In this paper we introduce an architecture, an implementation and an evaluation of a system for the automatic creation of interactive stories for games. Our goal is to algorithmically create a branched story for the entire game; in each game run a different variant is generated. The architecture uses natural language processing (NLP) to generate meaningful stories. For NLP we use a statistical language model based on a neural network (Generative Pretrained Transformer, GPT-2). The basic architecture generates stories with too many characters which tend to get incoherent for longer texts, so we add a component restricting the number of persons and improving the consistency. The system is initialized with a hand-written game introduction that defines the main characters and the inventory; it also sets the goals for the game. From that text the remainder of the game story is generated algorithmically. We have fully implemented our system, and we report initial, encouraging experimental results.

This article is about the procedural generation of accessible multistory buildings including stairwells. We present an algorithm featuring a natural bottom-up approach, where each building is defined by a set of rooms that can be connected by doors or stairways and are equipped with windows. Our approach is robust so that neither the rooms, nor the connections, nor the objects can be placed in invalid positions. In the second part, we enhance the process by a procedural growth algorithm with automatic corridor detection and stairwell placement. Finally, we propose an automatic mesh generation for either procedurally or manually designed buildings. We evaluate our approach by creating a full implementation of the algorithm, and judge it based on the resulting realism, accessibility, and diversity of a generated test set of buildings.

The Information-Centric Networking (ICN) paradigm is deemed to enable simpler and more efficient networking interaction by moving from a strict connection based relationship between client and server to an interest-based relationship between user and content. Hence, addressing shifts to content objects rather than any specific copy or location of the content. In order to achieve this new way of addressing the client uses the content name, which is propagated into the network. As a result, a higher efficiency is expected since ICN network nodes (e.g., routers) may reply to such requests using copies from their own caches, or different sources hosting a content object may be used in parallel. Thus, this concept promises better support for device mobility and implicit caching, and it provides inherent multicast support.However, the simplicity of this concept comes at a price. As established applications, such as adaptive bitrate video streaming, have been designed and optimized having a client-server networking environment in mind. In particular, the quality adaptation algorithms used by today's de-facto streaming standard Dynamic Adaptive Streaming over HTTP (DASH) uses bandwidth estimation techniques that are specifically designed for a client-server networking environment where all video segments are retrieved from the same host.This paper addresses issues related to adaptive video streaming in an ICN environment. It analyzes the video streaming behavior of state-of-the-art video quality adaptation algorithms such as PANDA and BOLA in emulated ICN environments. The analysis focuses on the impact ICN chunk-based throughput measurements and ICN caches have on quantitative measurements of Quality-of-Experience (QoE). The paper provides a detailed investigation of the chunk-based throughput estimation showing that it behaves fundamentally different due to ICN caching. Based on these results we provide extensions to existing adaptation algorithms (e.g., PANDA) that can significantly improve the QoE in ICN environments.

This survey introduces the current state of the art in image and video retargeting and describes important ideas and technologies that have influenced the recent work. Retargeting is the process of adapting an image or video from one screen resolution to another to fit different displays, for example, when watching a wide screen movie on a normal television screen or a mobile device. As there has been considerable work done in this field already, this survey provides an overview of the techniques. It is meant to be a starting point for new research in the field. We include explanations of basic terms and operators, as well as the basic workflow of the different methods.

The current body of research on Dynamic Adaptive Streaming over HTTP (DASH) contributes various adaptation algorithms aiming to optimize performance metrics such as the Quality of Experience. Intuitively, the heterogeneity of the streaming environment and the underlying technologies lead many of the developed approaches to possess clear performance affinities denoted here as sweet spots. We observe, however, that systematic comparisons of these algorithms are usually conducted within homogeneous player environments.

High quality video streaming over cellular networks is expensive for users and often limited by data caps. Offloading the traffic over other cheap wireless networks, e.g. WLAN, would be beneficial however they are often not available for mobile streaming sessions. A potential solution is to load video to a mobile device before the user accesses it, which is called prefetching. Prefetching requires indicators to perform a prediction what a single user is going to watch in the future. This prediction determines which videos are loaded to the users' mobile device. We leverage recommender systems of the video sharing site YouTube to design and evaluate mobile prefetching algorithms. A user study has been performed over a month in which users' YouTube accesses were supported by our prefetching algorithms which allowed for significant reductions in data usage on mobile networks while having a low computational overhead.

Many teachers use Audience Response Systems (ARS) in lectures to re-activate their listeners and to get an insight in students’ knowledge of the current lecture contents. Plenty of such applications have been developed in recent years, they provide a high variety of different teaching scenarios with the use of the students’ smartphones, including quizzes, lecture feedback and dynamic message boards. We developed a novel application based on an abstract model to enable this variety of customizable teaching scenarios within one application. After presenting the application to the first charge of lecturers, the responses were quite good, and several new teaching scenarios were created and used. This paper presents first experiences when using a variety of customizable teaching scenarios, the special opportunities and challenges as well as the opinions of lecturers and students, which we collected with a survey at the end of the semester.

Instant sharing of user-generated video recordings has become a widely used service on platforms such as YouNow. Yet, it still poses technical challenges, as mobile upload speed and capacities are limited. One proposed solution to address these issues is video composition. It allows switching between multiple video streams-selecting the best source for a given time-for composing a live video of a better overall quality for viewers. Previous approaches require visual analysis of the video streams, usually limiting the scalability of the system. In contrast, our work allows the stream selection to be realized solely on context information, based on video-and service-quality aspects from sensor and network measurements. The implemented monitoring service for context-aware upload of video streams is evaluated in varying network conditions, with diverse user behavior, including camera shaking and user mobility. We show that a higher efficiency for video upload as well as QoE for viewers can be achieved.

In comparison to professional productions, UGV often suffers from quality degradations such as camera shakes or harmful occlusions. Quick and reliable algorithms are needed to detect and assess the impact of these quality degradations. Recently, researchers leverage data from auxiliary sensors such as gyroscope readings or accelerometer values for quality assessment. In comparison to video-based approaches, auxiliary sensor-based ones achieve results more quickly but often lack precision.

Adaptive streaming systems gain rising relevance for streaming services. Therefore, the same video is offered in multiple quality versions to clients for adaptation during playback. However, optimizing adaptation in a Quality of Experience (QoE) centric way is difficult. Current systems maximize bit rate, ignoring that different types of adaptation (resolution, framerate, quantization) correlate differently and in a non-linear way with user's perception. User validated video quality metrics can provide precise quality information. However, measurements of state-of-the-art metrics show either high computational intensity or weak correlation with subjective tests. This makes large-scale offline quality assessment processing intensive while real-time constrained scenarios like live streaming and video conferencing are hardly supportable. Consequently, this work presents the Real-Time Video Quality Metric (RT-VQM), a real-time, Graphics Processing Unit (GPU) supported version of the widely used Video Quality Metric (VQM). RT-VQM introduces efficient filtering operations, hardware-supported scaling and high-performance feature pooling. The approach outperforms VQM by a factor of 30, thus enabling a real-time assessment of up to 9 parallel video stream representations up to High Definition (HD) 720 resolution at 30fps.

