Simulating Distributed Systems

The simulation framework developed within the "Models of Networked Analysis at Regional Centers" (MONARC) project as a design and optimization tool for large scale distributed systems is presented. The goals are to provide a realistic simulation of distributed computing systems, customized for specific physics data processing tasks and to offer a flexible and dynamic environment to evaluate the performance of a range of possible distributed computing architectures. A detailed simulation of a large system, the CMS High Level Trigger (HLT) production farm, is also presented

MonALISA : A Distributed Monitoring Service Architecture

The MonALISA (Monitoring Agents in A Large Integrated Services Architecture) system provides a distributed monitoring service. MonALISA is based on a scalable Dynamic Distributed Services Architecture which is designed to meet the needs of physics collaborations for monitoring global Grid systems, and is implemented using JINI/JAVA and WSDL/SOAP technologies. The scalability of the system derives from the use of multithreaded Station Servers to host a variety of loosely coupled self-describing dynamic services, the ability of each service to register itself and then to be discovered and used by any other services, or clients that require such information, and the ability of all services and clients subscribing to a set of events (state changes) in the system to be notified automatically. The framework integrates several existing monitoring tools and procedures to collect parameters describing computational nodes, applications and network performance. It has built-in SNMP support and network-performance monitoring algorithms that enable it to monitor end-to-end network performance as well as the performance and state of site facilities in a Grid. MonALISA is currently running around the clock on the US CMS test Grid as well as an increasing number of other sites. It is also being used to monitor the performance and optimize the interconnections among the reflectors in the VRVS system.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 8 pages, pdf. PSN MOET00

Sulfate and MSA in the air and snow on the Greenland Ice Sheet

Sulfate and methanesulfonic acid (MSA) concentrations in aerosol, surface snow, and snowpit samples have been measured at two sites on the Greenland Ice Sheet. Seasonal variations of the concentrations observed for these chemical species in the atmosphere are reproduced in the surface snow and preserved in the snowpit sequence. The amplitude of the variations over a year are smaller in the snow than in the air, but the ratios of the concentrations are comparable. The seasonal variations for sulfate are different at the altitude of the Ice Sheet compared to those observed at sea level, with low concentrations in winter and short episodes of elevated concentrations in spring. In contrast, the variations in concentrations of MSA are similar to those measured at sea level, with a first sequence of elevated concentrations in spring and another one during summer, and a winter low resulting from low biogenic production. The ratio MSA/sulfate clearly indicates the influence of high-latitude sources for the summer maximum of MSA, but the large impact of anthropogenic sulfate precludes any conclusion for the spring maximum. The seasonal pattern observed for these species in a snowpit sampled according to stratigraphy indicates a deficit in the accumulation of winter snow at the summit of the Greenland Ice Sheet, in agreement with some direct observations. A deeper snowpit covering the years 1985–1992 indicates the consistency of the seasonal pattern for MSA over the years, which may be linked to transport and deposition processes

Statistics of eigenfunctions in open chaotic systems: a perturbative approach

We investigate the statistical properties of the complexness parameter which characterizes uniquely complexness (biorthogonality) of resonance eigenstates of open chaotic systems. Specifying to the regime of isolated resonances, we apply the random matrix theory to the effective Hamiltonian formalism and derive analytically the probability distribution of the complexness parameter for two statistical ensembles describing the systems invariant under time reversal. For those with rigid spectra, we consider a Hamiltonian characterized by a picket-fence spectrum without spectral fluctuations. Then, in the more realistic case of a Hamiltonian described by the Gaussian Orthogonal Ensemble, we reveal and discuss the r\^ole of spectral fluctuations

Quasimodes of a chaotic elastic cavity with increasing local losses

We report non-invasive measurements of the complex field of elastic quasimodes of a silicon wafer with chaotic shape. The amplitude and phase spatial distribution of the flexural modes are directly obtained by Fourier transform of time measurements. We investigate the crossover from real mode to complex-valued quasimode, when absorption is progressively increased on one edge of the wafer. The complexness parameter, which characterizes the degree to which a resonance state is complex-valued, is measured for non-overlapping resonances and is found to be proportional to the non-homogeneous contribution to the line broadening of the resonance. A simple two-level model based on the effective Hamiltonian formalism supports our experimental results