14513982
An Online Model Checking Tool for Safety and Liveness Bugs
Modern software model checkers are usually used to find safety violations. However, checking liveness properties can offer a more natural and effective way to detect errors, particularly in complex concurrent and distributed e-business systems. Specifying global liveness properties which should always eventually be true proves to be more desirable, but it is hard for existing software model checkers to verify liveness in real codes because doing so requires finding an infinite execution. For solving such a challenge, this paper proposes an online checking tool to verify the safety and liveness properties of complex systems. We adopt the linear temporal logic to describe the semantics of the finite model checking, use binary instrumentation to obtain the distribute states and apply a checking engine to dynamically verify the finite trace linear temporal logic properties. At last, we demonstrate the method in a distributed system using distributed protocol Paxos and achieve good results by experiments.
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.
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.
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.
11622519
Applying Knowledge Sharing for Business Intelligence Collaboration
IT services need an automatic and flexible ability to react to dynamic changes in their environment. Managing change effectively and reducing the negative effects of day-to-day operations has become one of the most important tasks in IT service management, which require hiring highly skilled IT professionals with correspondingly high labor costs. There is a challenge to select, implement and integrate the right resources quickly and effectively. Although there is a growing body of research into IT management, many techniques are either too narrow (focusing on a single component rather than the entire system), or they address only configuration data collection and integration. Instead, one needs to scale or respond to special domain knowledge, collaboration and the right data for helping IT professionals to improve their work. In this paper, we propose a knowledge-sharing based collaborating management system for IT service management. It aims to bridge the gap between domain experts’ knowledge and manageable systems. We developed a proof-of-concept of an impact analysis service based on knowledge-sharing; it establishes an IT service management collaboration paradigm and ecosystem, leveraging the expert’s rich knowledge and experience to improve the management quality and reduce the cost. A case study driven by customers demonstrates that collaboration with knowledge sharing is effective both at constructing useful system analysis services and in using those services to improve system management.
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.
10224186
Bandwidth Selection and Reconstruction Quality in Point-Based Surfaces
We investigate the influence of bandwidth selection in the reconstruction quality of point-based surfaces. While the problem has received relatively little attention in the literature, we show that appropriate selection plays a significant role in the quality of reconstructed surfaces. We show how to compute optimal bandwidths for one class of moving least-squares surfaces by formulating the polynomial fitting step as a kernel regression problem for both noiseless and noisy data. In the context of Levin's projection, we also discuss the implications of the two-step projection for bandwidth selection. We show experimental comparisons of our method, which outperforms heuristically chosen functions and weights previously proposed. We also show the influence of bandwidth on the reconstruction quality of different formulations of point-based surfaces. We provide, to the best of our knowledge, the first quantitative comparisons between different MLS surface formulations and their optimal bandwidths. Using these experiments, we investigate the choice of effective bandwidths for these alternative formulations. We conclude with a discussion of how to effectively compare the different MLS formulations in the literature.
28870218
An algorithm for optimal difference systems of sets
Abstract
Difference Systems of Sets (DSS) are combinatorial structures that generalize cyclic difference sets and are used in code synchronization. A DSS is optimal if the associated code has minimum redundancy for the given block length n, alphabet size q, and error-correcting capacity ρ. An algorithm for finding optimal DSS is presented together with tables of optimal solutions found by this algorithm.

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.
17568245
Security metrics for software systems
Security metrics for software products provide quantitative measurement for the degree of trustworthiness for software systems. This paper proposes a new approach to define software security metrics based on vulnerabilities included in the software systems and their impacts on software quality. We use the Common Vulnerabilities and Exposures (CVE), an industry standard for vulnerability and exposure names, and the Common Vulnerability Scoring System (CVSS), a vulnerability scoring system designed to provide an open and standardized method for rating software vulnerabilities, in our metric definition and calculation. Examples are provided in the paper, which show that our definition of security metrics is consistent with the common practice and real-world experience about software quality in trustworthiness.
8140967
Character-like region verification for extracting text in scene images
This paper proposes a method of identifying character-like regions in order to extract and recognize characters in natural color scene images automatically. After connected component extraction based on a multi-group decomposition scheme, alignment analysis is used to check the block candidates, namely, the character-like regions in each binary image layer and the final composed image. Priority adaptive segmentation (PAS) is implemented to obtain accurate foreground pixels of the character in each block. Then some heuristic meanings such as statistical features, recognition confidence, and alignment properties, are employed to justify the segmented characters. The algorithms are robust for a wide range of character fonts, shooting conditions, and color backgrounds. Results of our experiments are promising for real applications.