In most adaptive video streaming systems adaptation decisions rely solely on the available network resources. As the content of a video has a large influence on the perception of quality our belief is that this is not sufficient. Thus, we have proposed a support service for content-aware video adaptation on mobile devices: Video Adaptation Service (VAS). Based on the content of a streamed video, the adaptation process is improved by setting a target quality level for a session based on an objective video quality metric. In this work, we demonstrate VAS and its advantages of a reduced data traffic by only streaming the lowest video representation which is necessary to reach a desired quality. By leveraging the content properties of a video stream, the system is able to keep a stable video quality and at the same time reduce the network load.

Network emulations are widely used in the networking community. The network emulator Mininet recently gained popularity, as it allows running real Linux applications on top of an emulated network. The specification of the network includes the topology as well as static bandwidth, latency, and packet drops probability parameters. Even though evaluations with static parameters provide useful insights, real world measurements show dynamically changing bandwidths, posing special challenges that need to be addressed in network research.

This work discusses a distributed interactive video system that supports video annotation using simultaneous hyperlinking by multiple users. The users mark and annotate objects within the video with links to other media such as text, images, websites, or other videos. Annotations are visualized on the client user interface as an overlay close to the objects. Our system is intuitive to use; for example, it contains automatic object-tracking functionality that correctly positions the annotations, even when the form or location of an object changes. Thus, our first contribution discusses the adaptive object-tracking algorithm used for this repositioning. It shows improved precision and reliability in comparison to nonadaptive algorithms. A second key issue is to keep the system responsive when the number of concurrent annotators increases. Thus, we rely on the concept of eventual consistency between different network entities. While this weak form of consistency allows temporary inconsistencies, it ensures that a consistent state can be reached. Thus, the second contribution is the design and evaluation of our distributed interactive video system, which relies on the weak consistency paradigm.

Adaptive video streaming systems rely on the availability of different quality versions of a video. Such a system can dynamically adjust the quality of a video stream during its playback depending on the available network throughput. Even if the necessary throughput is available, mobile users can benefit from limiting the generated data traffic as most cellular network contracts have data caps. Usually, if the cap is reached, the throughput is throttled to a speed that does not allow video streaming. Existing systems react to varying network conditions but often neglect content-specific adaptation needs. Content inspection can help to save data traffic when a higher bitrate representation would not increase the perceived quality. In this work, we present the Video Adaptation Service (VAS), a support service for a content-aware video adaptation for mobile devices. Based on the video content, the adaptation process is improved for both the available network resources and the perception of the user. By leveraging the content properties of a video stream, the system is able to maintain a stable video quality and at the same time reduce the generated data traffic. The system is evaluated with different adaptation schemes and shows that content-specific adaptation can both increase the perceived quality as well as reduce the data traffic. Additionally, we demonstrate the practical feasibility of this approach by integrating the VAS into Dynamic Adaptive Streaming over the Hypertext Transfer Protocol.

Audience Response Systems (ARS) are quite common nowadays. With a very high smart phone availability among students, the usage of ARS within classroom settings has become quite easy. Together with the trend for developing web applications, the number of ARS implementations grew rapidly in recent years. Many of these applications are quite similar to each other, and fit into many classroom learning scenarios like test questions, self-assessment and audience feedback. But they are mostly limited to their original purpose. Using another question types or little differences in the existing quiz logic cause considerable effort to develop as they have to be implemented separately. We searched for similarities between the different ARS implementations, matched them to a universal process and present a generalized model for all of them. We implemented a prototype that serves many known scenarios ranging from simple knowledge feedback questions up to complex marketplace simulations. A first evaluation in different course types with up to fifty students showed, that the model satisfies our expectations and offers a lot of new opportunities for classroom learning scenarios.

A recent trend in user-generated video is to broadcast live video from mobile phones. Mobile broadcasting platforms such as YouNow or Periscope understood this trend and attract multiple thousands of concurrent views per second. Amateur produced mobile live video often suffers from only a limited duration of the recordings. Usually, the live recordings do not cover entire events. To address this problem our approach tries to understand how to increase the recording duration by integrating features for influencing the user behavior including gamification.

The re-capturing of video content poses significant challenges to algorithms in the fields of video forensics, watermarking, and near-duplicate detection. Using a camera to record a video from a display introduces a variety of artifacts, such as geometric distortions, luminance transformations, and temporal aliasing. A deep understanding of the causes and effects of such phenomena is required for their simulation, and for making the affected algorithms more robust. In this paper, we provide a detailed model of the temporal effects in re-captured video. Such effects typically result in the re-captured frames being a blend of the original video's source frames, where the specific blend ratios are difficult to predict. Our proposed parametric model captures the temporal artifacts introduced by interactions between the video renderer, display device, and camera. The validity of our model is demonstrated through experiments with real re-captured videos containing specially marked frames.

To compose high-quality movies directors need life-long learning and talent. User-generated video defines a new era of video production in which non-professionals record videos and share them on platforms such as YouTube. As hiring professional directors results in high costs, our work focuses on replacing those directors by crowdsourcing. The proposed system allows users to record and stream live videos to servers on which workers create a video mashup. A smartphone application for recording live video has been designed that supports the composition in the crowd by a multi-modal analysis of the recording quality. The contributions of this work are: The proposed system demonstrates that composing a large number of video views can be achieved in near real-time. Second, the system achieves comparable video quality for user-generated video in comparison to manual composition. Third, it offers insights on how to design real-time capable crowdsourcing systems. Fourth, by leveraging multi-modal features that can already be evaluated during recording the number of streams considered for presentation can be reduced.

Even though cellular networks offer a ubiquitous access to the Internet for mobile devices, their throughput is often insufficient for the rising demand for mobile video. Classical video streaming approaches can not cope with bandwidth fluctuations common in those networks. As a result adaptive approaches for video streaming have been proposed and are increasingly adopted on mobile devices. However, existing adaptive video systems often rely on available network resources alone. As video content properties have a large influence on the perception of occurring quality adaptations our belief is that this is not sufficient. In this work, we thus present a support service for a content-aware video adaptation on mobile devices. Based on the actual video content the adaptation process is improved for both the available network resources and the perception of the user. By leveraging the content properties of a video stream, the system is able to keep a stable video quality and at the same time reduce the network load.

