12th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS'05), 2005
The high cost of operating large computing installations has motivated a broad interest in reduci... more The high cost of operating large computing installations has motivated a broad interest in reducing the need for human intervention by making systems self-managing. This paper explores the extent to which control theory can provide an architectural and analytic foundation for building self-managing systems, either from new components or layering on top of existing components. Further, we propose a deployable testbed for autonomic computing (DTAC) that we believe will reduce the barriers to addressing key research problems in autonomic computing. The initial DTAC architecture is described along with several problems that it can be used to investigate. Monitor Analyze Plan Execute Resource Sensor Effector Knowledge Autonomic Manager
We present an autonomic controller for quality collaborative video viewing, which allows groups o... more We present an autonomic controller for quality collaborative video viewing, which allows groups of geographically dis-persed users with different network and computer resources to view a video in synchrony while optimizing the video qual-ity experienced. The autonomic controller is used within a tool for enhancing distance learning with synchronous group review of online multimedia material. The autonomic con-troller monitors video state at the clients' end, and adapts the quality of the video according to the resources of each client in (soft) real time. Experimental results show that the autonomic controller successfully synchronizes video for small groups of distributed clients and, at the same time, en-hances the video quality experienced by users, in conditions of fluctuating bandwidth and variable frame rate.
Blind source separation (BSS) decomposes a multidimensional time series into a set of sources, ea... more Blind source separation (BSS) decomposes a multidimensional time series into a set of sources, each with a one-dimensional time course and a xed spatial distribution. For EEG and MEG, the former corresponds to the simultaneously separated and temporally overlapping signals for continuous non-averaged data; the latter corresponds to the set of attenuations from the sources to the sensors. These sensor projection vectors give information on the spatial locations of the sources. Here we use standard Neuromag dipole-tting software to localize BSS-separated components of MEG data collected in several tasks in which visual, auditory, and somatosensory stimuli all play a role. We found that BSS-separated components with stimulusor motor-locked responses can be localized to physiological and anatomically meaningful locations within the brain. 1. INTRODUCTION Blind source separation (BSS) algorithms, such as Infomax (Bell and Sejnowski, 1995), second-order blind identication (SOBI) (Belouc...
As users interact with the world and their peers through their computers, it is becoming importan... more As users interact with the world and their peers through their computers, it is becoming important to archive and later search the information that they have viewed. We present DejaView, a personal virtual computer recorder that provides a complete record of a desktop computing experience that a user can playback, browse, search, and revive seamlessly. DejaView records visual output, checkpoints corresponding application and file system state, and captures displayed text with contextual information to index the record. A user can then browse and search the record for any visual information that has been displayed on the desktop, and revive and interact with the desktop computing state corresponding to any point in the record. DejaView combines display, operating system, and file system virtualization to provide its functionality transparently without any modifications to applications, window systems, or operating system kernels. We have implemented DejaView and evaluated its perform...
International Journal of Distance Education Technologies, 2007
The increasing popularity of online courses has highlighted the need for collaborative learning t... more The increasing popularity of online courses has highlighted the need for collaborative learning tools for student groups. In addition, the introduction of lecture videos into the online curriculum has drawn attention to the disparity in the network resources available to students. We present an e-Learning architecture and adaptation model called AI 2 TV (Adaptive Interactive Internet Team Video), which allows groups of students to collaboratively view a video in synchrony. AI 2 TV upholds the invariant that each student will view semantically equivalent content at all times. A semantic compression model is developed to provide instructional videos at different level-of-details to accommodate dynamic network conditions and users' requirements; video player actions, like play, pause and stop, can be initiated by any group member. These features allow students to review a lecture video in tandem, facilitating the learning process. Experimental trials show that AI 2 TV successfully synchronizes instructional videos for distributed students while, at the same time, optimizing the video quality, even under conditions of fluctuating bandwidth, by adaptively adjusting the quality level for each student while still maintaining the invariant.
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles - SOSP '07, 2007
As users interact with the world and their peers through their computers, it is becoming importan... more As users interact with the world and their peers through their computers, it is becoming important to archive and later search the information that they have viewed. We present DejaView, a personal virtual computer recorder that provides a complete record of a desktop computing experi- ence that a user can playback, browse, search, and revive seamlessly. DejaView records visual output,
The increasing popularity of distance learning and online courses has highlighted the lack of col... more The increasing popularity of distance learning and online courses has highlighted the lack of collaborative tools for student groups. In addition, the introduction of lecture videos into the online curriculum has drawn attention to the disparity in the network resources used by students. We present an e-Learning architecture and adaptation model called AI 2 TV (Adaptive Internet Interactive Team Video), a system that allows borderless, virtual students, possibly some or all disadvantaged in network resources, to collaboratively view a video in synchrony. AI 2 TV upholds the invariant that each student will view semantically equivalent content at all times. Video player actions, like play, pause and stop, can be initiated by any of the students and the results of those actions are seen by all the other students. These features allow group members to review a lecture video in tandem to facilitate the learning process. We show in experimental trials that our system can successfully synchronize video for distributed students while, at the same time, optimizing the video quality given actual (fluctuating) bandwidth by adaptively adjusting the quality level for each student.
