16728359
TRAC: toward recency and consistency reporting in a database with distributed data sources
Distributed computing environments, including workflows in computational grids, present challenges for monitoring, as the state of the system may be captured only in logs distributed throughout the system. One approach to monitoring such systems is to "sniff" these distributed logs and to store their transformed content in a DBMS. This centralizes the state and exposes it for querying; unfortunately, it also creates uncertainty with respect to the recency and consistency of the data. Previous related work has focused on allowing queries to express currency and consistency constraints, which are then enforced by "pulling" data from the distributed sources on demand, or by requiring synchronous updates of a centralized data store. In some instances this is impossible due to legacy system issues or inefficient as the system scales to large numbers of processors. Accordingly, we propose that instead of enforcing consistency and recency, such monitoring systems should report these properties along with query results, with the hope that this will allow the data to be appropriately interpreted. We present techniques for reporting consistency and recency for queries and evaluate them with respect to efficiency and precision. Finally, we describe our prototype implementation and present experimental results of our techniques.
8770859
K-relevance: a spectrum of relevance for data sources impacting a query
Applications ranging from grid management to sensor nets to web-based information integration and extraction can be viewed as receiving data from some number of autonomous remote data sources and then answering queries over this collected data. In such environments it is helpful to inform users which data sources are "relevant" to their query results. It is not immediately obvious what "relevant" should mean in this context, as different users will have different requirements. In this paper, rather than proposing a single definition of relevance, we propose a spectrum of definitions, which we term "k-relevance", for k ≥ 0. We give algorithms for identifying k-relevant data sources for relational queries and explore their efficiency both analytically and experimentally. Finally, we explore the impact of integrity constraints (including dependencies) and materialized views on the problem of computing and maintaining relevant data sources.
10414560
Distributed Interactive Learning in Multi-Agent Systems
Both explanation-based and inductive learning techniques have proven successful in a variety of distributed domains. However, learning in multi-agent systems does not necessarily involve the participation of other agents directly in the inductive process itself. Instead, many systems frequently employ multiple instances of induction separately, or single-agent learning. In this paper we present a new framework, named the Multi-Agent Inductive Learning System (MAILS), that tightly integrates processes of induction between agents. The MAILS framework combines inverse entailment with an epistemic approach to reasoning about knowledge in a multi-agent setting, facilitating a systematic approach to the sharing of knowledge and invention of predicates when required. The benefits of the new approach are demonstrated for inducing declarative program fragments in a multi-agent distributed programming system.
806919
Using Learning to Facilitate the Evolution of Features for Recognizing Visual Concepts
This paper describes a hybrid methodology that integrates genetic algorithms (GAs) and decision tree learning in order to evolve useful subsets of discriminatory features for recognizing complex visual concepts. A GA is used to search the space of all possible subsets of a large set of candidate discrimination features. Candidate feature subsets are evaluated by using C4.5, a decision tree learning algorithm, to produce a decision tree based on the given features using a limited amount of training data. The classification performance of the resulting decision tree on unseen testing data is used as the fitness of the underlying feature subset. Experimental results are presented to show how increasing the amount of learning significantly improves feature set evolution for difficult visual recognition problems involving satellite and facial image data. In addition, we also report on the extent to which other more subtle aspects of the Baldwin effect are exhibited by the system.
392551
Finding Target Language Correspondence for Lexicalized EBMT System
This paper presents a three-phase approach to find the correspondence in Target Language (TL) sentence for a fragment of Source Language (SL) sentence in a lexicalized EBMT system. To be practical, it exploits surface information as much as possible instead of using parsers. Experiments show that, although not so perfect, it is very robust and effective. The three phases are: First, align the sentence pair at word level in order to provide anchors for phrase alignment. Second, based on the aligned anchors, find all the TL fragments which may possibly correspond to a SL fragment. And finally, using a score function, select the best TL fragment as the correspondence of a SL fragment.
6334357
An energy-conserved on-demand data broadcasting system
We propose in this paper an energy-conserved on-demand data broadcasting system by employing the data indexing technique. We also propose algorithm AIDOA to adjust the degree of buckets according to system workload. Experimental results show that algorithm AIDOA is able to greatly reduce power consumption at the cost of slight increment in average access time and adjust the index and data organization dynamically to adapt to change of system workload.
10979198
Weakly Hamiltonian-connected ordinary multipartite tournaments
Abstract We characterize weakly Hamiltonian-connected ordinary multipartite tournaments. Our result generalizes such a characterization for tournaments by Thomassen and implies a polynomial algorithm to decide the existence of a Hamiltonian path connecting two given vertices in an ordinary multipartite tournament and finds one, if it exists.