Wireless, high-bandwidth data transfer gains increasing significance with a wider adoption of high-quality video streaming on mobile devices. Technologies enabling such data transfer (e.g., 802.11 or LTE) can adapt dynamically to changing conditions, which allows data transfers in a reliable way. However, applications have little or no influence on how those underlying systems execute their adaptations. Yet, in applications such as video streaming, this could provide important clues on what requirements are relevant for data delivery. In this demonstration, we present a system that allows application-defined underlay control to use such potentials in a mobile scalable video based streaming scenario by combining Android smartphones with software-defined radios (SDRs) for advanced physical layer control.

To support the development of any system that includes the generation and evaluation of camcorder copies, as well as to provide a common benchmark for robustness against camcorder copies, we present a tool to simulate digital video re-acquisition using a digital video camera. By resampling each video frame, we simulate the typical artifacts occurring in a camcorder copy: geometric modifications (aspect ratio changes, cropping, perspective and lens distortion), temporal sampling artifacts (due to different frame rates, shutter speeds, rolling shutters, or playback), spatial and color subsampling (rescaling, filtering, Bayer color filter array), and processing steps (automatic gain control, automatic white balance). We also support the simulation of camera movement (e.g., a hand-held camera) and background insertion. Furthermore, we allow for an easy setup and calibration of all the simulated artifacts, using sample/reference pairs of images and videos. Specifically temporal subsampling effects are analyzed in detail to create realistic frame blending artifacts in the simulated copies. We carefully evaluated our entire camcorder simulation system and found that the models we developed describe and match the real artifacts quite well.

In this paper, a novel warping-based retargeting approach for stereoscopic video is proposed. It considers the three conflicting goals: preserving salient image content, avoiding flickering and maintaining consistency between the two views. The first step of the approach focuses on content-aware image resizing and considers image saliency, motion saliency, and depth saliency. In the second step, temporal coherence is preserved by tracking and optimizing deformed pathlines. The proposed algorithm maps the mesh from the left to the right view to guarantee consistency between the deformation of objects between the views. Users rated the quality of the adapted videos as good. In particular, distortions in the perceived depth are not noticeable, and the temporal stability is significantly higher compared to seam carving approaches.

Video sharing sites such as Youtube are prominent examples for the increasing demand of private camera owners to record, save and share their real life experiences as videos. Whereas professional video productions use advanced camera equipment in a controlled environment with skilled cameramen, User-Generated Video (UGV) differs significantly in regard of equipment, skill and thus in video quality. In this work we focus on a detailed analysis of the effects of camera shakes, harmful occlusions as well as a possible misalignment between the recording camera and the scene, on the resulting video quality. In contrast, most of the video quality discussion in the literature has focused on encoding artifacts and other compression problems. Our data was systematically gathered using large crowdsourcing experiments over three genres of video, and it was validated in a controlled lab setting. Our results show that even minimal camera shaking as well as occlusions lead to a significant reduction in the perceived video quality.

The ACM First International Workshop on Serious Games was held on November 7, 2014. It was co-located with ACM's Inter-national Conference on Multimedia in Orlando. The purpose of the workshop was to bring together researchers and practitioners working on the development and use of serious games. The rationale behind co-locating this workshop with ACM Multimedia was that games are indeed multimedia systems, involving 3D graphics, integrated audio processing, human factors for the input devices, and often also the real-time transmission of events over computer networks.

Mobile video broadcasting services offer the opportunity to instantly share video from mobile handhelds to a large audience over the Internet. Additionally, the quality of those video streams is often reduced by the lack of skills of recording users and the technical limitations of the video capturing devices. Our research focuses on large-scale events that attract dozens of users to record video in parallel. In such scenarios, our aim is to design a collaborative mobile video broadcasting service that composes video streams from multiple sources to create one video stream with enhanced perceived quality. Our realization of such a service combines high quality video streaming and at the same time reduces the network load.

The increasing capabilities of mobile handhelds to record high definition videos enable us to share moments with friends and the public. In large-scale events such as concerts, the manifold of potential views recorded by the audience allows to watch an event from different perspectives. In this work, we elaborate on the effects of different recording positions on quality and show that especially with retail smart phone camera sensors the quality differs as the position changes. This is a first systematic approach to describe why user-generated video sequences differ in terms of quality depending on changing recording positions. To achieve a sound understanding, we conduct a large-scale systematic subjective study using crowdsourcing, inspecting the effect of distance and orientation of a recorder in relation to the event taking place. Our results indicate an effect of the recording position on the perceived quality of a video.

In this paper, we present a fast parallel algorithm for the retargeting of videos. It combines seam carving and cropping and is aimed for real-time adaptation of video streams. The basic idea is to first find an optimal cropping path over the whole sequence with the target size. Then, the borders are slightly extended to be reduced again by seam carving on a frame-by-frame basis. This allows the algorithm to get more important content into the cropping window as it is also able to remove pixels from within the window. In contrast to the previous SeamCrop algorithm, the presented technique is optimized for parallel processes and a CUDA GPU implementation. In comparison, the computation time of our GPU algorithm is 10.5 times faster (on a 960 x 540 video with a retarget factor of 25%) than the already efficient CPU implementation.

In 1998, Petitcolas et al. proposed StirMark [14] as a benchmark for image watermarking schemes. The main idea was to introduce a re-sampling process that mimics the analog process of printing and scanning a watermarked image. For digital video, the corresponding concept is a camcorder copy, where a video displayed on a screen is (digitally) recorded using a video camera. As most commercial video streaming systems (VOD, IPTV) and offline distribution (Blu-ray, HDDs for cinemas) are strongly protected by means of DRM, filming a display is actually a relevant use case and a requirement for robust video watermarking systems to survive.

We present a novel system to assist users in choosing suitable exposure values for photography on smartphones. The user specifies the desired shape of the histogram of the captured image by adjusting the parameters of a function. The system then uses the smartphone's camera and varying exposure values to calculate a high dynamic range (HDR) histogram of the scene. It contains the entire brightness range from the darkest to the brightest area of the scene. For any exposure value, the HDR histogram can be used to synthesize a conventional histogram of a low dynamic range (LDR) image as if captured by this exposure value. This process is much faster than capturing the image itself. By comparing a number of synthesized LDR histograms to the user's desired histogram shape, the system determines an exposure value that best meets the user's preference.

