37720806
An efficient method for mutual exclusion in truly distributed systems
Many operations in a distributed system require mutual exclusion to guarantee correctness. Quorum methods have been widely proposed for implementing mutual exclusion. Majority voting is the best known quorum method. It has the merit of simplicity, but may incur high message overhead. The tree algorithm is an efficient structured quorum method for mutual exclusion problems. The quorums generated by a tree algorithm are smaller on average than those generated by a majority voting. However, the tree algorithm enforces a highly biased treatment to the nodes at different levels. This affects its performance in a distributed system where the nodes have similar characteristics. We propose a new structured quorum method which treats the nodes more evenly than the tree algorithm yet still preserves a satisfactory availability. We believe that this method is desirable for implementing mutual exclusion in a truly distributed system.<<ETX>>
10131271
Hierarchical Classification of Documents with Error Control
Classification is a function that matches a new object with one of the predefined classes. Document classification is characterized by the large number of attributes involved in the objects (documents). The traditional method of building a single classifier to do all the classification work would incur a high overhead. Hierarchical classification is a more efficient method -- instead of a single classifier, we use a set of classifiers distributed over a class taxonomy, one for each internal node. However, once a misclassification occurs at a high level class, it may result in a class that is far apart from the correct one. An existing approach to coping with this problem requires terms also to be arranged hierarchically. In this paper, instead of overhauling the classifier itself, we propose mechanisms to detect misclassification and take appropriate actions. We then discuss an alternative that masks the misclassification based on a well known software fault tolerance technique. Our experiments show our algorithms represent a good trade-off between speed and accuracy in most applications.
444470
Handling uncertainties in workflow applications
Workflow techniques are currently seen as the key techniques to improve the effectiveness and productivity of business processes. Most workflow models take a static view toward workflow applications. The static view requires that all the components are known in advance and the structural information alone can uniquely determine an execution path. Some applications may not have either or both of these properties. In these applications, uncertainty exists. In this paper, we study the issues related to uncertainties. We characterize uncertainties into three categories, domain uncertainty, structural uncertainty and implementation uncertainty, and discuss the impact they have on workflow specification and implementation. We then propose approaches to coping with each of them.
5173411
Email data cleaning
Addressed in this paper is the issue of 'email data cleaning' for text mining. Many text mining applications need take emails as input. Email data is usually noisy and thus it is necessary to clean it before mining. Several products offer email cleaning features, however, the types of noises that can be eliminated are restricted. Despite the importance of the problem, email cleaning has received little attention in the research community. A thorough and systematic investigation on the issue is thus needed. In this paper, email cleaning is formalized as a problem of non-text filtering and text normalization. In this way, email cleaning becomes independent from any specific text mining processing. A cascaded approach is proposed, which cleans up an email in four passes including non-text filtering, paragraph normalization, sentence normalization, and word normalization. As far as we know, non-text filtering and paragraph normalization have not been investigated previously. Methods for performing the tasks on the basis of Support Vector Machines (SVM) have also been proposed in this paper. Features in the models have been defined. Experimental results indicate that the proposed SVM based methods can significantly outperform the baseline methods for email cleaning. The proposed method has been applied to term extraction, a typical text mining processing. Experimental results show that the accuracy of term extraction can be significantly improved by using the data cleaning method.
59732955
What video can and can't do for collaboration: a case study
4332072
A Component Retrieval Method Based on Facet-Weight Self-learning
Component-based development method has been a new software development paradigm. How to get the needed components quickly and accurately is one of the basic problems about reusing software component automatically. In this paper, an intelligent component retrieval model – FWRM. is proposed. Facet presentation is used to model query and component. Multiple types of facets are defined which extends traditional keyword-based facet presentation. Genetic algorithm based facet weight self-learning algorithm can change the facet weight dynamically in order to improve retrieval accuracy. Corresponding similarity functions are defined also. In addition, risk minimization-based component sampling method is used to solve the insufficiency of training data. All these algorithms and methods are integrated into FWRM’s three main implementation parts: Facet-Weight Optimize System, Component Retrieve System and Resource. The experimental results prove that this method is feasible and can improve component retrieval effectively.
207188648
Reliable Ad Hoc Routing Based on Mobility Prediction
Reliability is a very important issue in Mobile Ad hoc NETworks (MANETs). Shortest paths are usually used to route packets in MANETs. However, a shortest path may fail quickly, because some of the wireless links along a shortest path may be broken shortly after the path is established due to mobility of mobile nodes. Rediscovering routes may result in substantial data loss and message exchange overhead. In this paper, we study reliable ad hoc routing in the urban environment. Specifically, we formulate and study two optimization problems. In the minimum Cost Duration-bounded Path (CDP) routing problem, we seek a minimum cost source to destination path with duration no less than a given threshold. In the maximum Duration Cost-bounded Path (DCP) routing problem, we seek a maximum duration source to destination path with cost no greater than a given threshold. We use a waypoint graph to model the working area of a MANET and present an offline algorithm to compute a duration prediction table for the given waypoint graph. An entry in the duration prediction table contains the guaranteed worst-case duration of the corresponding wireless link. We then present an efficient algorithm which computes a minimum cost duration-bounded path, using the information provided in the duration prediction table. We also present a heuristic algorithm for the DCP routing problem. In addition, we show that the proposed prediction and routing schemes can be easily applied for designing reliable ad hoc routing protocols. Simulation results show that our mobility prediction based routing algorithms lead to higher network throughput and longer average path duration, compared with the shortest path routing.
206793142
What video can and cannot do for collaboration: A case study
As multimedia become an integral part of collaborative systems, we must understand how to design such systems to support the user's rich set of existing interaction skills, rather than requiring people to adapt to arbitrary constraints of technology-driven designs. To understand how we can make effective use of video in remote collaboration, we compared a small team's interactions through a desktop video conferencing prototype with face-to-face interactions and phone conversations. We found that, compared with audio-only, the video channel of our desktop video conferencing prototype adds or improves the ability to show understanding, forecast responses, give nonverbal information, enhance verbal descriptions, manage pauses, and express attitudes. These findings suggest that video may be better than the phone for handling conflict and other interaction-intense activities. However, the advantages of video depend critically on the nearly-instantaneous transmission of audio, even if it means getting out of sync with the video image. Nonetheless, when compared with face-to-face interaction, it can be difficult in video interactions to notice peripheral cues, control the floor, have side conversations, point to things or manipulate real-world objects. To enable rich interactions fully, video should be integrated with other distributed tools that increase the extent and type of shared space in a way that enables natural collaborative behaviors within those environments.