The semiconductor industry is lacking qualified integrated circuit (IC) test engineers to serve in the field of mixed-signal electronics. The absence of mixed-signal IC test education at the collegiate level is cited as one of the main sources for this problem. In response to this situation, the Department of Electrical and Computer Engineering at the Ohio State University, Columbus, has partnered with Texas Instruments to establish an IC test-engineering-oriented course. The course objectives are to familiarize students with industrial testing techniques and to help students obtain the fundamental skill sets required to be competent mixed-signal IC test engineers. A novel laboratory pedagogy is developed to achieve these objectives. The results of the classroom assignments and the feedback provided by students, faculty, and industry representatives indicate that the approach has successfully achieved these goals.

This paper describes a new course on mixed-signal IC test engineering, jointly established by the Department of Electrical and Computer Engineering (ECE) of The Ohio State University and Texas Instruments. The course is motivated by the lack of qualified test engineers in industry and the absence of this education at the collegiate level. The course objective is to help student obtain the fundamental skills required for a mixed-signal IC test engineer. The course structure and laboratory developments are covered in details. Students feedbacks based on anonymous survey indicate that the goals are well met.

Remote access of electron microscopes over the Internet (i.e., Telemicroscopy) is a unique network-dependent immersive multimedia application. It demands high-resolution (2D and 3D) video image transfers with simultaneous real-time mouse and keyboard controls. Consequently, user Quality of Experience (QoE) is highly sensitive to network bottlenecks caused by cross-traffic congestion and network faults. Further, improper user control while reacting to impaired video causededue to network bottlenecks could result in physical damages to the microscope that are prohibitively expensive to fix. Hence, it is vital to understand the interplay between: (a) the user keyboard/mouse actions (i.e., TCP control traffic) towards the microscope and (b) the corresponding network reactions for transport of microscope video images (i.e., RTP media traffic) towards the user. In this paper, we present an analytical model for characterizing user and network interplay during Telemicroscopy sessions in terms of demand and supply interplay principles of economics, respectively. To study the trends of the model parameters, we use data obtained from QoE experiments conducted on a Telemicroscopy testbed involving actual users as well as both LAN and WAN network paths. Also, we describe an application called Remote Instrumentation Collaboration Environment (RICE) we are developing that leverages our user and network interplay characterization studies to provide optimum user QoE and also reliably support Internet Telemicroscopy.

Increased access to broadband networks has led to a fast-growing demand for voice and video over IP (VVoIP) applications such as Internet telephony (VoIP), videoconferencing, and IP television (IPTV). For pro-active troubleshooting of VVoIP performance bottlenecks that manifest to end-users as performance impairments such as video frame freezing and voice dropouts, network operators cannot rely on actual end-users to report their subjective quality of experience (QoE). Hence, automated and objective techniques that provide real-time or online VVoIP QoE estimates are vital. Objective techniques developed to-date estimate VVoIP QoE by performing frame-to-frame peak-signal-to-noise ratio (PSNR) comparisons of the original video sequence and the reconstructed video sequence obtained from the sender-side and receiver-side, respectively. Since processing such video sequences is time consuming and computationally intensive, existing objective techniques cannot provide online VVoIP QoE. In this paper, we present a novel framework that can provide online estimates of VVoIP QoE on network paths without end-user involvement and without requiring any video sequences. The framework features the "GAP-model", which is an offline model of QoE expressed as a function of measurable network factors such as bandwidth, delay, jitter, and loss. Using the GAP-model, our online framework can produce VVoIP QoE estimates in terms of "Good", "Acceptable", or "Poor" (GAP) grades of perceptual quality solely from the online measured network conditions.

Internet videoconferencing has emerged as a viable medium for communication and entertainment. However, its widespread use is being challenged. This is because videoconference end-users frequently experience perceptual quality impairments such as video frame freezing and voice dropouts due to changes in network conditions on the Internet. These impairments cause extra end-user interaction effort and correspondingly lead to unwanted network bandwidth consumption that affects user Quality of Experience (QoE) and Internet congestion. Hence, it is important to measure and subsequently minimize the extra end-user interaction effort in a videoconferencing system. In this paper, we describe a novel active measurement scheme that considers end-user interaction effort and the corresponding network bandwidth consumption to provide videoconferencing interaction QoE measurements. The scheme involves a “Multi-Activity Packet-Trains” (MAPTs) methodology to dynamically emulate a videoconference session’s participant interaction patterns and corresponding video activity levels that are affected by transient changes in network conditions. Also, we describe the implementation and validation of the Vperf tool we have developed to measure the videoconferencing interaction QoE on a network path using our proposed scheme.

Recent computing applications such as videoconferencing and grid computing run their tasks on distributed computing resources connected through networks. For such applications, knowledge of the network status such as delay, jitter, and available bandwidth can help them select proper network resources to meet the Quality-of-Service (QoS) requirements. Also, the applications can dynamically change the resource selection if the current selection is found to experience poor performance. For such purposes, Internet Service Providers (ISPs) have started to instrument their networks with Network Measurement Infrastructures (NMIs) that run active measurement tasks periodically and/or on demand. However, one problem that most network engineers have overlooked is the measurement conflict problem, which happens when multiple active measurement tasks inject probing packets into the same network segment at the same time, resulting in misleading reports of network performance due to their combined effects. This paper proposes enhanced Earliest Deadline First (EDF) algorithms that allow "Concurrent Executions" to orchestrate offline/online measurement jobs in a conflict-free manner. The simulation study shows that our measurement scheduling mechanism can improve the schedulable utilization of offline measurement tasks up to 300 percent and the response time of on-demand jobs up to 50 percent. Further, we implement and deploy our scheduling mechanism in a real working NMI for monitoring the Internet2 Abilene network. As a case study, we show the utility of our algorithms in the widely used Network Weather Service (NWS).