We present a novel system for automatically detecting salient image regions in stereoscopic videos. Our proposed algorithm considers information based on three dimensions: salient colors in individual frames, salient information derived from camera and object motion, and depth saliency. These three components are dynamically combined into one final saliency map based on the reliability of the individual saliency detectors. Such a combination allows using more efficient algorithms even if the quality of one detector degrades. For example, we use a computationally efficient stereo correspondence algorithm that might cause noisy disparity maps for certain scenarios. In this case, however, a more reliable saliency detection algorithm such as the image saliency is preferred. To evaluate the quality of the saliency detection, we created modified versions of stereoscopic videos with the non-salient regions blurred. Having users rate the quality of these videos, the results show that most users do not detect the blurred regions and that the automatic saliency detection is very reliable.

This paper is a personal look back at twenty years of research in multimedia content analysis. It addresses the areas of audio, photo and video analysis for the purpose of indexing and retrieval from the perspective of a multimedia researcher. Whereas a general analysis of content is impossible due to the personal bias of the user, significant progress was made in the recognition of specific objects or events. The paper concludes with a brief outlook on the future.

The endeavor of this work is to study the impact of content popularity in a large-scale Peer-to-Peer network, namely KAD. Based on an extensive measurement campaign, we pinpoint several deficiencies of KAD in handling popular content and provide a series of improvements to address such shortcomings. Our work reveals that keywords, which are associated with content, may become popular for two distinct reasons. First, we show that some keywords are intrinsically popular because they are common to many disparate contents: in such case we ameliorate KAD by introducing a simple mechanism that identifies stopwords. Then, we focus on keyword popularity that directly relates to popular content. We design and evaluate an adaptive load balancing mechanism that is backward compatible with the original implementation of KAD. Our scheme features the following properties: 1) it drives the process that selects the location of peers responsible to store references to objects, based on object popularity; 2) it solves problems related to saturated peers that would otherwise inflict a significant drop in the diversity of references to objects, and 3) if coupled with a load-aware content search procedure, it allows for a more fair and efficient usage of peer resources.

Although the importance of video sharing and of social media is increasing from day to day, a full integration of videos into social media is not achieved yet. We have developed a system that maps the concept of hypervideo - allowing to annotate objects in a video - to social media. We define this combination as social video that simultaneously allows a large number of users to contribute to the content of a video. Users can annotate video objects by adding images, text, other videos, Web links, or even communication topics. An integrated chat system allows users to communicate with friends and to link these topics to distinct objects in the video. We analyze the technical functionality and the user acceptance of our social video system in detail. Due to the integration into the social network Facebook more than 12,000 users have already accessed our system.

We present a system that is capable of capturing, processing and displaying High Dynamic Range (HDR) videos at 23 frames per second. For each frame in the video, a sequence of regular images is captured in quick succession at optimally chosen shutter speeds. Intermediate camera motion is compensated and the images are combined into an HDR frame which is tone mapped for display. Our system makes use of novel algorithms that are fast enough for processing the frames in real-time. The most time-consuming operations are parallelized and executed on a graphics card for a speed-up of 15 to 1 over the sequential version.

We present a novel system that allows small handheld devices to detect other devices in the local proximity and to exchange messages with them. The client devices use WLAN to access the system via a web interface and do not require additional software or modification of the device's operating system. The physical closeness of client devices is estimated based on their signal strengths measured by the system's access points. A major advantage compared to indoor positioning systems is the fact that our system does not require a training phase. We conduct a comprehensive evaluation to demonstrate the practicability of our approach.

We propose a novel approach for tracking video objects in interactive multimedia systems. Instead of designing a single tracking algorithm that works well with some templates (video objects to be tracked) but fails with others, our adaptive algorithm uses three distinct tracking techniques with different strengths and weaknesses. The tracking technique that is selected for a given template depends on its visual content and the content of the video. Our approach is robust and allows tracking requests of users to be computed despite an imprecise selection of a template. In addition, our approach is designed to comply with high precision, speed, and scalability to support many users simultaneously. As an exemplary testing environment for this tracking system, an interactive hypervideo system was chosen. The system was integrated into the social network Facebook and used by more than 12,000 users.

We introduce a novel approach for image registration for high dynamic range (HDR) videos. We estimate a translation vector between two low dynamic range (LDR) frames captured at different exposure settings. By using row and column histograms, counting the number of dark and bright pixels in a row or column, and maximizing the correlation between the histograms of two consecutive frames, we reduce the two-dimensional problem to two one-dimensional searches. This saves computation time, which is critical in recording HDR videos in real-time. The robustness of our estimation is increased through application of a Kalman filter. A novel certainty criterium controls whether the estimated translation is used directly or discarded and extrapolated from previous frames. Our experiments show that our proposed approach performs registration more robustly on videos and is 1.4 to 3 times faster than comparable algorithms.

In the efforts to fight piracy of high-valued media content, forensic digital watermarking as a passive content security scheme is a potential alternative to current, restrictive approaches like DRM. In this paper, we present a novel watermarking scheme for videos based on affine geometric transformations. Frames can be modified in an imperceptible manner by applying a small, global rotation, translation, or zooming, which can be detected later on by comparison with the originals. To compensate geometric distortions that have been introduced while a video travels down legal as well as illegal distribution chains, a spatio-temporal synchronization is performed using our video registration toolkit application. To evaluate our approach, we compare it with several other schemes regarding the robustness against common attacks, including camcorder capture.

Virtually every video watermarking technology can benefit from comparison with the original content. For non-blind schemes it is fundamental; for others it is an improvement to increase the watermark’s signal-to-noise ratio by subtract-ing the content that is often noise to the detector. A direct frame-by-frame comparison of the videos is not possible due to the fact that illegal copies of videos usually differ signifi-cantly from their originals caused by different spatial resolu-tion or frame rates, geometric distortions from capturing, or targeted attacks. In this paper, we present a software tool that enables the semi-automatic temporal and spatial syn-chronization of frames and pixels of two similar videos. This process is called registration. We put our focus on utilizing human capabilities with the smallest possible effort, to allow a high overall performance and precision of the registration. An efficient graphical user interface supports the users and visualizes the results of all steps. In addition, we specifically distinguish digitally reproduced copies from analog (cam-corded) copies in which two or more frames are blended into a new frame.

In this demo we present a performance evaluation testbed for peer-to-peer gaming overlays. It consists of a 3D first person shooter game that is designed to run in a simulated network environment as well as on a real network. Simulation with autonomous players (bots) guarantees scalability, a controlled workload, and reproducible results; a prototype deployment on a real network can then validate the simulation results. The information dissemination overlay pSense is implemented as a first subject for evaluation.

Beacon-based Short Message eXchange (BSMX) is a system to exchange small-sized messages between unassociated WLAN devices. We implemented BSMX for the Android operating system and developed several applications to demonstrate the potential of our novel approach.

