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Minimizing the communication overhead is always a hot topic in wireless sensor networks. In a multirate query system, data sources disseminate the data streams to users at the frequency they request. However, sending data in different frequencies to individual users is very costly. We address this problem by broadcasting a single consolidated data stream, aiming at reducing the amount of transmitted data. Taking into account the data correlation, we can reconstruct the data streams at lower frequencies from the consolidated stream at a higher frequency. In this paper, we propose an energy-efficient framework to process multirate queries and investigate the path-sharing routing tree construction method together with the rate conversion mechanism. We evaluate both the accuracy and energy efficiency by simulation. Simulation results indicate that with a reasonable level of tolerance, the performance gain is significant. As far as we know, this is the first energy-efficient solution for multirate query in wireless sensor networks.

A dialogue-based interface for information systems is considered a potentially very useful approach to information access. A key step in computer processing of natural-language dialogues is dialogue-act (DA) recognition. In this paper, we apply a feature-based classification approach for DA recognition, by using the maximum entropy (ME) method to build a classifier for labeling utterances with DA tags. The ME method has the advantage that a large number of heterogeneous features can be flexibly combined in one classifier, which can facilitate feature selection. A unique characteristic of our approach is that it does not need to model the prior probability of DAs directly, and thus avoids the use of a discourse grammar. This simplifies the implementation of the classifier and improves the efficiency of DA recognition, without sacrificing the classification accuracy. We evaluate the classifier using a large data set based on the Switchboard corpus. Encouraging performance is observed; the highest classification accuracy achieved is 75.03%. We also propose a heuristic to address the problem of sparseness of the data set. This problem has resulted in poor classification accuracies of some DA types that have very low occurrence frequencies in the data set. Preliminary evaluation shows that the method is effective in improving the macroaverage classification accuracy of the ME classifier. [ABSTRACT FROM AUTHOR]

In a mobile cooperative caching environment, we observe the need for cooperating peers to cache useful data items together, so as to improve cache hit from peers. This could be achieved by capturing the data requirement of individual peers in conjunction with their mobility pattern, for which we realized via a GROup-based COoperative CAching scheme (GroCoca). In GroCoca, we define a tightly-coupled group (TCG) as a collection of peers that possess similar mobility pattern and display similar data affinity. A family of algorithms is proposed to discover and maintain all TCGs dynamically. Furthermore, two cooperative cache management protocols, namely, cooperative cache admission control and replacement, are designed to control data replicas and improve data accessibility in TCGs. A cache signature scheme is also adopted in GroCoca in order to provide information for the mobile clients to determine whether their TCG members are likely caching their desired data items and to perform cooperative cache replacement. Experimental results show that GroCoca outperforms the conventional caching scheme and standard COoperative CAching scheme (COCA) in terms of access latency and global cache hit ratio. However, GroCoca generally incurs higher power consumption. [ABSTRACT FROM AUTHOR]

XML (eXtensible Markup Language) has been developed and deployed by domain-specific standardization bodies and commercial companies. Studies have been conducted on a wide variety of issues encompassing XML. In the use of XML for wireless computing, the focus has been on investigating ways to efficiently represent XML data for transmission over a wireless environment. We propose a middleware, Xstrearn (XML Streaming), for efficiently streaming XML contents over a wireless environment by leveraging the rich semantics and structural characteristics of XML documents and by flexibly managing units containing fragments of data into autonomous units, known as XDU (Xstream Data Unit) fragments. The concept of an XDU is fundamental to the operation of Xstream. It provides for the efficient transfer of documents across a wireless link and allows other issues and challenges pertaining to wireless transmission to be addressed. By fragmenting and organizing an XML document into XDU fragments, we are able to incrementally send fragments across a wireless link, while the receiver is able to perform look-ahead processing of the document without having to wait for the entire document to be downloaded. In this paper, we propose a fragmenting strategy based on the value of the wireless link's Maximum Transfer Units (MTUs). In addition, we present and evaluate several packetizing strategies, i.e., strategies wherein a collection of XDU5 are grouped into a packet to optimize packet delivery and processing. At the receiving end of this process, a reassembly strategy incrementally reconstructs the XML document as XDU fragments are being received, thereby facilitating client application implementation of look-ahead processing. [ABSTRACT FROM AUTHOR]

The formulation of a context-aware middleware requires researchers to devise suitable control mechanisms that allow applications to directly participate in resource adaptation in response to dynamic operating environments. This paper describes the design and implementation of an event model for a highly adaptive mobile middleware, Web Proxy for Actively Deployable Services (WebPADS) platform. The event model provides a highly composable event notification framework that uses multiple levels of environment monitors to provide a complex setup of composite events. Based on the event model and the dynamic reconfiguration feature WebPADS supports context awareness and a high level of adaptation to contextual changes through reconfiguration and migration of services. [ABSTRACT FROM AUTHOR]

Distance education, e-learning, and virtual university are similar terms for a trend of modern education. It is an integration of information technologies, computer hardware systems, and communication tools, to support educational professionals in remote teaching. This paper presents an overview of distance education from the perspective of policy, people, and technology. A number of questions frequently asked in distance learning panel discussions are presented, with the suggested answers from the authors. The survey presented in this paper includes communication, intelligent, and educational technologies of distance education. Readers of this paper are academic researchers and engineers who are interested in new research issues of distance education, as well as educators and general participants who are seeking new solutions. [ABSTRACT FROM AUTHOR]

Presents a semantic-based broadcast approach. Semantic descriptor of each broadcast unit; Function of the semantic descriptor; Techniques in organizing data chunks.