Mobile Computing in Physics Analysis - An Indicator for eScience

This paper presents the design and implementation of a Grid-enabled physics analysis environment for handheld and other resource-limited computing devices as one example of the use of mobile devices in eScience. Handheld devices offer great potential because they provide ubiquitous access to data and round-the-clock connectivity over wireless links. Our solution aims to provide users of handheld devices the capability to launch heavy computational tasks on computational and data Grids, monitor the jobs status during execution, and retrieve results after job completion. Users carry their jobs on their handheld devices in the form of executables (and associated libraries). Users can transparently view the status of their jobs and get back their outputs without having to know where they are being executed. In this way, our system is able to act as a high-throughput computing environment where devices ranging from powerful desktop machines to small handhelds can employ the power of the Grid. The results shown in this paper are readily applicable to the wider eScience community.Comment: 8 pages, 7 figures. Presented at the 3rd Int Conf on Mobile Computing & Ubiquitous Networking (ICMU06. London October 200

Investigating the Role of Handheld Devices in the Accomplishment of Grid-Enabled Analysis Environment

We investigate the role of handheld devices as a potential platform to be used in the Grid Enabled Analysis Environment (GAE) by porting desktop PC-based analysis software to run on Pocket PC’s and other handhelds. This will enable them to be used for the analysis of data from the Compact Muon Solenoid (CMS), which goes online in 2006 at the European Organization for Nuclear Research (CERN). The environment currently comprises client software that runs on the Pocket PC providing interactive analysis features on the device and a remote data server named Clarens, which functions as a portal to the Grid, and ensures secure and authenticated access to the CMS data