14490221
Exploiting Request Characteristics to Improve Performance of Web Services Based Business Applications
Web Services and workflow have been widely adopted in building complicated business systems. In these systems, high security concern is claimed. But frequent authentication and computing-intensive encoding and decoding operation bring extra workload to the systems and greatly impact the performance of Web Services and workflow engine, especially under heavy load. In this paper, we propose Requests Automated Binding Mechanism, RABM, to automatically pack the requests from multiple clients but to a common target service in a short time period into one SOAP message, then sent by the workflow engine at runtime. Extra security operation costs are reduced without modifying of application programs. We use the Travel Service provided by W3C to evaluate RABM. As the experiment result shows, we can achieve up to 130% improvement of throughput and lower the average response time to 41%1.
3219653
Key Elements Tracing Method for Parallel XML Parsing in Multi-Core System
Though XML is applied intensively in a lot of applications, XML parsing is not practical in many fields because of its poor performance. Parallel XML parsing on multi-core is a promising choice. Previous methods all adopt data parallel approach on XML parsing. As the semi-structured nature of XML, they were obliged to divide the data into well-formed XML chunks and then parse these chunks parallel. The division process is named as preparsing. As the preparsing is serial, it becomes the bottleneck of parallel XML parsing. Related work Simultaneous Finite Transducer (SFTXP) parallelized the preparsing stage. It maintained multiple preparser results for each equal sized chunk according to enumerated all possible parsing states. In spite of finite states for each XML, the overhead by SFTXP is tremendous, including CPU time and memory for multiple results generating and storing, respectively. In this work, we address parallel XML parsing by Key Element Parse Tracing (KEPT) method which parallelizes the preparsing and parsing at element level. It remolds the preparsing as a key element extracting process and schedules the processing of key elements in the framework of KEPT. Then parsing process is parallelized as a whole. To demonstrate the effectiveness, we implement it on libxml2 and obtain good scalability on both an 8-core Linux machine and an 8-core 24 SMT Sun machine running Solaris.
10926021
Agora: Grid Community in Vega Grid
In grid environment, how to organize, discover and use grid resources is one of the basic research problems. In this paper, we introduce a new concept called agora, which refers grid community in our Vega grid project. We propose a principle on agora as one of the basic design principles of Vega grid, which is the community principle. We give a detailed definition of the agora as a 4-tuple(S, O, C, P), representing the set of Subject, Object, Context, and Policy respectively. Our research methodology is comparative studies, drawing an analog between the grid and other platform systems such as OS, CPU, and MPI. We also study some properties about the agora, for example, grid law of inertia. This agora approach could be used to unify the grid invariability and dynamic variability effectively, develop the appropriate technology to support the dynamic and open properties of the grid, and deal with the complexity in the grid more efficiently.
31706841
A Fast Subspace Clustering Algorithm Based on Pattern Similarity
Traditional clustering models define similarity by distance over dimensions. However, distance functions are not always adequate in capturing correlations among the objects. Pattern-based clustering can discover this kind of clusters. But state-of-the-art pattern-based clustering methods are inefficient and haven't criteria to evaluate the quality of clusters. This paper presents a novel pattern similarity-based subspace clustering with the pattern tree (PPSC for short) that offers these capabilities. The method uses new evaluation criteria to discover best clusters, which enables user to find clusters according to different needs. Meanwhile, observing the analogy between mining frequent itemsets and discovering subspace clusters around random points, we apply the pattern-tree to determine subspace by scanning the database once, so it can perform efficiently in large datasets.
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.
27202859
Affective interaction based on person-independent facial expression space
This paper proposes a person-independent facial expression space (PIFES) to analyze and synthesize facial expressions based on supervised locality preserving projections (SLPP), which aligns different subjects and different intensities of facial expressions on one generalized expression manifold. Interactive curves of different patterns are generated according to the input facial expression image sequence, and target responsive expression images are synthesized for different emotions. In order to synthesize arbitrary expressions for a new person with natural details, a novel approach based on local geometry preserving between the input face image and the target expression image is proposed. Experimental results clearly demonstrate the efficiency of the proposed algorithm.
13862518
Low Cost Mechanism for QoS-Aware Re-Planning of Composite Service
To meet the business and user requirements, it is crucial to manage the Quality of Service (QoS) of composite web service. Due to the dynamics nature of the web services, the runtime behavior of web services is likely to differ from the initial estimated one. Therefore, a re-planning to adapt the composite service to the QoS violated services, ensuring the global constraints and preferences will be needed. In this paper, we propose a low cost mechanism for re-planning. Such mechanism is supported by an offline re-planning execution environment and a performance prediction based low cost policy.The experimentations show better performance of the mechanism.
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.