Computing offers many opportunities to enhance the Earth's environment, and Microsoft Research is examining the most promising strategies. From increasing the energy efficiency of computing in data centers to addressing the era of data-intensive science, Microsoft Research is exploring ways to protect our planet.
|A New Way to Get Climate Information
A team from Microsoft Research Cambridge has created a tool that turns climate data into useful information and makes it available to the world.
|From Excel to the Cloud
The team behind Excel DataScope doesn’t think of big data as a problem—especially when the data are stored in the cloud, are readily accessible, and are as easy to manipulate as an Excel spreadsheet.
|A New Way to Visualize Earth
Layerscape, created by Microsoft Research, builds on WorldWide Telescope to give earth scientists a powerful new way to explore and analyze our planet.
The Joulemeter project provides a modeling tool to measure the energy usage of virtual machines, servers, desktops, laptops, and even individual software applications running on a computer. The visibility provided by Joulemeter can be used to improve power-provisioning costs for data centers, virtualized power budgeting, desktop energy optimizations, and mobile battery management. The technology is especially helpful for IT leaders who analyze power-management settings, PC users who wish to get fine-grained visibility into their computing energy use, and enthusiast developers who want to leverage power measurement for optimizing software and hosted service design for power usage.
Energy-Aware VMs and Cloud Computing
Virtual machines (VMs) become key platform components for data centers and Microsoft products such as Win8, System Center, and Azure. But existing power-management schemes designed at the server level, such as power capping and CPU throttling, do not work with VMs. VMmeter can estimate per-VM power consumption from Hyper-V performance counters, with the assistance of WinServer2008 R2 machine-level power metering, thus enabling power management at VM granularity. For example, we can selectively throttle VMs with the least performance hit for power capping. This demo compares VMmeter-based with hardware-based power-management solutions. We run multiple VMs, one of them being a high-priority video playback on a server. When a user requests power capping with our solution, the video playback will maintain high performance, while with hardware-capping solutions, we see reduced performance. We also will show how VMmeter can be part of System Center management packs.
PreHeat: Controlling Home Heating with Occupancy Prediction
Home heating uses more energy than any other residential energy expenditure, making increasing the efficiency of home heating an important goal for saving money and protecting the environment. We have built a home-heating system, PreHeat, that automatically programs your thermostat based on when you are home. PreHeat’s goal is to reduce the amount of time a household’s thermostat needs to be on without compromising the comfort of household members.
Atlantic Rainforest Sensor Net Research
Brazilian rainforests are of immense importance to the world, helping regulate climate temperatures, create rainfall, and provide habitat for biodiversity. In November 2009, Microsoft Research, in collaboration with researchers from the Johns Hopkins University and the University of São Paulo, deployed a network of sensors to study the Serra do Mar rainforest on minute-by-minute basis. The team used hundreds of sensors to measure temperature, water vapor, and solar radiation across a hill slope—essentially taking the vital signs of the rainforest.
This type of micrometeorology—the study of atmosphere just above the ground on small temporal and spatial scales—is critical to understanding how different ecosystems affect the Earth's climate and vice versa. Similar sensor networks can be deployed across extended terrain, in the ground and in the air, opening new ways of examining our climate and how various ecosystems interact.
The Swiss Experiment
The main goal of the collaboration between Microsoft Research and the Swiss Experiment project is to explore and enable the use of recent developments in the Microsoft Research SenseWeb/SensorMap project to enhance the capabilities of the SwissEx infrastructure and to validate the appropriateness of the Microsoft Research tools in a major e-science context to respond to concrete requirements of environmental scientists in the type of large-scale, collaborative experimental approach taken by the SwissEx. Furthermore, we will explore selected novel technical challenges that emerge through the use of sensor middleware in the context of e-science, specifically in environmental research and engineering, in order to enhance the currently employed methods. The project will be driven by requirements and feedback from environmental scientists.
Carbon-Climate Feedback Modeling
Climate change is the greatest global challenge of the 21st century. Models that reliably forecast future climates associated with different policy scenarios are urgently needed.Currently one of the largest single sources of uncertainty in global climate models is the future of carbon stored in vegetation*. In recent years vegetation (mostly forests) has soaked up 25% of human CO2 emissions, but models disagree drastically about the future of this ‘carbon sink’: will vegetation soak up ever larger amounts of carbon, acting as an ever-stronger brake on climate change? Or will vegetation become a significant carbon source, accelerating climate change which in turn would demand much more radical policy action to reduce CO2 emissions now? These alternative scenarios have been predicted by conteporary DGVMs but unfortunately technical obstacles make it practically impossible to compare existing models and identify objectively what the most likely future scenario is.