We propose a global system for acquisition, maintenance and communication of achievements in the real-world. The main focus of the proposal lies on a context-aware notification service for achievements. Users of the system can browse the achievement web application and will only get notifications of users within the same context. The definition of context is based on the network infrastructure of the client accessing the system. Our server utilizes information derived from IP-routing traces to build the notification groups.

We present an approach for integrating voice communication into massively multiplayer online games (MMOG). The currently available third-party software solutions involve additional fees and are not connected to the game logic. Other approaches use the game servers directly for mixing and transmitting speech. Doing so allows for a tight coupling of speech and in-game events but consumes large amounts of bandwidth and computational power on the servers. Our novel idea is a mix between server-based signaling and peer-to-peer data transmission. While the entire game context resides on the server, audio streams are transmitted in a peer-to-peer fashion and processed at the peer nodes only. This technique splits up the workload among all machines while still allowing to relate speech processing to game events. We further improve the processing performance on the clients by using SOUND, a novel technique for distance based resampling.

In terms of intercarrier compensation traffic flows are measured to allocate the costs between networks. This method provides a poor basis for sharing any costs. In this work we analyze the benefits of the traffic differentiation on the interconnection charges in unilateral and bilateral arrangements. We determine an original initiator of a transmission and compensate differently for the distinguished traffic flows. The presented approach was compared with the existing solutions, which perform cost compensation based on the traffic flows.

In contrast to many applications on the PC and in the Internet which are accessible to visually impaired people today, making electronic music with limited eye-sight is still a challenge. Standard software and hardware are both strongly dominated by graphical output. In order to close this cap, we developed a MIDI (Musical Instrument Digital Interface) sequencer with audio-feedback and a new interaction paradigm which eliminates interaction with the PC's keyboard and screen. The blind musician relies solely on input via the instrument itself. He can both, record and play music via the instrument's black & white keys but at the same time control all functions of a multi-track MIDI sequencer without ever taking the hands off the instrument. We also use the MIDI-connection for coding different kinds of feedback to the user in an efficient way. The software which runs on a PC and is connected to an electronic instrument has been evaluated and improved extensively and is made available free of charge for visually impaired and normal-sighted people.

The presentation of multimedia data and especially of high resolution videos on small mobile devices is still a great challenge today. Both cropping of borders and scaling of frames may result in the removal of essential content of videos or lost details due to the reduced size of the visual content. Another major problem emerges if the aspect ratio of the original video and the display of the mobile device differ. User evaluations indicate that changing the aspect ratio may reduce the visual quality of videos significantly. In this paper, we present the new FSCAV algorithm (Fast Seam Carving for Size Adaptation of Videos) to adapt the size of videos to the limited display resolution and different aspect ratios of handheld mobile devices. The general idea of the seam carving algorithm for still images is to remove seams in images so that the essential content is preserved. We extended this technique which works very well for images to create videos without jitter or visible artifacts. A major feature of our FSCAV algorithm is the low computational complexity which enables an efficient adaptation of videos to small screens. Nevertheless, severe distortions are clearly visible in some shots of the adapted videos. We present a new heuristic to identify shots with such a low visual quality. If the quality drops below a threshold, a different adaptation technique is used for this shot (e.g., scaling or cropping). User evaluations confirm a very high visual quality of our approach.

We present our system for automatic lecture recording. In contrast to traditional lecture recording systems our approach aims to imitate a real camera team, consisting of multiple cameramen and a director, in order to make the recording more vivid. At first, we introduce the environment. Then, we present our approach, beginning with the director module, followed by the cameraman module and the sensor tools module, referring to the jobs of the respective human originals. The director is based on an Extended Finite State Machine, with transition conditions depending on input from sensor tools. The cameraman automatically controls iris, focus, etc., and also takes basic cinematographic rules into account. The video concludes with an example result of our virtual camera team of a real lecture. A video demo of our approach is available at [4].

In this paper we present an optimized approach to capture high dynamic range (HDR) images. It is based on existing methods of creating HDR images by fusing a set of differently exposed low dynamic range (LDR) images. We optimize the capturing process of LDR images towards improved capture speed by using partial re-exposures. That is, we make use of the idea that it is not always necessary to capture full size images when only small portions of the scene require HDR. By analyzing captured images for badly exposed regions and re-exposing selectively, we save overall capture time and increase the frame rate when image sequences are recorded.

A challenge for the development of mobile applications is the heterogeneity of the different device classes. For instance, an application which runs well on a personal digital assistant (PDA) might be unsuitable for mobile phones. To facilitate the development of mobile applications we have develope

Location-based services in general require information about the position of certain objects. For instance, for a navigation service the position of the user needs to be known. This position is usually provided by a positioning system. However, it is typical for all positioning systems that they are

In this demo proposal we present Planet Π4, a Massively Multiplayer Online Game (MMOG) developed to evaluate and compare peer-to-peer-based MMOG systems with scalability in mind. The game requires low network latency and creates frequent game state updates. It has a modular architecture that can be adapted and extended with new functionality. Using this modular design we have developed different peer-to-peer infrastructures. Workshop participants will be able to play the game and compare the versions with each other.

Fingerprinting is a popular technology for 802.11-based positioning systems: Radio characteristics from different access points are measured at various positions and stored in a database. The database is copied to all mobile devices, and in case that a position estimate is needed, the device compares its currently measured radio characteristics with all the database entries. In this paper, we present two on-demand fingerprint selection algorithms to avoid the cumbersome and time-consuming approach of manually copying all fingerprints. Our algorithms only request those fingerprints from the database that are currently required to compute a position. The two algorithms differ in the way they shape the region for which fingerprints are requested. On-demand selection also allows storage-restricted mobile devices to utilize the positioning system. We carefully evaluate our algorithms in a real-world experiment. The results show that our algorithms do not harm the position accuracy of the positioning system. In addition, we analyze the space requirements of our algorithms and show that the typical constraints of mobile devices are met.

In vehicular ad-hoc networks unicast packet forwarding can be separated into the one-dimensional highway case and the two-dimensional city case; in this paper, we deal with the latter. We survey existing position-based routing protocols and present GRANT, our own approach of greedy routing with an abstract neighbor table. We simulate each protocol in our city scenario of Karlsruhe, consisting of streets with a length of 66 km, 390 junctions, and radio obstacles derived from high-definition satellite images. We also simulate the protocols with a FACE-2- and a distance vector-based recovery strategy. As a result we propose GRANT as a routing protocol for unicast city scenarios.

