate the well-known distributed protocol WS-Reliable Messaging to demonstrate its applications and detect some hidden bugs with our prototype system.
189947
Evaluating Service Identification with Design Metrics on Business Process Decomposition
One of the key activities to construct a successful Service-Oriented Architecture (SOA) is the identification of services with the right level of abstraction. Most of existing SOA design methodologies advocate identifying services from the top-down decomposition of business processes. However, the identification quality in these methodologies heavily depends on the expertise and experience of individual designers. The ability to quantitatively evaluate service identification is absolutely needed. In this paper, we propose an approach that supports such evaluation by applying the measurement technology to the service-based business process decomposition. A model to capture related architectural elements with their relationships is presented. A set of design metrics are proposed for measuring various features of identified services in the service portfolio, including service granularity, coupling, cohesion, and business entity convergence. To apply the approach, a prototypical measurement tool for service identification is developed. An automotive work order scenario is used as an illustration example to explain our approach and demonstrate its effectiveness.
12111515
Algorithm of integrating QFD and TRIZ for the innovative design process
TRIZ, the Russian acronym of the Theory of Inventive Problem Solving, is a useful tool that can solve the problem of "how to do" effectively in the innovative design process, while QFD (Quality Function Deployment) is able to settle the problem of "what to do". Although the potential of using both QFD and TRIZ in the product design process is huge, there are little tools to integrate these two methods effectively. In this research, we describe an algorithm that can integrate QFD and TRIZ effectively for the purpose of the innovative design process. The core of the algorithm is to identify the contradictions in TRIZ by defining rules based on HOQ (House of Quality) in QFD. A software tool called TRIZmatrix is developed based on this algorithm. Application of the algorithm to the case of the airbag problem is studied in detail. The software application and the case study show the advantage of this algorithm for CAI (computer aided innovation) software development.
15004157
A Semantic QoS-Aware Discovery Framework for Web Services
Augmenting web services with explicit semantics forms the foundation of Service Oriented Architectures (SOAs) automation. As more and more Semantic Web Services (SWSs) are deployed, similar SWSs could have quite different quality-of-service (QoS) levels. The QoS-aware discovery becomes an important challenge. While some efforts try to solve it via Constraint Programming (CP), they suffer from the purely syntactic matchmaking method. Furthermore, the construction of constraints and the selection of services are completely dependent on the literal translation from QoS descriptions, which increase obstacles to actually apply CP. In this paper, we propose a semantic QoS-aware framework for SWSs discovery by combining the semantic matchmaking and CP. Initially, a QoS ontology is presented to define QoS data into service descriptions. Then the ontology reasoning is adopted to change previous syntactic matchmaking into a semantic way. Through confirming the compatibility of concepts, complex QoS conditions are solved as constraints and a selection algorithm is proposed to obtain the optimal offer. Finally, the prototype implementation of our framework is discussed and a SWSs discovery case is used to illustrate the comprehensive discovery process.
7625765
Solving QoS-driven Web service dynamic composition as fuzzy constraint satisfaction
The creation of value-added composite web service raises an opportunity to the formation of online B2B collaborations. However, web services are usually overlapping in functionality. How to make a choice based on non-functional factors becomes a problem that needs to be solved. In this paper, it argues that the selection of component services should be considered in a global manner and the user's QoS preferences is more appropriate to be expressed in a fuzzy way. It advocates using fuzzy set to express the user's QoS preference on a specific QoS criteria and using fuzzy expression to express the user's trade-off among QoS criteria's. The service selection problem is formalized as a fuzzy constraint satisfaction problem and deep-first branch-and-bound method is chosen to search for a solution with some adjustments to web service composition. It also develops an uncritical fuzzy consistency checking algorithm as an aid to faster search. Experiments are conducted to prove the effectiveness of the approach.
940637
Apply ant colony optimization to Tetris
Tetris is a falling block game where the player's objective is to arrange a sequence of different shaped tetrominoes smoothly in order to survive. In the intelligence games, agent imitates the real player and chooses the best move based on a linear value function. In this paper, we apply Ant Colony Optimization (ACO) method to learn the weights of the function, trying to search an optimal weight-path in the weight graph. We use dynamic heuristic to prevent premature convergence to local optima. Our experimental result is better than most of traditional reinforcement learning methods.
17038094
On-line Algorithm for Server Selection of Video Streaming over P2P Networks
Abstract We consider a video streaming application over P2Pnetworks and introduce the P2P on-line server selection problem. This task is related to the classic K-server problem, known from the theory of online algorithms. The difference is that our problem has a dynamic cost matrix, due to network congestion which may trigger the rerouting of streaming paths. With the assumption that the number of hops of any alternative path from the server node p to the requesting node q is at most δ times the number of hops of the shortest path from p to q, our dynamic work function algorithm works for the P2P on-line server selection problem with competitive ratio δ×(2k-1). 1. Introduction In this paper we consider a video streaming application over P2Pnetworks. As we know, it isdifficult to provide large scale streaming service using traditional, centralized client-serverarchitecture, since a bottleneck occurs at the server. The network service model known as Peer-to-Peer (P2P) solves this problem, due to its distributed nature. We address the issue of optimizing the server selection for video streaming in P2P networks.Optimization tasks are classified into online and offline problems. Optimization problems in which the input is received piece by piece and the corresponding piece of output must be produced before knowing the entire input are called online problems. In some optimization tasks, such as job scheduling, both the online and offline versions of the problem are meaningful. Many other situations, such as telephone circuit switching, investment planning etc. are intrinsically online. For these problems, offline algorithms are not acceptable. Competitive algorithms were introduced by Sleator and Tarjan [1] in the context of optimization problems. They sought a worst case complexity measure for on-line algorithms that have to make decisions based on current and previous parts of the input. In the on-line problem the input is given as a sequence σ = σ
38679232
Short Definitions of the Ordinals
In this paper, a simple inductive characterization of the ordinal numbers is stated and developed. The characterization forms the basis for a set of axioms for ordinal theory and also for several short explicit definitions of the ordinals. The axioms are shown to be sufficient for ordinal theory, and, subject to suitable existence assumptions, each of the definitions is shown to imply the axioms. The present results apply to the familiar von Neumann version of the ordinals, but the methods used are easily adapted to other versions. ? 1. Axioms for ordinal theory. According to the usual interpretation, each ordinal is the set of all lesser ordinals. Thus zero is the empty set A, a successor ordinal x' is x U {x} for some ordinal x, and a limit ordinal is a set w of ordinals that is equal to its own sum set Zw. In fact, the class On of all ordinals might be characterized informally as the smallest class Z such that (1) AEZ, (2) (y) (yEZ D y'EZ), and (3) (w) (1w = w c Z D wEZ). More simply, On can be characterized as the smallest Z such that
45158244
Discovering pattern-based subspace clusters by pattern tree
Traditional clustering models based on distance similarity are not always effective in capturing correlation among data objects, while pattern-based clustering can do well in identifying correlation hidden among data objects. However, the state-of-the-art pattern-based clustering methods are inefficient and provide no metric to measure the clustering quality. This paper presents a new pattern-based subspace clustering method, which can tackle the problems mentioned above. Observing the analogy between mining frequent itemsets and discovering subspace clusters, we apply pattern tree - a structure used in frequent itemsets mining to determining the target subspaces by scanning the database once, which can be done efficiently in large datasets. Furthermore, we introduce a general clustering quality evaluation model to guide the identifying of meaningful clusters. The proposed new method enables the users to set flexibly proper quality-control parameters to meet different needs. Experimental results on synthetic and real datasets show that our method outperforms the existing methods in both efficiency and effectiveness.