A flexible monitoring and notification system for distributed resources

Resource monitoring in distributed systems is required to understand the 'health' of the overall system and to help identify particular problems, such as dysfunctional hardware, a faulty, system or application software. Desirable characteristics for monitoring systems are the ability to connect to any number of different types of monitoring agents and to provide different views of the system, based on a client's particular preferences. This paper outlines and discusses the ongoing activities within the GridRM wide-area resource-monitoring project.

Monitoring and modelling the three-dimensional flow of water under drip irrigation

The interpretation of soil water dynamics under drip irrigation systems is relevant for crop production as well as on water use and management. In this study a three-dimensional representation of the flow of water under drip irrigation is presented. The work includes analysis of the water balance at point scale as well as area-average, exploring uncertainties in water balance estimations depending on the number of locations sampled. The water flow was monitored by detailed profile water content measurements before irrigation, after irrigation and 24 h later with a dense array of soil moisture access tubes radially distributed around selected drippers. The objective was to develop a methodology that could be used on selected occasions to obtain 'snap shots' of the detailed three-dimensional patterns of soil moisture. Such patterns are likely to be very complex, as spatial variability will be induced for a number of reasons, such as strong horizontal gradients in soil moisture, variations between individual sources in the amount of water applied and spatial variability is soil hydraulic properties. Results are compared with a widely used numerical model, Hydrus-2D. The observed dynamic of the water content distribution is in good agreement with model simulations, although some discrepancies concerning the horizontal distribution of the irrigation bulb are noted due to soil heterogeneity. (c) 2006 Elsevier B.V. All rights reserved.

Using a RESTful messaging and registry system to support a range a distributed applications

Tycho was conceived in 2003 in response to a need by the GridRM [1] resource-monitoring project for a ldquolight-weightrdquo, scalable and easy to use wide-area distributed registry and messaging system. Since Tycho's first release in 2006 a number of modifications have been made to the system to make it easier to use and more flexible. Since its inception, Tycho has been utilised across a number of application domains including widearea resource monitoring, distributed queries across archival databases, providing services for the nodes of a Cray supercomputer, and as a system for transferring multi-terabyte scientific datasets across the Internet. This paper provides an overview of the initial Tycho system, describes a number of applications that utilise Tycho, discusses a number of new utilities, and how the Tycho infrastructure has evolved in response to experience of building applications with it.

A web 2.0 user interface for wide-area resource monitoring

Resource monitoring in distributed systems is required to understand the 'health' of the overall system and to help identify particular problems, such as dysfunctional hardware or faulty system or application software. Monitoring systems such as GridRM provide the ability to connect to any number of different types of monitoring agents and provide different views of the system, based on a client's particular preferences. Web 2.0 technologies, and in particular 'mashups', are emerging as a promising technique for rapidly constructing rich user interfaces, that combine and present data in intuitive ways. This paper describes a Web 2.0 user interface that was created to expose resource data harvested by the GridRM resource monitoring system.

Distributed multimedia quality: the user perspective

Distributed multimedia supports a symbiotic infotainment duality, i.e. the ability to transfer information to the user, yet also provide the user with a level of satisfaction. As multimedia is ultimately produced for the education and / or enjoyment of viewers, the user’s-perspective concerning the presentation quality is surely of equal importance as objective Quality of Service (QoS) technical parameters, to defining distributed multimedia quality. In order to extensively measure the user-perspective of multimedia video quality, we introduce an extended model of distributed multimedia quality that segregates quality into three discrete levels: the network-level, the media-level and content-level, using two distinct quality perspectives: the user-perspective and the technical-perspective. Since experimental questionnaires do not provide continuous monitoring of user attention, eye tracking was used in our study in order to provide a better understanding of the role that the human element plays in the reception, analysis and synthesis of multimedia data. Results showed that video content adaptation, results in disparity in user video eye-paths when: i) no single / obvious point of focus exists; or ii) when the point of attention changes dramatically. Accordingly, appropriate technical- and user-perspective parameter adaptation is implemented, for all quality abstractions of our model, i.e. network-level (via simulated delay and jitter), media-level (via a technical- and user-perspective manipulated region-of-interest attentive display) and content-level (via display-type and video clip-type). Our work has shown that user perception of distributed multimedia quality cannot be achieved by means of purely technical-perspective QoS parameter adaptation.