In mobile ad-hoc networks, the multicast paradigm is of central importance. It can help to save scarce medium bandwidth if packets are to be delivered to multiple destinations. We consider the problem of congestion control for multicast traffic in wireless multihop networks. We propose to apply a congestion control concept which is tailored to the very special properties of the wireless multihop medium: implicit hop-by-hop congestion control. The idea, so far only having been considered for unicast traffic, is here generalized to multicast. We implement it in the Backpressure Multicast Congestion Control (BMCC) protocol, with a focus on how to realize it in combination with geographic multicast routing in the Scalable Position-Based Multicast (SPBM) protocol. Our evaluation points out a number of highly desirable properties of the proposed scheme. In particular, it achieves and maintains high throughput and high packet delivery ratios at low packet latencies, even in the presence of significant network load.

While indoor positioning systems based on 802.11 and fingerprinting work pretty well, it is unknown how to distribute large amounts of fingerprint data to mobile devices. Even worse, many mobile devices are restricted in terms of memory capabilites. We identified three classes of mobile devices representing different levels of storage capabilities. For each of these classes, we present a distribution approach for fingerprint data: the Union of Access Points (UAP), the Strongest Access Point (SAP), and the Intersection of Access Points (IAP) algorithm. These approaches utilize the 802.11 network to download only a subset of the fingerprint data to a mobile device. The subset covers the area close to the actual position of the mobile device in such a way that position estimates can be computed. The size of the subset is different for each of the three algorithms.

The capturing of panoramic 360° images has become a popular photographic technique. While a panoramic image gives an impressive view of the environment, many people have difficulties to understand the spatial scene arrangement from this flat image. In this paper, we present a new visualization technique for panoramic images based on a coarse reconstruction of the indoor environment, in which the panorama was captured. Applications of this are, for example, real-estate or hotel advertising, featuring virtual tours through the apartment. We use a semi-automatic reconstruction process, in which the user marks the room corners in the panoramic images. These can be translated into viewing-angle measurements, from which our algorithms can compute the exact sizes of the walls, based on a pre-defined geometric model.

Not only the communication capabilities of 802.11, but also the capability to determine the position of mobile devices make 802.11 highly appealing for many application areas. Typically, a mobile device that wants to identify its position regularly performs active or passive scans to obtain the signal strength measurements of neighboring access points. However, so far, no investigations are known to have been launched into how regular scanning affects concurrent data transmissions from an end-user point of view. In this paper, we explore how common data communication is affected while actively or passively scanning at the same time. Furthermore, we present a novel scan scheme called monitor sniffing. Monitor sniffing exploits the fact that 802.11 operates on overlapping channels by overhearing the wireless interface. We have implemented our monitor sniffing algorithm using commodity 802.11g hardware, and we demonstrate that it does not disturb concurrent data communication

A large number of videos cannot be visualized on mobile devices (e.g.,PDAs or mobile phones)due to an inappropriate color depth of the displays. Important details are lost if the color depth is reduced. A major challenge is the preservation of the semantic content in spite of this fact. In this paper, we present a novel adaptation algorithm to enable the playback of videos on color-limited mobile devices. Dithering algorithms diffuse the error to neighbor pixels and do not work very well for videos. We propose a non-linear transformation of luminance values and use textures in combination with edges to reduce the color depth in videos.

A large number of previously recorded videos cannot be directly visualized on mobile devices like PDAs or mobile phones due to an inappropriate screen resolution of their displays. Transcoding can be used to change the resolution, however, the usual transcoding algorithms have problems preserving the semantic content. For instance, superimposed text is unreadable if the character size drops below a certain value. In this paper, we present a novel adaptation algorithm to scale and crop videos while preserving their semantic content. Semantic features in a shot are combined to select a suitable region to be resented in the adapted video.

In order to prolong a sensor's operational lifetime, a main challenge in the field of sensor networks is energy efficiency. Since much energy is spent for the radio communication, many approaches exist that put sensor nodes into a sleep mode with the communication radio turned off. We propose a new Topology and Energy Control Algorithm called TECA that uses a very simple clustering approach and connects these clusters in a very energy-efficient way. Using the concept of virtual links, passive nodes decide in a distributed way if they should join the topology and stay active or rather go into a low-powered sleep mode. Compared to other approaches, TECA establishes a well-connected topology and is able to save more energy. By means of simulations, we show that TECA outperforms the two other approaches in terms of operational lifetime, packet delivery, and network connectivity.

Vehicular ad hoc networks (VANETs) enable new applications by providing self-organizing vehicle-to-vehicle and vehicle-to-roadside communication. Some of these applications require reliable, in-order data delivery across end-to-end connections. The performance of a vehicular transport protocol (VTP) that provides such a service depends on its ability to adapt quickly to the varying path characteristics of highly dynamic environments. This paper studies path characteristics of VANETs in highway scenarios. An analytical evaluation derives upper bounds on the expected connectivity and disruption duration. Simulations validate these results and study further metrics, such as packet loss, packet reordering and round trip times. The paper also briefly outlines a preliminary VTP design that incorporates these analytical results.

Energy-efficient forwarding becomes important if resources and battery lifetime are limited such as in wireless sensor networks. Although widely used, simple hop-based forwarding along a path from one node towards a sink can be very inefficient in terms of delivery rate as well as energy efficiency, especially in lossy environments. We will show that just minimizing the expected number of transmissions within the network is not always the most efficient forwarding strategy. Using a realistic link loss model, we derive two new forwarding schemes named single-link and multi-link energy-efficient forwarding that trade off delivery rate and energy costs best by maximizing energy efficiency. Multi-link forwarding further benefits from addressing multiple receivers during packet forwarding, instead of a single one. By mathematical analyses, extensive simulations, and experimental evaluations we contrast the performance of our approaches against a comprehensive framework of other forwarding strategies

Position-based routing suffers from inaccurate neighbor positions, especially at low beaconing rates. In this paper we propose to add dead-reckoning to the forwarder selection process to predict the positions of neighboring nodes. We have carried out simulations to investigate the consequences of this modification and explain the trade-offs. With the modified algorithm, we achieve a complete packet delivery for beaconing intervals of as much as 6 seconds for a medium-density German highway setting. We will show that the dead-reckoning scheme results in (a) less beacon traffic with equal or better neighbor position prediction and (b) less overhead induced by transmit failures when using the same beaconing frequencies.

No abstract available.

The curvature scale space (CSS) technique, which is also part of the MPEG-7 standard, is a robust method to describe complex shapes. The central idea is to analyze the curvature of a shape and derive features from inflection points. A major drawback of the CSS method is its poor representation of convex segments: Convex objects cannot be represented at all due to missing inflection points. We have extended the CSS approach to generate feature points for concave and convex segments of a shape. This generic approach is applicable to arbitrary objects. In the experimental results, we evaluate as a comprehensive example the automatic recognition of characters in images and videos.