Greening Corporate Networks with Sleep Proxy
In a corporate network, most desktop machines always are left on, even when they are not in use for extended periods, such as at night. This is wasteful, bad for the environment, and bad for the corporate treasury. While Win7 provides aggressive sleep functionality, most users override it because they occasionally might want to access their machine remotely. Ideally, a desktop would go to sleep when not in use and awaken seamlessly when the user tries to access it. We have built a system to enable this. Our system consists of a “sleep server” that maintains the network presence of the sleeping machine and seamlessly awakens it on remote access. We do not require special hardware or changes to existing software. Our system is operational in Building 99 and has resulted in substantial savings in terms of money, power consumption, and carbon-dioxide emissions.
Saving Desktop Energy: WakeOnLAN & Virtualization
Saving desktop energy has been an area of focus at Microsoft Research India over the past year. WARP and LiteGreen are complementary projects under this theme. WARP is a composition of platform components that facilitates remote power-state management of a PC using the Wake-on-LAN and other system-management mechanisms. This system is virtually stateless and provides user interfaces for system management. Features include remote peer-to-peer wakeups and remote sleep, hibernate, or shutdown of a desktop and asynchronous machine-state transitions based on events published from user interfaces such as the Web, e-mail, SMS, and location-based services. Automatic desktop upgrades, centralized system control, delegation of power management, and auditing are also components of this system. LiteGreen is a system for saving energy from idle PCs in enterprises by exploiting short idle periods as well as long ones. To avoid user disruption, LiteGreen virtualizes the desktop computing environment and migrates it between the physical PC and a virtual-machine server, depending on whether the desktop computing environment is being used. Based on usage analysis of 120 desktops at Microsoft Research India, LiteGreen was able to deliver energy savings of 72 to 74 percent. When a user steps away from a PC, the desktop is migrated to a server and the PC is put to sleep. When the user returns, he or she is able to start using the desktop immediately.
Trident is an open source workbench for scientific workflow that is implemented on top of Microsoft’s Windows Workflow Foundation, levering existing functionally of a commercial workflow engine. Trident provides a workflow environment in which scientists can visually design and execute scientific workflows by specifying the desired sequence of computational actions and the appropriate data flow, including required data transformations, between these steps. The scientific workflow approach offers a number of advantages over traditional scripting-based approaches, including ease of configuration, improved reusability and maintenance of workflows and components, automated provenance management, "smart" re-running of different versions of workflow instances, on-the-fly updateable parameters, monitoring of long running tasks, and support for fault-tolerance and recovery from failures. Trident has been developed in collaboration with researchers for several large-scale eScience projects, ranging from oceanography, and astronomy, to the atmospheric sciences.
Scaling from Trees to Forests
This project aims to understand how to accurately and usefully scale from the short-term biology of individual trees, to the longer-term dynamics of forest stands, and forested landscapes. Why do this? First, there are good reasons to believe that, in order to make useful predictions about several aspects of forest dynamics, it is necessary to represent the fact that forests are built of trees. For example, increased growth causes increased competition for light, which in turn increases mortality rates, which in turn decreases carbon storage. Second, we have lots of short-term measurements of individual trees which, if we only knew how to scale them up, might let us understand and predict the dynamics of forests over much of the globe.
Optimal Forest Management
How can we best manage the world's forest resources for wood yield, biodiversity, and/or carbon storage? Building on our work in forest modeling, this project uses computational approaches to objectively and automatically search for forest management 'programs' (e.g. tree harvesting schedules) that best achieve pre-stated goals.
Global Ecosystem Function
An expanding population, with expanding resource use per capita, is resulting in an alarming loss and degradation of ecosystems. In order to balance the need for increased food, timber and textiles production, with industrial use of natural resources, with the healthy functioning of natural, semi-natural and artificial ecosystems, we require predictive, global models of the response of ecosystems to various human activities. CEES is working with the United Nations Environment Programme World Conservation Monitoring Centre ( UNEP-WCMC ), to develop just such a model.