Packet drops caused byresidueerrors(MAC-layer errors) can severely deteriorate the wireless video quality. Prior studies have shown that this loss of quality can be circumvented by using forward error correction (FEC) to recover information from the corrupted packets. The performance of FEC encoded video streaming is critically dependent upon the choice of source and channel coding rates. In practice, the wireless channel conditions can vary significantly, thus altering the optimal rate choices. Thus, it is essential to develop an architecture which can estimate the channel capacity and utilize this estimate for rate allocation. In this paper we develop such a framework. Our contributions consist of two parts. In the first part we develop a prediction framework that leverages the received packets' signal to silence ratio (SSR) indications and MAC-layer checksum as side information to predict the operational channel capacity. In the second part, we use this prediction framework for rate allocation. The optimal rate allocation is dependent upon thechannelcapacity, the distribution of the (capacity)predictionerrorand the rate-distortion (RD) characteristics of the video source. Consequently, we propose a framework that utilizes the aforementioned statistics for RD optimal rate adaptation. We exhibit the efficacy of the proposed scheme by simulations using actual 802.11b wireless traces, an RD model for the video source and an ideal FEC model. Simulations using source RD models derived from five different popular video codecs (including H.264), show that the proposed framework provides up-to 5-dB improvements in peak signal-to-noise ratio (PSNR) when compared with conventional rate-adaptive schemes.

The purpose of this study is to develop an evaluation methodology for performing the initial evaluation, operational evaluation, and post evaluation of the collaborative information system that will support new product development efforts of domestic mould companies. After all, this system will efficiently support new product development by using the collaborative information system to link goals to performance. For these, we derived the CSFs and KPIs for evaluating the collaborative information system. And, the derived KPIs are applied to the design collaborative information system, the outcome of the e-Manufacturing project, and pre evaluation and post evaluation are conducted. If the web-based evaluation system developed in this study is integrated with the collaborative information system, real-time level evaluation will be possible.

Performance of cross-layer protocols that recommend the relay of corrupted packets to higher layers can be improved significantly by accurately inferring/predicting the bit error rate (BER) in the packets. In practice, higher layers observe the bits only after some hard decision. Hence physical layer link-quality indications, such as the signal strength of each individual bit, are not observable at higher layers. Therefore, it is essential to identify practically observable variables, which can be used for reasonably robust channel state inference/prediction (CSI/CSP). Here, inference specifically refers to estimating the BER in an already received packet, while prediction refers to anticipating the BER in a future packet. In this paper, we note that, in practical 802.11b devices, it is possible to acquire a Signal to Silence Ratio (SSR) indication and measure the background traffic intensity (p) on a per packet basis. This paper, thus presents a measurement-based study that analyzes the utility of SSR andpas side-information for CSI/CSP. In this work, we exploit the method of types to measure the robustness of the observable side-information. Our analysis and simulations based on an extensive set of actual 802.11b traces exhibit the practical utility of the considered observable variables.

Competitive and dynamically changing markets make design collaboration in a CSCW system essential for the mould industry. Design processes including design of a target product, parts, and assembly are essential in mould creation. Even though many systems supporting collaborative design have been implemented, they chiefly support technical difficulties from spatial and time differences such as data translation for heterogeneous CAD systems, and co-editing systems through Web access. However, they have focused on a specific process rather than considering the entire collaborative process of the real application such as collaboration between contractors and sub-contractors, collaboration among human operators in the shop floor, etc. These factors must be taken into account prior to system development in order to allow the system to function correctly. Therefore, we propose a new method, referred to as the POD method, to generate "business templates" focusing on three viewpoints to analyze business workflows, namely process, organization, and document. In order to use the POD method, we need to model manufacturing processes beforehand. To do so, we introduce our definition of process modeling and illustrate it using a case study. The POD method gives us a way to analyze business or manufacturing processes and generate business templates by extraction and deduction of business information. By using the proposed method, we have acquired a large variety of business templates, and they are currently being implemented as a Web-based collaboration hub system in Korea.