Discrete-event network simulation is a major tool for the research and development of mobile ad-hoc networks (MANETs). These simulations are used for debugging, teaching, understanding, and performance-evaluating MANET protocols. For the first three tasks, visualization of the processes occurring in the simulated network is crucial for verification and credibility of the generated results. Working with the popular network simulator ns-2, we have not yet found a visualization toolkit capable of reading native ns-2 trace files and providing means to change the evaluated parameters without changing the visualization software. Thus, we developed Huginn, a software providing an intuitive way to visualize simulation properties and to determine how they should be displayed without the need of programming. In addition, Huginn has a 3D interface allowing an improved exploitation of the (human) user's perceptual system. It helps to handle the significant cognitive load associated with the mental reconstruction of simulated network processes. Besides presenting the software interface and architecture, we describe algorithmic solutions that might be of a more general interest for similar problems.

Recording systems and media servers for networked audio and video streams have become an important part of today's Internet. In contrast to this, only a few recording and playback solutions currently exist for the data streams of interactive media applications (e.g., shared whiteboards and distributed virtual environments). So far these solutions are application-specific: individual algorithms and implementations are required for each application that is to be recorded. In this paper, we are proposing generic algorithms for the recording and playback of interactive media streams. These algorithms are based on a common model for the class of interactive media. They enable full random access to recordings by initializing the replaying applications with the required state information (e.g., the current slide in a recorded presentation). We have implemented these algorithms in the Interactive Media on Demand (IMoD) system. In order to interpret the semantics of an interactive media stream, the system requires that the Real-Time Application-Level Protocol for Distributed Interactive Media (RTP/I) protocol is used for the framing of the transmitted data. Any application using RTP/I can be recorded directly using the system without any modification. Interactive media streams not using RTP/I can be recorded using the generic recording algorithms. However, they require an adaptation of the system so that it is able to extract a minimal set of information from the application-level protocol of these streams. In addition to the generic recording algorithms, we present the architecture and major design considerations of the system and discuss the experiences gained from recording different interactive media applications.

We present a new semiautomatic segmentation tool, which is motivated by the intelligent scissors algorithm, but which uses a modified concept of user-interaction. This new interface provides better capabilities for modifying previous segmentation results. The advantage of the new approach is that it enables to gradually increase the quality of the segmentation. The segmentation tool is based on a shortest circular path search within a corridor that is drawn by the user along the object boundary. For this purpose, we present a new algorithm for computing the shortest circular paths. Our algorithm is so fast that it almost achieves the speed of a regular noncircular shortest path search, while still ensuring an optimal solution.

The background subtraction algorithm is a frequently-used object segmentation technique because of its algorithmic simplicity. However, we show that, for general rotational camera-motion, it is impractical, or even impossible, to use a single background image. As a solution, we propose to use multi-sprite backgrounds which enables processing of arbitrary rotational camera-motion. The paper describes a complete video-object segmentation system employing multi-sprites. The system generates object masks and background sprites that are compatible with MPEG-4 object-oriented video-coding tools. Good segmentation results are also obtained for sequences which cannot be processed with ordinary background images.

A video summary is a sequence of video clips extracted from a longer video. Much shorter than the original, the summary preserves its essential messages. In the ECHO (European Chronicles On-line) project, a system was developed to store and manage large collections of historical films for the preservation of cultural heritage. At the University of Mannheim, we have developed the video summarization component of the ECHO system. We discuss the particular challenges the historical film material poses, and how we have designed new video processing algorithms and modified existing ones to cope with noisy black-and-white films.

The degree of dynamics with respect to changes of the network's topology strongly affect the performance of a wireless mobile ad hoc network. Main reasons for topological changes are (i) node mobility and (ii) wireless radio fluctuations, e.g., due to fading effects. The impact of node mobility on ad hoc network performance has already been studied intensively. However these studies usually do not consider temporal fluctuations of the wireless channel. We quantitatively study the impact of radio fluctuations on the performance of wireless ad hoc networks. Based on field trial measurements of IEEE 802.11b wireless LAN communication in a static line-of-sight scenario, we derive a basic model for non-deterministic, but temporally dependent, received signal power variations. According to the derived model, we quantify the impact of radio fluctuations on topological change rate (TCR) and link stability as relevant ad hoc network performance metrics via simulation. The effects of pure node mobility and the effects of signal strength fluctuations, as well as the combination of node mobility and fluctuations, are studied. We demonstrate that signal strength fluctuations have a significant impact on ad hoc network performance metrics sometimes 'outperforming' the impact of node mobility. Thus, non-deterministic radio fluctuations cannot be ignored when designing robust ad hoc network protocols based on ad hoc network simulation and analysis.

Object-oriented coding in the MPEG-4 standard enables the separate processing of foreground objects and the scene background (sprite). Since the background sprite only has to be sent once, transmission bandwidth can be saved. This paper shows that the concept of merging several views of a non-changing scene background into a single background sprite is usually not the most efficient way to transmit the background image. We have found that the counter-intuitive approach of splitting the background into several independent parts can reduce the overall amount of data. For this reason, we propose an algorithm that provides an optimal partitioning of a video sequence into independent background sprites (a multi-sprite), resulting in a significant reduction of the involved coding cost. Additionally, our algorithm results in background sprites with better quality by ensuring that the sprite resolution has at least the final display resolution throughout the sequence. Even though our sprite generation algorithm creates multiple sprites instead of a single background sprite, it is fully compatible with the existing MPEG-4 standard. The algorithm has been evaluated with several test-sequences, including the well-known Table-tennis and Stefan sequences. The total coding cost could be reduced by factors of about 2.7 or even higher.

In this paper, we investigate how consistency can be established for replicated applications changing their state in reaction to user-initiated operations as well as the passing of time. Typical examples of these applications are networked computer games and distributed virtual environments. We give a formal definition of the terms consistency and correctness for this application class. Based on these definitions, it is shown that an important tradeoff relationship exists between the responsiveness of the application and the appearance of short-term inconsistencies. We propose to exploit the knowledge of this tradeoff by voluntarily decreasing the responsiveness of the application in order to eliminate short-term inconsistencies. This concept is called local-lag. Furthermore, a timewarp scheme is presented that complements local-lag by guaranteeing consistency and correctness for replicated continuous applications. The computational complexity of the timewarp algorithm is determined in theory and practice by examining a simple networked computer game. The timewarp scheme is then compared to the well-known dead-reckoning approach. It is shown that the choice between both schemes is application-dependent.

