Current data integration approaches by bioinformaticians frequently involve extracting data from a wide variety of public and private data repositories, each with a unique vocabulary and schema, via scripts. These separate data sets must then be normalized through the tedious and lengthy process of resolving naming differences and collecting information into a single view. Attempts to consolidate such diverse data using data warehouses or federated queries add significant complexity and have shown limitations in flexibility. The alternative of complete semantic integration of data requires a massive, sustained effort in mapping data types and maintaining ontologies. We focused instead on creating a data architecture that leverages semantic mapping of experimental metadata, to support the rapid prototyping of scientific discovery applications with the twin goals of reducing architectural complexity while still leveraging semantic technologies to provide flexibility, efficiency and more fully characterized data relationships. A metadata ontology was developed to describe our discovery process. A metadata repository was then created by mapping metadata from existing data sources into this ontology, generating RDF triples to describe the entities. Finally an interface to the repository was designed which provided not only search and browse capabilities but complex query templates that aggregate data from both RDF and RDBMS sources. We describe how this approach (i) allows scientists to discover and link relevant data across diverse data sources and (ii) provides a platform for development of integrative informatics applications.

Many researchers have observed that TCP's congestion control mechanisms can lead to bursty traffic flows on modern high-speed networks, with a negative impact on overall network efficiency. A proposed solution to this problem is to evenly space, or "pace", data sent into the network over an entire round-trip time, so that data is not sent in a burst. In this paper, we quantitatively evaluate this approach. Pacing offers better fairness, throughput, and lower drop rates in some situations. However, we show that contrary to intuition, pacing often has significantly worse throughput than regular TCP because it is susceptible to synchronized losses and it delays congestion signals. We propose and evaluate approaches for eliminating this effect.

This paper proposes a protocol suite for dynamic replication and migration of Internet objects. It consists of an algorithm for deciding on the number and location of object replicas and an algorithm for distributing requests among currently available replicas. Our approach attempts to place replicas in the vicinity of a majority of requests while ensuring at the same time that no servers are overloaded. The request distribution algorithm uses the same simple mechanism to take into account both server proximity and load, without actually knowing the latter. The replica placement algorithm executes autonomously on each node, without the knowledge of other object replicas in the system. The proposed algorithms rely on the information available in databases maintained by Internet routers. A simulation study using synthetic workloads and the network backbone of UUNET, one of the largest Internet service providers, shows that the proposed protocol is effective in eliminating hot spots and ...

A new object tracking algorithm based on affine structure has been developed and it is shown that its performance is better than that of a Kalman filter based correlation tracker. The algorithm is fast, reliable, viewpoint invariant, and insensitive to occlusion and/or individual corner disappearance or reappearance. Detailed experimental analysis on a long real image sequence is also presented.