Intelligent agents for fault tolerance: from multi-agent simulation to cluster-based implementation

Recent research in multi-agent systems incorporate fault tolerance concepts, but does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely 'Intelligent Agents'. A task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator, and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Transport in the low-latitude tropopause zone diagnosed using particle trajectories

Recent literature has described a “transition zone” between the average top of deep convection in the Tropics and the stratosphere. Here transport across this zone is investigated using an offline trajectory model. Particles were advected by the resolved winds from the European Centre for Medium-Range Weather Forecasts reanalyses. For each boreal winter clusters of particles were released in the upper troposphere over the four main regions of tropical deep convection (Indonesia, central Pacific, South America, and Africa). Most particles remain in the troposphere, descending on average for every cluster. The horizontal components of 5-day trajectories are strongly influenced by the El Niño–Southern Oscillation (ENSO), but the Lagrangian average descent does not have a clear ENSO signature. Tropopause crossing locations are first identified by recording events when trajectories from the same release regions cross the World Meteorological Organization lapse rate tropopause. Most crossing events occur 5–15 days after release, and 30-day trajectories are sufficiently long to estimate crossing number densities. In a further two experiments slight excursions across the lapse rate tropopause are differentiated from the drift deeper into the stratosphere by defining the “tropopause zone” as a layer bounded by the average potential temperature of the lapse rate tropopause and the profile temperature minimum. Transport upward across this zone is studied using forward trajectories released from the lower bound and back trajectories arriving at the upper bound. Histograms of particle potential temperature (θ) show marked differences between the transition zone, where there is a slow spread in θ values about a peak that shifts slowly upward, and the troposphere below 350 K. There forward trajectories experience slow radiative cooling interspersed with bursts of convective heating resulting in a well-mixed distribution. In contrast θ histograms for back trajectories arriving in the stratosphere have two distinct peaks just above 300 and 350 K, indicating the sharp change from rapid convective heating in the well-mixed troposphere to slow ascent in the transition zone. Although trajectories slowly cross the tropopause zone throughout the Tropics, all three experiments show that most trajectories reaching the stratosphere from the lower troposphere within 30 days do so over the west Pacific warm pool. This preferred location moves about 30°–50° farther east in an El Niño year (1982/83) and about 30° farther west in a La Niña year (1988/89). These results could have important implications for upper-troposphere–lower-stratosphere pollution and chemistry studies.

Adaptive alarm processor for fault diagnosis on power transmission networks

The authors describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive online diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.

Real-time expert system for fault location on high voltage underground distribution cables

To ensure minimum loss of system security and revenue it is essential that faults on underground cable systems be located and repaired rapidly. Currently in the UK, the impulse current method is used to prelocate faults, prior to using acoustic methods to pinpoint the fault location. The impulse current method is heavily dependent on the engineer's knowledge and experience in recognising/interpreting the transient waveforms produced by the fault. The development of a prototype real-time expert system aid for the prelocation of cable faults is described. Results from the prototype demonstrate the feasibility and benefits of the expert system as an aid for the diagnosis and location of faults on underground cable systems.

Application of logistic regression for fault analysis in an industrial printing process

A statistical technique for fault analysis in industrial printing is reported. The method specifically deals with binary data, for which the results of the production process fall into two categories, rejected or accepted. The method is referred to as logistic regression, and is capable of predicting future fault occurrences by the analysis of current measurements from machine parts sensors. Individual analysis of each type of fault can determine which parts of the plant have a significant influence on the occurrence of such faults; it is also possible to infer which measurable process parameters have no significant influence on the generation of these faults. Information derived from the analysis can be helpful in the operator's interpretation of the current state of the plant. Appropriate actions may then be taken to prevent potential faults from occurring. The algorithm is being implemented as part of an applied self-learning expert system.

Power transmission network simulation for fault diagnosis

The authors discuss an implementation of an object oriented (OO) fault simulator and its use within an adaptive fault diagnostic system. The simulator models the flow of faults around a power network, reporting switchgear indications and protection messages that would be expected in a real fault scenario. The simulator has been used to train an adaptive fault diagnostic system; results and implications are discussed.

Ultra-distal tephra deposits from super-eruptions: examples from Toba, Indonesia and Taupo Volcanic Zone, New Zealand

Voluminous rhyolitic eruptions from Toba, Indonesia, and Taupo Volcanic Zone (TVZ), New Zealand, have dispersed volcanic ash over vast areas in the late Quaternary. The ~74 ka Youngest Toba Tuff (YTT) eruption deposited ash over the Bay of Bengal and the Indian subcontinent to the west. The ~340 ka Whakamaru eruption (TVZ) deposited the widespread Rangitawa Tephra, dominantly to the southeast (in addition to occurrences northwest of vent), extending across the landmass of New Zealand, and the South Pacific Ocean and Tasman Sea, with distal terrestrial exposures on the Chatham Islands. These super-eruptions involved ~2500 km^3 and ~1500 km3 of magma (dense-rock equivalent; DRE), respectively. Ultra-distal terrestrial exposures of YTT at two localities in India, Middle Son Valley, Madhya Pradesh, and Jurreru River Valley, Andhra Pradesh, at distances of >2000 km from the source caldera, show a basal ‘primary’ ashfall unit ~4 cm thick, although deposits containing reworked ash are up to ~3 m in total thickness. Exposures of Rangitawa Tephra on the Chatham Islands, >900 km from the source caldera, are ~15-30 cm thick. At more proximal localities (~200 km from source), Rangitawa Tephra is ~55-70 cm thick and characterized by a crystal-rich basal layer and normal grading. Both distal tephra deposits are characterized by very-fine ash (with high PM10 fractions) and are crystal-poor. Glass chemistry, stratigraphy and grain-size data for these distal tephra deposits are presented with comparisons of their correlation, dispersal and preservation. Using field observations, ash transport and deposition were modeled for both eruptions using a semi-analytical model (HAZMAP), with assumptions concerning average wind direction and strength during eruption, column shape and vent size. Model outputs provide new insights into eruption dynamics and better estimates of eruption volumes associ- ated with tephra fallout. Modeling based on observed YTT distal tephra thicknesses indicate a relatively low (<40 km high), very turbulent eruption column, consistent with deposition from a co-ignimbrite cloud extending over a broad region. Similarly, the Whakamaru eruption was modeled as producing a predominantly Plinian column (~45 km high), with dispersal to the southeast by strong prevailing winds. Significant ash fallout of the main dispersal direction, to the northwest of source, cannot be replicated in this modeling. The widespread dispersal of large volumes of fine ash from both eruptions may have had global environmental consequences, acutely affecting areas up to thousands of kilometers from vent.