Knowing the background image of a video scene simplifies the general video-object segmentation problem and therefore it is required by several automatic segmentation algorithms. This paper presents a new background estimation algorithm which is applicable to complex video sequences where many objects are simultaneously visible and the background is visible for a short time period only. The algorithm applies a rough segmentation of the input images into foreground and background regions to exclude the foreground objects from background synthesis. This prevents a bias of the synthesized background image towards the color of foreground objects. Experiments show that the obtained background images differ significantly less from the real background than those obtained with previous algorithms.

Clustering techniques have been widely used in automatic video-summarization applications to group shots with comparable content. We enhance the popular k-means clustering algorithm to integrate user-supplied domain-knowledge into the cluster generation step. This provides a convenient way to exclude scenes from the summary which are a-priori known to be irrelevant. Furthermore, we added an additional, time-constrained clustering step preceding the scene clustering step to exclude short ranges with transitional content. This makes the algorithm robust to fading and wipe-effects in the input without requiring explicit cut detection.

No abstract available.

Distributed interactive media are media that involve communication over a computer network as well as user interactions with the medium itself. Examples of this kind of media are shared whiteboard presentations and networked computer games. One key problem of this media class is that a large amount of common functionality is currently redesigned and redeveloped for each single medium. In order to solve this problem we present a media model and an application level protocol called RTP/I. Derived from the experience gained with audio and video transmission using RTP, RTP/I is defined as a new protocol framework which reuses many aspects of RTP while it is thoroughly adapted to meet the demands of distributed interactive media. By identifying and supporting the common aspects of distributed interactive media RTP/I allows the reuse of key functionality in form of generic services. Furthermore RTP/I makes it possible for applications of different vendors to interact with each other in a standardized way.

This panel will discuss a recommendation for curricula guidelines for courses about multimedia. Based on conference input, the guidelines will be modified for review prior to future publication by ACM (with other groups). The recommendation will be one of the main results of a June 2000 Dagstuhl workshop led by 4 of the panelists. Dr. Heller, the 5th panelist, also attended that workshop, and is co-PI with the panel moderator on a directly related NSF project, Curriculum Resources in Interactive Multimedia, CRIM, see http://ei.cs.vt.edu/~crim. Each of the panelists has taught courses about multimedia. Each is interested in developing tools/demonstrations/resources to help in those course. Each has a particular area of interest in the multimedia field. Together they constitute a representative group among those who will contribute to and benefit from curricula resources in multimedia.

Active networks allow protocol processing code to be loaded dynamically into network nodes at run-time. This code can perform tasks specific to a stream of packets or even a single packet. In this paper we compare two active network architectures: the active node transfer system (ANTS) and the messenger system (M0). We have implemented a robust audio multicast protocol and a layered video multicast protocol with both active network systems. We discuss the differences of the two systems, evaluate architectural strengths and weaknesses, compare the runtime performance, and report practical experience and lessons learned.

This paper describes the theoretic framework and applications of automatic audio content analysis.After explaining the basic properties of audio analysis, we present a toolbox being the basis for the development of audio analysis algorithms.We also describe new applications which can be developed using the toolset, among them music indexing and retrieval as well as violence detection in the sound track of videos.

No abstract available.

No abstract available.

We describe a system for storing, transmitting, and presenting digital movies in a computer network. The hardware used in the system is standard hardware, as found in typical workstations today; no special hardware is required, but if available it can be used to provide better performance. The XMovie system has several innovative features. First, it contains a new algorithm for the gradual adaptation of the color lookup table during the presentation of the movie to ensure optimal color quality on low-end workstations. Second, it is a multistandard system supporting the compression techniques MPEG, Motion JPEG, and a newly developed extension to the well-known Color Cell Compression method. Third, it contains AdFEC, a new adaptable forward error correction method for our movie transmission protocol.

In this paper we describe the tool-supported specification and implementation of a multimedia communication protocol on parallel hardware. MCAM is an application layer protocol for movie control, access and management. We specify the full MCAM protocol together with ISO presentation and session layers in Estelle. Using a code generator, we derive parallel C++ code from the specification. The code is compiled and executed on a multiprocessor system under OSF/1 and on UNIX workstations. Measurements show the performance speedup gained by several different configurations of parallel units. We also report on experiences with our methodology.>

Article Free Access Share on MCAM: an application layer protocol for movie control, access, and management Authors: Ralf Keller View Profile , Wolfgang Effelsberg View Profile Authors Info & Claims MULTIMEDIA '93: Proceedings of the first ACM international conference on MultimediaSeptember 1993 Pages 21–29https://doi.org/10.1145/166266.166268Published:01 September 1993Publication History 11citation477DownloadsMetricsTotal Citations11Total Downloads477Last 12 Months12Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

A global schema is an integrated view of heterogeneous databases. Identifying common types of information from the various local Schemas is an important part of designing a global schema. After matching the entity types and attributes, the designer constructs the global schema by applying a set of integration operators. In this paper, we propose two types of matching techniques and discuss their use in global schema design. Entity type matching partitions the entity types of the local Schemas into subsets with common information. Attributes within each entity type cluster are then matched according to the similarity of their meaning and scope. We define assertion types for both kinds of matching and provide an algorithm to check the consistency and completeness of attribute assertions.

This paper discusses the implementation of a database buffer manager as a component of a DBMS. The interface between calling components of higher system layers and the buffer manager is described; the principal differences between virtual memory paging and database buffer management are outlined; the notion of referencing versus addressing of database pages is introduced; and the concept of fixing pages in the buffer to prevent uncontrolled replacement is explained. Three basic tasks have to be performed by the buffer manager: buffer search, allocation of frames to concurrent transactions, and page replacement. For each of these tasks, implementation alternatives are discussed and illustrated by examples from a performance evaluation project of a CODASYL DBMS.

This work investigates one aspect of the performance of CODASYL database systems: the data reference behavior. We introduce a model of database traversals at three levels: the logical, internal, and physical levels. The mapping between the logical and internal levels is defined by the internal schema, whereas the mapping between the internal and the physical levels depends on cluster properties of the database. Our model explains the physical reference behavior for a given sequence of DML statements at the logical level. Software has been implemented to monitor references in two selected CODASYL DBMS applications. In a series of experiments the physical reference behavior was observed for varying internal schemas and cluster properties of the database. The measurements were limited to retrieval transactions, so that a variety of queries could be analyzed for the same well-known state of the database. Also, all databases were relatively small in order to allow fast reloading with varying internal schema parameters. In all cases, the database transactions showed less locality of reference than do programs under virtual memory operating systems; some databases showed no locality at all. No evidence of physical sequentiality was found. This suggests that standard page replacement strategies are not optimal for CODASYL database buffer management; instead, replacement decisions in a database buffer should be based on specific knowledge available from higher system layers.