In this paper, we present cyberinfrastructure and grid computing efforts in New York State. In particular, we focus on fundamental efforts in Binghamton and Buffalo, including the design, development, and deployment of the New York State Grid, as well as a grass-roots New York State Initiative.

We have designed and deployed the New York State Grid (NYS Grid), which consists of an integrated computational and data grid. NYS Grid is used in a ubiquitous fashion, where the users have virtual access to their data sets and applications, allowing the user to perform tasks without knowledge of the physical hosts for data storage or compute systems. A wide variety of applications have been ported to NYS Grid, including critical programs in a variety of fields that are ideally suited to a multiprocessor computing environment with distributed datasets. Two applications from structural biology are presented as exemplars, including our Grid portal version of the SnB program, which has been run simultaneously on all computational resources on NYS Grid, as well as on the majority of the tens of thousands of processors available through the Open Science Grid. This paper also discusses previous grids that we developed, including the Buffalo-based (ACDC) experimental grid and the Western New York Grid, as well as a wide variety of advances that we have made in terms of grid monitoring, predictive scheduling, grid portal design, and grid-enabling application templates, to name a few.

The MEDEA+ SWANS (Silicon Platform for Wireless Advanced Networks of Sensors) project aims at defining a generic silicon platform, integrating analogue and digital Intellectual Property (IP) blocks for wireless sensor nodes technology. This generic platform will be used in various applications, such as transportation (aeronautics, automotive), homeland security, environmental and health/fitness. In the aeronautical application, the platform monitors, continuously, aircraft structures to detect whether a crack exists or not and process the data in real time, inside the platform. Measurements are provided by an inductive sensor glued on a structure and are acquired during flights. The sensor impedance (real and imaginary parts) varies depending on the state of the part area on which it is stuck. For example, this sensor aims at monitoring the further evolution of the crack too. The data are transmitted from the sensor to an ARM microcontroller through an electronic conditioner. Then, they are analysed and stored in a non volatile memory. Data measurements are collected by a RF transmission, every 2 or 4 months. A 3D stack platform demonstrator that allows the use of different technologies, will be realised, fully tested and characterised.

Grid computing integrates heterogeneous, geographically distributed, Internet-ready resources that are administered under multiple domains. A key challenge in grid computing is to provide a high quality of service to users in a transparent fashion, hiding issues that include ownership, administration, and geographic location of a wide variety of resources that provide compute cycles, data storage, rendering cycles, imaging devices, and sensors, to name a few. Ensuring the functionality of a wide variety of resources under multiple administrative policies requires tools for discovering, repairing, and publishing information on the services offered by individual sites within a given grid. In this paper, we present the ACDC Operations Dashboard, an interactive, collaborative environment for collecting, addressing, and publishing operational service information for resources across a computational grid.