Progress made in the field of high speed networking technology has led to the planning and prototyping of true high-bandwidth applications with very high throughput and low delay requirements. In this study we approach the problem of high throughput demand from the aspect of protocols and introduce the handling of error control in the application layer level as opposed to the transport layer since the eventual destination of data is the application itself. This scheme, called ACER (Application Conscious Error Recovery), is proposed and defined for bulk data transfers. A simple analytic throughput comparison of the sliding window scheme with go-back-N, and ACER is given later, Also, a prototype implementation of ACER for bulk data transfer and experimental measurement results are presented. Besides, we investigate the performance of the scheme by simulation for various network models. Finally, we present a discussion of extending the scheme to different traffic patterns and applications.

The Internet has become an important medium for effective marketing and efficient operations for many institutions. Visitors of a particular web site leave behind valuable information on their preferences, requirements, and demands regarding the offered products and/or services. Understanding these requirements online, i.e., during a particular visit, is both a difficult technical challenge and a tremendous business opportunity. Web sites that can provide effective online navigation suggestions to their visitors can exploit the potential inherent in the data such visits generate every day. However, identifying, collecting, and maintaining the necessary knowledge that navigation suggestions are based on is far from trivial. We propose a methodology for acquiring and maintaining this knowledge efficiently using data mart and web mining technology. Its effectiveness has been shown in an application for a bank's web site.

The behavior of visitors browsing in a web site offers a lot of information about their requirements and the way they use the respective site. Analyzing such behavior can provide the necessary information in order to improve the web site's structure. The literature contains already several suggestions on how to characterize web site usage and to identify the respective visitor requirements based on clustering of visitor sessions. Here we propose to combine visitor behavior with the content of the respective web pages and the similarity between different page sequences in order to define a similarity measure between different visits. This similarity serves as input for clustering of visitor sessions. The application of our approach to a bank's web site and its visitor sessions shows its potential for internet-based businesses.

This paper addresses issues regarding to the development of teleconferencing support collaboration focusing on the realistic sensation domain. It argues that the gaze communications are the important mechanisms to enable visual channel and social presence in human-human communications. We propose a new aspect to establish multiple eye contacts and community awareness in multiparty videoconference (VC). The participants can aware of being recognized from any remote sites while they are talking with each other. Community awareness means the ability to aware of group communication in the videoconference. The participant can recognize of who is talking with whom and any communicative groups in a conference. An intelligent image arrangement through a unique position of camera is built and simulated. The systematic placement of images serves the gaze communications by utilizing the characteristic of gaze direction and image's position. The experimental results show that the proposed approach has the significant improvement in the interpersonal communication compared with the conventional VC system.