This article proposes a runtime model that relates server energy consumption to its overall thermal envelope, using hardware performance counters and experimental measurements. While previous studies have attempted system-wide modeling of server power consumption through subsystem models, our approach is different in that it links system energy input to subsystem energy consumption based on a small set of tightly correlated parameters. The proposed model takes into account processor power, bus activities, and system ambient temperature for real-time prediction on the power consumption of long running jobs. Using the HyperTransport and QuickPath Link structures as case studies and through electrical measurements on example server subsystems, we develop a chaotic time-series approximation for runtime power consumption, arriving at the Chaotic Attractor Predictor (CAP). With polynomial time complexity, CAP exhibits high prediction accuracy, having the prediction errors within 1.6% (or 3.3%) for servers based on the HyperTransport bus (or the QuickPath Links), as verified by a set of common processor benchmarks. Our CAP is a superior predictive mechanism over existing linear auto-regressive methods, which require expensive and complex corrective steps to address the nonlinear and chaotic aspects of the underlying physical system.

The discovery and management of energy resources, especially at locations in the Gulf of Mexico, requires an economic but technically enhanced infrastructure. Research teams from Louisiana State University, University of Louisiana at Lafayette, and Southern University Baton Rouge are engaged in a collaborative effort to create a ubiquitous computing and monitoring system (UCoMS) for the discovery and management of energy resources. The UCoMS team has sucessfully addressed two difficult issues in this research: (1) the computational challenges faced by compute-intensive simulations for reservoir uncertainty analysis that requires thousands of simulations and deals with terabytes, and even petabytes, of data, (2) the development of a prototype wireless sensor network (WSN) infrastructure to collect and process realtime data from production locations. While the former requires the intensive computational power of the UCoMS grid resources, the latter requires efficient interfacing between WSN & grid. A unified workflow analysis has been performed to ensure smooth operation of both efforts and a unified portal has been created. This paper integrates the above two workflows and portals into a single platform. It illustrates the need for such integration for users with similar (but not same) goals and describes how to partition users among different groups with different access rights to ensure security within subgroups. Such a system can easily integrate future UCoMS sub-projects into a unified whole. Hence, our portal prototype serves as a good example of the benefit that may accrue from integrated workflows.