8490795
A Bayesian knowledge engineering framework for service management
Service management is becoming more and more important within the area of IT service management. How to efficiently manage and organize service in complicated IT environments with frequent changes is a challenging issue. Service and the related information from different sources are characterized as diverse, incomplete, heterogeneous, and geographically distributed. It is hard to consume these complicated data without knowledge assistant. To address this problem, a knowledge engineering framework is proposed to tackle the challenges of acquisition, structuring and refinement of structured knowledge regarding existing different unstructured information resource, and the Bayesian network is utilized as the knowledge model. This framework can be successfully applied on key tasks in service management, such as problem determination and change impact analysis. And a real example of Cisco VoIP system is introduced to show the usefulness of this method.
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.
5812455
Knowledge Enhanced IT Service Management
To manage the increasing complexity of IT systems and align IT services with business is the main theme of IT Service Management (ITSM). Current ITSM architecture adopts ITU as the framework to integrate silos of operational management tools and configuration information to build an end-to-end solution based on best practices. However, it lacks of a systematic means to address an important aspect of IT operation, i.e., managing the knowledge separated in various tools and experts' minds. In this paper, a novel knowledge-enhanced architecture is proposed to improve the effectiveness and efficiency of ITSM. The essential contribution of this novel architecture is to involve a Knowledge Management Database (KMDB) which provides assistance for knowledge capture, mining, storage and sharing. The paper will discuss an approach of how to construct such a KMDB with motivating scenarios and detailed description of key components. To validate the approach, a prototype system is developed and evaluated by being applied for problem analysis on a Cisco Voice over IP (VoIP) system. The experiment results show a remarkable improvement in the effectiveness and efficiency for practical IT service management operations.
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.
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.
10702245
A wireless LAN-based indoor positioning technology
Context-aware computing is an emerging computing paradigm that can provide new or improved services by exploiting user context information. In this paper, we present a wireless-local-area-network-based (WLAN-based) indoor positioning technology. The wireless device deploys a position-determination model to gather location information from collected WLAN signals. A model-based signal distribution training scheme is proposed to trade off the accuracy of signal distribution and training workload. A tracking-assistant positioning algorithm is presented to employ knowledge of the area topology to assist the procedure of position determination. We have set up a positioning system at the IBM China Research Laboratory. Our experimental results indicate an accuracy of 2 m with a 90% probability for static devices and, for moving (walking) devices, an accuracy of 5 m with a 90% probability. Moreover, the complexity of the training procedure is greatly reduced compared with other positioning algorithms.
44811386
Classification of Polarimetric SAR Data Based on Multidimensional Watershed Clustering
This paper proposes a polarimetric synthetic aperture radar (PolSAR) data classification method which applies multi-dimensional transform to identify density peaks and valleys for polarimetric signatures clustering. The new approach firstly introduces an improved maximum homogeneous region filter which can effectively preserve structure feature and polarimetric signatures. Then polarimetric signatures are extracted based on Freeman-Durden three-component composition. Finally, we obtain the classification results by multi-dimensional watershed clustering on the extracted polarimetric signatures. The effectiveness of this classification scheme is demonstrated using the full polarimetric L-band SAR imagery.
16326025
Research on Positioning Technology of Xinjiang Mobile GIS
In this paper, the characteristics of Xinjiang mobile communication network are analyzed, the results show that for a reliable mobile communication network, BS (base station) and base station control BSC (base station controller) monitoring system, cable and fiber optic cable monitoring system and mobile communications troubleshooting and dispatching system should be built. Combined with GIS, GPS, GSM and geographic database technology, positioning technology for different targets and detection on fault point are studied, the results indicate that precise positioning of static target can accurately locate the failure telecom equipment in the electronic map and provide data source for the realization of real-time monitoring and management system for telecom equipment based on GIS & wireless sensor network technology. GSM-based wireless messaging communications and real-time fast positioning of dynamic target is the key to the emergency repair vehicles monitoring and dispatch system. The proposed fault determination and fault point location method can provide fast accurately fault devices location with detailed geography information and prompt the efficiency of fault management and improve the reliability of telecom network services. The above research results are important basis on the design and implementation of the system.
15067408
Adapting LDA Model to Discover Author-Topic Relations for Email Analysis
Analyzing the author and topic relations in email corpus is an important issue in both social network analysis and text mining. The Author-Topic model is a statistical model that identifies the author-topic relations. However, in its inference process, it ignores the information at the document level, i.e., the co-occurrence of words within documents are not taken into account in deriving topics. This may not be suitable for email analysis. We propose to adapt the Latent Dirichlet Allocation model for analyzing email corpus. This method takes into account both the author-document relations and the document-topic relations. We use the Author-Topic model as the baseline method and propose measures to compare our method against the Author-Topic model. We did empirical analysis based on experimental results on both simulated data sets and the real Enron email data set to show that our method obtains better performance than the Author-Topic model.
3839837
Creating Vulnerability Signatures Using Weakest Preconditions
Signature-based tools such as network intrusion detection systems are widely used to protect critical systems. Automatic signature generation techniques are needed to enable these tools due to the speed at which new vulnerabilities are discovered. In particular, we need automatic techniques which generate sound signatures - signatures which will not mistakenly block legitimate traffic or raise false alarms. In addition, we need signatures to have few false negatives and will catch many different exploit variants. We investigate new techniques for automatically generating sound vulnerability signatures with fewer false negatives than previous research using program binary analysis. The key problem to reducing false negatives is to consider as many as possible different program paths an exploit may take. Previous work considered each possible program path an exploit may take separately, thus generating signatures that are exponential in the size of the number of branches considered. In the exact same scenario, we show how to reduce the overall signature size and the generation time from exponential to polynomial. We do this without requiring any additional assumptions, or relaxing any properties. This efficiency gain allows us to consider many more program paths, which results in reducing the false negatives of generated signatures. We achieve these results by creating algorithms for generating vulnerability signatures that are based on computing weakest preconditions (WP). The weakest precondition for a program path to a vulnerability is a function which matches all exploits that may exploit the vulnerability along that path. We have implemented our techniques and generated signatures for several binary programs. Our results demonstrate that our WP-based algorithm generates more succinct signatures than previous approaches which were based on forward symbolic execution.
8760513
The Design of a Nanometer Biosensor and Its Microfluidic Integration