12211000
Intelligent Agent Supported Business Process Management
The complex business environment requires managing business processes with the ability to adapt to changes and to collaborate in activities. Conventional workflow approaches based on predefined logical procedure offer little support for the dynamic business environment. A cognitive agent-based approach is proposed to manage business activities based on situational awareness and real-time decisions on activities. Business activities are delegated to a number of cognitive and collaborative problem-solving agents. Each software agent perceives its environment by capturing events and monitoring the state of tasks and resources. Based on the continuous perception of environment, business rules concerning process routing, operational constraint, exception handling and business strategy are used by such software agents to perform appropriate actions. The mechanism of this approach is investigated, and a case application of exception management in securities trading is developed to demonstrate the validity and benefits of this approach.
7484569
The design of intelligent workflow monitoring with agent technology
In recent years, workflow technology has been widely used in business process management. With the increased complexity, uncertainty and risks in business operations, workflow monitoring is gaining growing attention in business process controlling and supervision. However, monitoring functions provided in traditional workflow systems lack flexibility, and provide little support for managing complex and dynamical changes in business process. In this paper, we propose a novel workflow monitoring approach, in which various intelligent agents work together to perform flexible monitoring tasks in an autonomous and collaborative way. By using customized monitoring plan and proactive monitoring process, the workflow monitoring activities can be executed flexibly and efficiently. The application of intelligent agents for such flexible, adaptive and collaborative workflow monitoring is investigated through an intelligent monitoring system in securities trading.
231152
Capturing the spatio-temporal behavior of real traffic data
Traffic data, such as disk and memory accesses, typically exhibits burstiness, temporal locality, and spatial locality. However, except for qualitative speculations, it is not even known how to measure the spatio-temporal correlation, let alone how to re-produce it realistically. In this paper, we propose the "entropy plots" to quantify the correlation and develop a new statistical model, the "PQRS" model, to capture the burstiness and correlation of the real spatio-temporal traffic. Moreover, the model requires very few parameters and offers linear scalability. Experiments with multiple real data sets show that our model can mimic real traces very well.
612178
A learning-based approach to estimate statistics of operators in continuous queries: a case study
Statistic estimation such as output size estimation of operators is a well-studied subject in the database research community, mainly for the purpose of query optimization. The assumption, however, is that queries are ad-hoc and therefore the emphasis has been on capturing the data distribution. When long standing continuous queries on a changing database are concerned, a more direct approach, namely building an estimation model for each operator, is possible. In this paper, we propose a novel learning-based method. Our method consists of two steps. The first step is to design a dedicated feature extraction algorithm that can be used incrementally to obtain feature values from the underlying data. The second step is to use a data mining algorithm to generate an estimation model based on the feature values extracted from the historical data. To illustrate the approach, this paper studies the case of similarity-based searches over streaming time series. Experimental results show this approach provides accurate statistic estimates with a low overhead.
15871879
A Growth-Based Address Allocation Scheme for IPv6
IP address allocation policies significantly impact the Internet infrastructure, affecting many parties such as router manufacturers, ISPs, and end users. An address allocation policy can also directly affect the performance of the Internet. For example, address fragmentation, a key problem in IPv4, degrades address lookup performance in routers. Thus, a well-designed address allocation policy needs to minimize fragmentation while using the address space efficiently. 
 
This paper attempts toquantify the performance of address allocation policies by modeling key features that lead to fragmentation and inefficient address space usage. Our main contributions are: (i) we identify a drawback of the current IPv6 address allocation policy, which treats all entities uniformly, (ii) we propose a scheme that takes future growth rate into account for allocations, and (iii) an analytical model for measuring the efficiency of allocation schemes, allowing us to quantify the improvement our proposal offers over the current scheme.We believe that a quantitative study of allocation policies is timely since IPv6 address allocation is just beginning in earnest.
15805455
SciPort: An Adaptable Scientific Data Integration Platform for Collaborative Scientific Research
Scientific data are posing new challenges to data management due to the large volume, complexity and heterogeneity of the data. Meanwhile, scientific collaboration becomes increasingly important, which relies on integrating and sharing data from distributed institutions. In this demo, we present SciPort, a Web-based platform on supporting scientific data management and integration based on peer-to-peer architectures, where researchers can easily collect, publish, and share their complex scientific data across multi-institutions. SciPort provides a general metadata based data model to capture the context description of experiments and link experiment data into comprehensive metadata documents, and supports a hierarchical organization of the overall data space for data browsing. SciPort takes two alternative "peer"-to-"peer" (or peer-database-to-peer-database) based approaches to integrate scientific data: pure peer-to-peer architecture and central server based peer-to-peer architecture. The later provides a virtual view of all published data from multiple local sites and supports complex queries with XQuery. The system provides a unified framework for adaptable architectures and customizable schemas, and supplies comprehensive tool set to manage and share scientific data. SciPort was first prototyped in Siemens Corporate Research, and now becomes a mature product and has been successfully used in both biomedical research and clinical trials for scientific research communities.
19020482
A cost-effective three-in-one personal digital assistant input control
Abstract We attach an inexpensive pressure sensor to the side of a personal digital assistant and use it as three input devices at once. Users can squeeze the device to provide near-continuous input to applications. At the same time the drivers interpret a sudden full squeeze as the push of a virtual button. A user's sudden pressure release while squeezing is detected as the push of a second virtual button. We briefly describe our hardware and signal processing techniques. The remainder of the writing describes an experiment that explores whether users can cope cognitively with the 3-in-1 control. We compare against a three-control setup consisting of a jog wheel and two physical buttons. We show that the three-in-one control enables a 13% faster reaction time over the three-control one, but that the three-in-one control suffers a 4% penalty in the accuracy of users choosing between the two buttons in response to cues from an application. We show that a good choice of application cue is more important for assuring accuracy in the 3-in-1 than in the more traditional set of separate controls.