Abstract

Abstract

Abstract

Abstract
Association rule engines typically output a very large set of rules. Despite the fact that association rules are regarded as highly comprehensible and useful for data mining and decision support in fields such as marketing, retail, demographics, among others, lengthy outputs may discourage users from using the technique. In this paper we propose a post-processing methodology and tool for browsing/visualizing large sets of association rules. The method is based on a set of operators that transform sets of rules into sets of rules, allowing focusing on interesting regions of the rule space. Each set of rules can be then seen with different graphical representations. The tool is web-based and uses SVG. Association rules are given in PMML.

Abstract
Fault-tolerant control systems can be built by replicating critical components. However, replication raises the issue of inconsistency. Multiple protocols for ensuring consistency have been described in the literature. PADRE (Protocol for Asymmetric Duplex Redundancy) is such a protocol, and an interesting case study of a complex and sensitive problem: the management of replicated traffic controllers in a railway system [5]. However, the low level at which the protocol lots been developed embodies system details, namely timeliness assumptions, that make it difficult to understand and may narrow its applicability. We argue that, when designing a protocol, it is preferable to consider first a general solution that does not include any timeliness assumptions; then, by taking into account additional hypothesis, one can easily design a time-based solution tailored to a specific environment. This paper illustrates the benefit of a top-down protocol design approach, and shows that PADRE can be seen as an instance of a standard Primary-backup replication protocol based on View Synchronous Communication (VSC).

Abstract
Traditional reliable broadcast protocols fail to scale to large settings. The paper proposes a reliable multicast protocol that integrates two approaches to deal with the large-scale dimension in group communication protocols: gossip-based probabilistic broadcast and semantic reliability. The aim of the resulting protocol is to improve the resiliency of the probabilistic protocol to network congestion by allocating scarce resources to semantically relevant messages. Although intuitively it seems that a straightforward combination of probabilistic and semantic reliable protocols is possible, we show that it offers disappointing results. Instead, we propose an architecture based on a specialized probabilistic semantically reliable layer and show that it produces the desired results. The combined primitive is thus scalable to large number of participants, highly resilient to network and process failures, and delivers a high quality data flow even when the load exceeds the available bandwidth. We present a summary of simulation results that compare different protocol configurations. © 2001 IEEE.