61900310
Infopipes: an abstraction for multimedia streaming
To simplify the task of building distributed streaming applications, we propose a new abstraction for information flow - Infopipes. Infopipes make information flow primary, not an auxiliary mechanism that is hidden away. Systems are built by connecting predefined component Infopipes such as sources, sinks, buffers, filters, broadcasting pipes, and multiplexing pipes. The goal of Infopipes is not to hide communication, like an RPC system, but to reify it: to represent communication explicitly as objects that the program can interrogate and manipulate. Moreover, these objects represent communication in application-level terms, not in terms of network or process implementation.
2348760
Adaptive live video streaming by priority drop
In this paper we explore the use of priority progress streaming (PPS) for video surveillance applications. PPS is an adaptive streaming technique for the delivery of continuous media over variable bit-rate channels. It is based on the simple idea of reordering media components within a time window into priority order before transmission. The main concern when using PPS for live video streaming is the time delay introduced by reordering. In this paper we describe how PPS can be extended to support live streaming and show that the delay inherent in the approach can be tuned to satisfy a wide range of latency constraints while supporting fine-grain adaptation.
37356020
Thread transparency in information flow middleware
Applications that process continuous information flows are challenging to write because the application programmer must deal with flow-specific concurrency and timing requirements, necessitating the explicit management of threads, synchronization, scheduling and timing. We believe that middleware can ease this burden, but many middleware platforms do not match the structure of these applications, because they focus on control-flow centric interaction models such as remote method invocation. Indeed, they abstract away from the very things that the informatian-flow centric programmer must control.This paper describes Infopipes--a new high-level abstraction for information flow applications--and a middleware framework that supports them. Infopipes handle the complexities associated with control flow and multi-threading, relieving the programmer of these tasks. Starting from a high-level description of an information flow pipeline, the framework determines which parts of a pipeline require separate threads or coroutines, and handles synchronization transparently to the application programmer. The framework also gives the programmer the freedom to write or reuse components in a passive style, even through the configuration will actually require the use of a thread or coroutine. Conversely, it is possible to write a component using a thread and know that the thread will be eliminated if it is not needed in a pipeline. This allows the most appropriate programming model to be chosen for a given task, and existing code to be reused irrespective of its activity model.
10932878
Thread Transparency in Information Flow Middleware
Applications that process continuous information flows are challenging to write because the application programmer must deal with flow-specific concurrency and timing requirements, necessitating the explicit management of threads, synchronization, scheduling and timing. We believe that middleware can ease this burden, but middleware that supports control-flow centric interaction models such as remote method invocation does not match the structure of these applications. Indeed, it abstracts away from the very things that the information-flow centric programmer must control
3062410
Conceptualizing the three dimensions of inter-organizational communities of practice
The paper describes and analyzes the way in which a particular case company stimulated the development of communities of practice as a vehicle for encouraging product and process innovation. Some unique features of these communities were explored. In particular the involvement of retired engineers and the inclusion of external parties were both found to contribute to the effectiveness of these communities. More specifically, the effectiveness of these communities were discussed in relation to three dimensions – structural, strategic and technological. Analysis of these three dimensions was useful in examining the role played by these communities within the case company. The paper concludes by considering the lessons for managers that can be drawn from this analysis. Newell,Huang,Galliers Conceptualizing the three dimensions of Inter-Organizational
14986573
Sharing ontology schema information for Web service integration
In spite of many standards efforts, Web services with similar or compatible functionalities often have heterogeneous semantics. One reason is the disparate ontologies used for service descriptions. In order to compare and compose Web services, the ability to merge different ontologies is essential. This paper describes an approach to align numerous, independently designed ontologies. Our approach is a completely automated one, without the need for prior agreement on semantics. It incorporates WordNet and heuristic reasoning and infers new knowledge by self-learning. Our system provides a solid base for the seamless integration of Web services.
1720329
Toward Inductive Logic Programming for Collaborative Problem Solving
In this paper, we tackle learning in distributed systems and the fact that learning does not necessarily involve the participation of agents directly in the inductive process itself. Instead, many systems frequently employ multiple instances of induction separately. The paper's main contribution is a new approach that tightly integrates processes of induction between distributed agents, based on inductive logic programming techniques, for a wider class of problem solving tasks. The approach combines inverse entailment with an epistemic approach to reasoning about knowledge, facilitating a systematic approach to the sharing of knowledge and invention of predicates only when required. We illustrate the approach for learning declarative program fragments and for a well-known path planning problem and compare results empirically to (multiple instances of) single agent-based induction over varying distributions of data. Given a chosen path planning algorithm, our algorithm enables agents to combine their local knowledge in an effective way to avoid central control while significantly reducing communication costs.
8122062
High quality splatting and volume synthesis
Our recent improvements to volume rendering using splatting allow for an accurate functional reconstruction and volume integration, occlusion-based acceleration, post-rendering classification and shading, 3D texture mapping, bump mapping, anti-aliasing and gaseous animation. A pure software implementation requiring low storage and using simple operations has been implemented to easily support these operations. This paper presents a unified framework and discussion of these enhancements, as well as extensions to support hypertextures efficiently. Discussions on appropriate volume models for effective usage of these techniques is also presented.
2763612
Information Marginalization on Subgraphs
Real-world data often involves objects that exhibit multiple relationships; for example, ‘papers' and ‘authors' exhibit both paper-author interactions and paper-paper citation relationships. A typical learning problem requires one to make inferences about a subclass of objects (e.g. ‘papers'), while using the remaining objects and relations to provide relevant information. We present a simple, unified mechanism for incorporating information from multiple object types and relations when learning on a targeted subset. In this scheme, all sources of relevant information are marginalized onto the target subclass via random walks. We show that marginalized random walks can be used as a general technique for combining multiple sources of information in relational data. With this approach, we formulate new algorithms for transduction and ranking in relational data, and quantify the performance of new schemes on real world data—achieving good results in many problems.