Five New and Narrowly Distributed Species of Paepalanthus Section Diphyomene (Eriocaulaceae) from Central Brazil

Five new species of Paepalanthus section Diphyomene are described and illustrated: P. brevis, P. flexuosus, P. longiciliatus, P. macer, and P. stellatus. Paepalanthus brevis, similar to P. decussus, is easily distinguished by its short reproductive axis, and pilose and mucronate leaves. Paepalanthus flexuosus, morphologically related to P. urbanianus, possesses a distinctive short and tortuous reproductive axis. Paepalanthus longiciliatus, morphologically similar to P. weddellianus, possesses long trichomes on the margins of the reproductive axis bracts, considered a diagnostic feature. Paepalanthus macer shares similarities with P. amoenus, differing by its sulfurous capitula and adpressed reproductive axis bracts. Paepalanthus stellatus also has affinity with P. decussus, but possesses unique, membranaceous, reproductive-axis bracts and a punctual inner-capitulum arrangement of pistillate flowers. Four of the described species are narrowly distributed in the state of Goias, whereas P. brevis is endemic to Distrito Federal. All are considered critically endangered. Detailed comparisons of these species are presented in tables. Comments on phenology, distribution, habitat and etymology, along with an identification key, are provided.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

EFFECTIVE NETWORKS FOR REAL-TIME DISTRIBUTED PROCESSING

This paper applies the concepts and methods of complex networks to the development of models and simulations of master-slave distributed real-time systems by introducing an upper bound in the allowable delivery time of the packets with computation results. Two representative interconnection models are taken into account: Uniformly random and scale free (Barabasi-Albert), including the presence of background traffic of packets. The obtained results include the identification of the uniformly random interconnectivity scheme as being largely more efficient than the scale-free counterpart. Also, increased latency tolerance of the application provides no help under congestion.

Elementary Petri net inside RFID distributed database (PNRD)

Usually, a Petri net is applied as an RFID model tool. This paper, otherwise, presents another approach to the Petri net concerning RFID systems. This approach, called elementary Petri net inside an RFID distributed database, or PNRD, is the first step to improve RFID and control systems integration, based on a formal data structure to identify and update the product state in real-time process execution, allowing automatic discovery of unexpected events during tag data capture. There are two main features in this approach: to use RFID tags as the object process expected database and last product state identification; and to apply Petri net analysis to automatically update the last product state registry during reader data capture. RFID reader data capture can be viewed, in Petri nets, as a direct analysis of locality for a specific transition that holds in a specific workflow. Following this direction, RFID readers storage Petri net control vector list related to each tag id is expected to be perceived. This paper presents PNRD cornerstones and a PNRD implementation example in software called DEMIS Distributed Environment in Manufacturing Information Systems.