Distributed classification for pocket data mining

Distributed and collaborative data stream mining in a mobile computing environment is referred to as Pocket Data Mining PDM. Large amounts of available data streams to which smart phones can subscribe to or sense, coupled with the increasing computational power of handheld devices motivates the development of PDM as a decision making system. This emerging area of study has shown to be feasible in an earlier study using technological enablers of mobile software agents and stream mining techniques [1]. A typical PDM process would start by having mobile agents roam the network to discover relevant data streams and resources. Then other (mobile) agents encapsulating stream mining techniques visit the relevant nodes in the network in order to build evolving data mining models. Finally, a third type of mobile agents roam the network consulting the mining agents for a final collaborative decision, when required by one or more users. In this paper, we propose the use of distributed Hoeffding trees and Naive Bayes classifers in the PDM framework over vertically partitioned data streams. Mobile policing, health monitoring and stock market analysis are among the possible applications of PDM. An extensive experimental study is reported showing the effectiveness of the collaborative data mining with the two classifers.

Ubiquitous grid resource monitoring

In any wide-area distributed system there is a need to communicate and interact with a range of networked devices and services ranging from computer-based ones (CPU, memory and disk), to network components (hubs, routers, gateways) and specialised data sources (embedded devices, sensors, data-feeds). In order for the ensemble of underlying technologies to provide an environment suitable for virtual organisations to flourish, the resources that comprise the fabric of the Grid must be monitored in a seamless manner that abstracts away from the underlying complexity. Furthermore, as various competing Grid middleware offerings are released and evolve, an independent overarching monitoring service should act as a corner stone that ties these systems together. GridRM is a standards-based approach that is independent of any given middleware and that can utilise legacy and emerging resource-monitoring technologies. The main objective of the project is to produce a standardised and extensible architecture that provides seamless mechanisms to interact with native monitoring agents across heterogeneous resources.

GridRM: a resource monitoring architecture for the grid

Monitoring resources is an important aspect of the overall efficient usage and control of any distributed system. In this paper, we describe a generic open-source resource monitoring architecture that has been specifically designed for the Grid. The paper consists of three main sections. In the first section, we outline our motivation and briefly detail similar work in the area. In the second section, we describe the general monitoring architecture and its components. In the final section of the paper, we summarise the experiences so far and outline our future work.

Using Distributed Temperature Sensing to monitor field scale dynamics of ground surface temperature and related substrate heat flux

We present one of the first studies of the use of Distributed Temperature Sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer and in the soil. Our field site was at a groundwater-fed wet meadow in the Netherlands covered by a canopy layer (between 0-0.5 m thickness) consisting of grass and sedges. At this site, we ran a single cable across the surface in parallel 40 m sections spaced by 2 m, to create a 40×40 m monitoring field for GST. We also buried a short length (≈10 m) of cable to depth of 0.1±0.02 m to measure soil temperature. We monitored the temperature along the entire cable continuously over a two-day period and captured the diurnal course of GST, and how it was affected by rainfall and canopy structure. The diurnal GST range, as observed by the DTS system, varied between 20.94 and 35.08◦C; precipitation events acted to suppress the range of GST. The spatial distribution of GST correlated with canopy vegetation height during both day and night. Using estimates of thermal inertia, combined with a harmonic analysis of GST and soil temperature, substrate and soil-heat fluxes were determined. Our observations demonstrate how the use of DTS shows great promise in better characterising area-average substrate/soil heat flux, their spatiotemporal variability, and how this variability is affected by canopy structure. The DTS system is able to provide a much richer data set than could be obtained from point temperature sensors. Furthermore, substrate heat fluxes derived from GST measurements may be able to provide improved closure of the land surface energy balance in micrometeorological field studies. This will enhance our understanding of how hydrometeorological processes interact with near-surface heat fluxes.