MultiGreen: Cost-Minimizing Multi-source Datacenter Power Supply with Online Control

Session 4: Data Center Energy ManagementFulltext of the conference paper in: http://conferences.sigcomm.org/eenergy/2013/papers/p13.pdfFaced by soaring power cost, large footprint of carbon emis- sion and unpredictable power outage, more and more mod- ern Cloud Service Providers (CSPs) begin to mitigate these challenges by equipping their Datacenter Power Supply Sys- tem (DPSS) with multiple sources: (1) smart grid with time- varying electricity prices, (2) uninterrupted power supply (UPS) of finite capacity, and (3) intermittent green or re- newable energy. It remains a significant challenge how to operate among multiple power supply sources in a comple- mentary manner, to deliver reliable energy to datacenter users over time, while minimizing a CSP’s operational cost over the long run. This paper proposes an efficient, online control algorithm for DPSS, called MultiGreen. MultiGreen is based on an innovative two-timescale Lyapunov optimiza- tion technique. Without requiring a priori knowledge of system statistics, MultiGreen allows CSPs to make online decisions on purchasing grid energy at two time scales (in the long-term market and in the real-time market), leveraging renewable energy, and opportunistically charging and dis- charging UPS, in order to fully leverage the available green energy and low electricity prices at times for minimum op- erational cost. Our detailed analysis and trace-driven sim- ulations based on one-month real-world data have demon- strated the optimality (in terms of the tradeoff between min- imization of DPSS operational cost and satisfaction of data- center availability) and stability (performance guarantee in cases of fluctuating energy demand and supply) of Multi- Green

Loanword adaptation as first-language phonological perception

We show that loanword adaptation can be understood entirely in terms of phonological and phonetic comprehension and production mechanisms in the first language. We provide explicit accounts of several loanword adaptation phenomena (in Korean) in terms of an Optimality-Theoretic grammar model with the same three levels of representation that are needed to describe L1 phonology: the underlying form, the phonological surface form, and the auditory-phonetic form. The model is bidirectional, i.e., the same constraints and rankings are used by the listener and by the speaker. These constraints and rankings are the same for L1 processing and loanword adaptation

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Monitoring and Modeling Farmland Productivity Along the Venice Coastland, Italy

AbstractThe southern portion of the Venice coastland is a very precarious environment and salt contamination of land and groundwater is a severe problem that is seriously impacting the farmland productivity. Geophysical surveys, lab testing and continuous monitoring of hydrological parameters together with crop yield distribution were performed and acquired from 2010 to 2012 in a 21ha basin cultivated with maize crop and representative of the area. The dataset is here used to set-up a numerical model of soil moisture dynamics coupled with plant transpiration, photosynthesis and growth. The hydraulic model is linked to the atmosphere by the calculation of the stomatal conductance which is optimized for maximum carbon gain. The model is applied to the field site to understand the impact of land elevation, soil heterogeneities, and seawater contamination on land productivity

Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age

Simultaneous Localization and Mapping (SLAM)consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications, and witnessing a steady transition of this technology to industry. We survey the current state of SLAM. We start by presenting what is now the de-facto standard formulation for SLAM. We then review related work, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers. This paper simultaneously serves as a position paper and tutorial to those who are users of SLAM. By looking at the published research with a critical eye, we delineate open challenges and new research issues, that still deserve careful scientific investigation. The paper also contains the authors' take on two questions that often animate discussions during robotics conferences: Do robots need SLAM? and Is SLAM solved