2005 IEEE International Conference on Cluster Computing, 2005
We have created ZapC, a novel system for transparent coordinated checkpoint-restart of distribute... more We have created ZapC, a novel system for transparent coordinated checkpoint-restart of distributed network applications on commodity clusters. ZapC provides a thin virtualization layer on top of the operating system that decouples a distributed application from dependencies on the cluster nodes on which it is executing. This decoupling enables ZapC to checkpoint an entire distributed application across all nodes in a coordinated manner such that it can be restarted from the checkpoint on a different set of cluster nodes at a later time. ZapC checkpoint-restart operations execute in parallel across different cluster nodes, providing faster checkpoint-restart performance. ZapC uniquely supports network state in a transport protocol independent manner, including correctly saving and restoring socket and protocol state for both TCP and UDP connections. We have implemented a ZapC Linux prototype and demonstrate that it provides low virtualization overhead and fast checkpointrestart times for distributed network applications without any application, library, kernel, or network protocol modifications.
Second International Conference on Autonomic Computing (ICAC'05), 2005
Most general-purpose work towards autonomic or self-managing systems has emphasized the front end... more Most general-purpose work towards autonomic or self-managing systems has emphasized the front end of the feedback control loop, with some also concerned with controlling the back end enactment of runtime adaptations -but usually employing an effector technology peculiar to one type of target system. While completely generic "one size fits all" effector technologies seem implausible, we propose a generalpurpose programming model and interaction layer that abstracts away from the peculiarities of targetspecific effectors, enabling a uniform approach to controlling and coordinating the low-level execution of reconfigurations, repairs, micro-reboots, etc.
Abstract As university-level distance learning programs become more and more popular, and softwar... more Abstract As university-level distance learning programs become more and more popular, and software engineering courses incorporate eXtreme Programming (XP) into their curricula, certain challenges arise when teaching XP to students who are not physically co ...
IEEE Journal on Selected Areas in Communications, 2000
The high cost of operating large computing installations has motivated a broad interest in reduci... more The high cost of operating large computing installations has motivated a broad interest in reducing the need for human intervention by making systems self-managing. This paper explores the extent to which control theory can provide an architectural and analytic foundation for building self-managing systems. Control theory provides a rich set of methodologies for building automated self-diagnosis and self-repairing systems with properties such as stability, short settling times, and accurate regulation. However, there are challenges in applying control theory to computing systems, such as developing effective resource models, handling sensor delays, and addressing lead times in effector actions. We propose a deployable testbed for autonomic computing (DTAC) that we believe will reduce the barriers to addressing research problems in applying control theory to computing systems. The initial DTAC architecture is described along with several problems that it can be used to investigate.
The increasing popularity of distance learning and online courses has highlighted the lack of col... more The increasing popularity of distance learning and online courses has highlighted the lack of collaborative tools for student groups. In addition, the introduction of lecture videos into the online curriculum has drawn attention to the disparity in the network resources used by the students. We present an architecture and adaptation model called AI 2 TV (Adaptive Internet Interactive Team Video), a system that allows geographically dispersed participants, possibly some or all disadvantaged in network resources, to collaboratively view a video in synchrony. AI 2 TV upholds the invariant that each participant will view semantically equivalent content at all times. Video player actions, like play, pause and stop, can be initiated by any of the participants and the results of those actions are seen by all the members. These features allow group members to review a lecture video in tandem to facilitate the learning process. We employ an autonomic (feedback loop) controller that monitors clients' video status and adjusts the quality of the video according to the resources of each client. We show in experimental trials that our system can successfully synchronize video for distributed clients while, at the same time, optimizing the video quality given actual (fluctuating) bandwidth by adaptively adjusting the quality level for each participant.
Independent component analysis (ICA) is a class of decomposition methods that separate sources fr... more Independent component analysis (ICA) is a class of decomposition methods that separate sources from mixtures of signals. In this chapter, we used second order blind identification (SOBI), one of the ICA method, to demonstrate its advantages in identifying magnetic signals associated with neural information processing. Using 122-channel MEG data collected during both simple sensory activation and complex cognitive tasks, we explored SOBI's ability to help isolate and localize underlying neuronal sources, particularly under relatively poor signal-to-noise conditions. For these identified and localized neuronal sources, we developed a simple threshold-crossing method, with which single-trial response onset times could be measured with a detection rate as high as 96%. These results demonstrated that, with the aid of ICA, it is possible to non-invasively measure human single trial response onset times with millisecond resolution for specific neuronal populations from multiple sensory modalities. This capability makes it possible to study a wide range of perceptual and memory functions that critically depend on the timing of discrete neuronal events.
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Papers by Dan Phung