A Monitoring System for the BaBar INFN Computing Cluster

Monitoring large clusters is a challenging problem. It is necessary to observe a large quantity of devices with a reasonably short delay between consecutive observations. The set of monitored devices may include PCs, network switches, tape libraries and other equipments. The monitoring activity should not impact the performances of the system. In this paper we present PerfMC, a monitoring system for large clusters. PerfMC is driven by an XML configuration file, and uses the Simple Network Management Protocol (SNMP) for data collection. SNMP is a standard protocol implemented by many networked equipments, so the tool can be used to monitor a wide range of devices. System administrators can display informations on the status of each device by connecting to a WEB server embedded in PerfMC. The WEB server can produce graphs showing the value of different monitored quantities as a function of time; it can also produce arbitrary XML pages by applying XSL Transformations to an internal XML representation of the cluster's status. XSL Transformations may be used to produce HTML pages which can be displayed by ordinary WEB browsers. PerfMC aims at being relatively easy to configure and operate, and highly efficient. It is currently being used to monitor the Italian Reprocessing farm for the BaBar experiment, which is made of about 200 dual-CPU Linux machines.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 10 pages, LaTeX, 4 eps figures. PSN MOET00

Cosmological Simulations on a Grid of Computers

The work presented in this paper aims at restricting the input parameter values of the semi-analytical model used in GALICS and MOMAF, so as to derive which parameters influence the most the results, e.g., star formation, feedback and halo recycling efficiencies, etc. Our approach is to proceed empirically: we run lots of simulations and derive the correct ranges of values. The computation time needed is so large, that we need to run on a grid of computers. Hence, we model GALICS and MOMAF execution time and output files size, and run the simulation using a grid middleware: DIET. All the complexity of accessing resources, scheduling simulations and managing data is harnessed by DIET and hidden behind a web portal accessible to the users.Comment: Accepted and Published in AIP Conference Proceedings 1241, 2010, pages 816-82

Cyber security investigation for Raspberry Pi devices

Big Data on Cloud application is growing rapidly. When the cloud is attacked, the investigation relies on digital forensics evidence. This paper proposed the data collection via Raspberry Pi devices, in a healthcare situation. The significance of this work is that could be expanded into a digital device array that takes big data security issues into account. There are many potential impacts in health area. The field of Digital Forensics Science has been tagged as a reactive science by some who believe research and study in the field often arise as a result of the need to respond to event which brought about the needs for investigation; this work was carried as a proactive research that will add knowledge to the field of Digital Forensic Science. The Raspberry Pi is a cost-effective, pocket sized computer that has gained global recognition since its development in 2008; with the wide spread usage of the device for different computing purposes. Raspberry Pi can potentially be a cyber security device, which can relate with forensics investigation in the near future. This work has used a systematic approach to study the structure and operation of the device and has established security issues that the widespread usage of the device can pose, such as health or smart city. Furthermore, its evidential information applied in security will be useful in the event that the device becomes a subject of digital forensic investigation in the foreseeable future. In healthcare system, PII (personal identifiable information) is a very important issue. When Raspberry Pi plays a processor role, its security is vital; consequently, digital forensics investigation on the Raspberry Pies becomes necessary

The Scalable Brain Atlas: instant web-based access to public brain atlases and related content

The Scalable Brain Atlas (SBA) is a collection of web services that provide unified access to a large collection of brain atlas templates for different species. Its main component is an atlas viewer that displays brain atlas data as a stack of slices in which stereotaxic coordinates and brain regions can be selected. These are subsequently used to launch web queries to resources that require coordinates or region names as input. It supports plugins which run inside the viewer and respond when a new slice, coordinate or region is selected. It contains 20 atlas templates in six species, and plugins to compute coordinate transformations, display anatomical connectivity and fiducial points, and retrieve properties, descriptions, definitions and 3d reconstructions of brain regions. The ambition of SBA is to provide a unified representation of all publicly available brain atlases directly in the web browser, while remaining a responsive and light weight resource that specializes in atlas comparisons, searches, coordinate transformations and interactive displays.Comment: Rolf K\"otter sadly passed away on June 9th, 2010. He co-initiated this project and played a crucial role in the design and quality assurance of the Scalable Brain Atla

An overview of the planned CCAT software system

CCAT will be a 25m diameter sub-millimeter telescope capable of operating in the 0.2 to 2.1mm wavelength range. It will be located at an altitude of 5600m on Cerro Chajnantor in northern Chile near the ALMA site. The anticipated first generation instruments include large format (60,000 pixel) kinetic inductance detector (KID) cameras, a large format heterodyne array and a direct detection multi-object spectrometer. The paper describes the architecture of the CCAT software and the development strategy.Comment: 17 pages, 6 figures, to appear in Software and Cyberinfrastructure for Astronomy III, Chiozzi & Radziwill (eds), Proc. SPIE 9152, paper ID 9152-10