8373854
Scalably supporting durable subscriptions in a publish/subscribe system
We describe algorithms to scalably support durable subscriptions in a publish-subscribe system. Durable subscriptions are guaranteed exactly-once message delivery, despite periods of disconnection from the system. Our algorithms persistently log each message only once in the system, and can support administratively specified ’early-release’ policies that reclaim persistent storage in the presence of misbehaving durable subscribers. To efficiently recover messages missed by a disconnected durable subscriber, without refiltering messages published while the subscriber was disconnected, we persistently log filtering information in a manner optimized for the read/write pattern of durable subscriptions. Consolidation of data-structures across all subscribers that are done with catching up (after a disconnection), helps the system support a larger number of subscribers. We experimentally demonstrate the low-latency and scalability properties of our implementation, both in the presence and absence of failures.
2358820
Subscription Propagation and Content-Based Routing with Delivery Guarantees
Subscription propagation enables efficient content-based routing in publish/subscribe systems and is a challenging problem when it is required to support reliable delivery in networks with redundant routes. We have designed a generic model and a highly-asynchronous algorithm accomplishing these goals. Existing algorithms can be interpreted as different encodings and optimizations of the generic algorithm and hence their correctness can be derived from the generic algorithm.
5871849
Exactly-once delivery in a content-based publish-subscribe system
This paper presents a general knowledge model for propagating information in a content-based publish-subscribe system. The model is used to derive an efficient and scalable Protocol for exactly-once delivery to large numbers (tens of thousands per broker) of content-based subscribers in either publisher order or uniform total order Our protocol allows intermediate content filtering at each hop, but requires persistent storage only at the publishing site. It is tolerant of message drops, message reorderings, node failures, and link failures, and maintains only "soft" state at intermediate nodes. We evaluate the performance of our implementation both under failure-free conditions and with fault injection.
15795709
Lattice-based flow field modeling
We present an approach for simulating the natural dynamics that emerge from the interaction between a flow field and immersed objects. We model the flow field using the lattice Boltzmann model (LBM) with boundary conditions appropriate for moving objects and accelerate the computation on commodity graphics hardware (GPU) to achieve real-time performance. The boundary conditions mediate the exchange of momentum between the flow field and the moving objects resulting in forces exerted by the flow on the objects as well as the back-coupling on the flow. We demonstrate our approach using soap bubbles and a feather. The soap bubbles illustrate Fresnel reflection, reveal the dynamics of the unseen flow field in which they travel, and display spherical harmonics in their undulations. Our simulation allows the user to directly interact with the flow field to influence the dynamics in real time. The free feather flutters and gyrates in response to lift and drag forces created by its motion relative to the flow. Vortices are created as the free feather falls in an otherwise quiescent flow.
6777571
Hierarchical and multi-resolution representation of protein flexibility
MOTIVATION
Conformational rearrangements during molecular interactions are observed in a wide range of biological systems. However, computational methods that aim at simulating and predicting molecular interactions are still largely ignoring the flexible nature of biological macromolecules as the number of degrees of freedom is computationally intractable when using brute force representations.


RESULTS
In this article, we present a computational data structure called the Flexibility Tree (FT) that enables a multi-resolution and hierarchical encoding of molecular flexibility. This tree-like data structure allows the encoding of relatively small, yet complex sub-spaces of a protein's conformational space. These conformational sub-spaces are parameterized by a small number of variables and can be searched efficiently using standard global search techniques. The FT structure makes it straightforward to combine and nest a wide variety of motion types such as hinge, shear, twist, screw, rotameric side chains, normal modes and essential dynamics. Moreover, the ability to assign shapes to the nodes in a FT allows the interactive manipulation of flexible protein shapes and the interactive visualization of the impact of conformational changes on the protein's overall shape. We describe the design of the FT and illustrate the construction of such trees to hierarchically combine motion information obtained from a variety of sources ranging from experiment to user intuition, and describing conformational changes at different biological scales. We show that the combination of various types of motion helps refine the encoded conformational sub-spaces to include experimentally determined structures, and we demonstrate searching these sub-spaces for specific conformations.
14675910
Generalized dimension-reduction framework for recent-biased time series analysis
Recent-biased approximations have received increased attention recently as a mechanism for learning trend patterns from time series or data streams. They have shown promise for clustering time series and incrementally pattern maintaining. In this paper, we design a generalized dimension-reduction framework for recent-biased approximations, aiming at making traditional dimension-reduction techniques actionable in recent-biased time series analysis. The framework is designed in two ways: equi-segmented scheme and vari-segmented scheme. In both schemes, time series data are first partitioned into segments and a dimension-reduction technique is applied to each segment. Then, more coefficients are kept for more recent data while fewer kept for older data. Thus, more details are preserved for recent data and fewer coefficients are kept for the whole time series, which improves the efficiency greatly. We experimentally evaluate the proposed approach, and demonstrate that traditional dimension-reduction techniques, such as SVD, DFT, DWT, PIP, PAA, and landmarks, can be embedded into our framework for recent-biased approximations over streaming time series.
1405072
Effective document clustering for large heterogeneous law firm collections
Computational resources for research in legal environments have historically implied remote access to large databases of legal documents such as case law, statutes, law reviews and administrative materials. Today, by contrast, there exists enormous growth in lawyers' electronic work product within these environments, specifically within law firms. Along with this growth has come the need for accelerated knowledge management---automated assistance in organizing, analyzing, retrieving and presenting this content in a useful and distributed manner.In cases where a relevant legal taxonomy is available, together with representative labeled data, automated text classification tools can be applied. In the absence of these resources, document clustering offers an alternative approach to organizing collections, and an adjunct to search.To explore this approach further, we have conducted sets of successively more complex clustering experiments using primary and secondary law documents as well as actual law firm data. Tests were run to determine the efficiency and effectiveness of a number of essential clustering functions. After examining the performance of traditional or hard clustering applications, we investigate soft clustering (multiple cluster assignments) as well as hierarchical clustering. We show how these latter clustering approaches are effective, in terms of both internal and external quality measures, and useful to legal researchers. Moreover, such techniques can ultimately assist in the automatic or semi-automatic generation of taxonomies for subsequent use by classification programs.
1134220
The design of an interactive online help desk in the Alexandria Digital Library
In large software systems such as digital libraries, electronic commerce applications, and customer support systems, the user interface and system are often complex and difficult to navigate. It is necessary to provide users with interactive online support to help users learn how to effectively use these applications. Such online help facilities can include providing tutorials and animated demonstrations, synchronized activities between users and system supporting staff for real time instruction and guidance, multimedia communication with support staff such as chat, voice, and shared whiteboards, and tools for quick identification of user problems. In this paper, we investigate how such interactive online help support can be developed and provided in the context of a working system, the Alexandria Digital Library (ADL) for geospatially-referenced data. We developed an online help system, AlexHelp!. AlexHelp! supports collaborative sessions between the user and the librarian (support staff) that include activities such as map browsing and region selection, recorded demonstration sessions for the user, primitive tools for analyzing user sessions, and channels for voice and text based communications. The design of AlexHelp! is based on user activity logs, and the system is a light-weight software component that can be easily integrated into the ADL user interface client. A prototype of AlexHelp! is developed and integrated into the ADL client; both the ADL client and AlexHelp! are written in Java.