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I think a key opportunity for sustainable computing is to do the hard engineering to make it easy to be green, ideally, easier than less green alternatives. As an analogy, driving a hybrid car is typically considered greener than driving a comparable gasoline-only car. But a really interesting thing is that, in my experience, driving a hybrid car is actually easier than driving a gasoline-only car, given the significantly fewer trips to the gas station. So, in this case, it's actually easier being greener, but it took significant innovation in automotive engineering to make this so. Working in the area of datacenter resource management at VMware, I see technology examples where it is easy to be green and examples where there is opportunity for improvement.
The transformation of many mainstream enterprise datacenters from running workloads directly on lightly-utilized dedicated hosts to consolidating those workloads in virtual machines (VMs) running on more highly-utilized servers was greener, and many power companies gave rebates to reward the savings. But a really interesting thing is that the transformation made datacenter management easier. Deploying
new server workloads was quicker and easier in VMs than on physical servers. Live migration allowed maintenance of servers and datastores to be handled without downtime and enabled the automatic scheduling of resources to VMs, further increasing consolidation while supporting service-level agreements, fairness, normalized headroom for demand spikes, and reservation of spare resources for failover.
However, at this point, some datacenters are not continuing to increase VM consolidation per host, due to concerns including the impact of resource overcommitment on application performance. Some are not adopting power proportionality technologies, due to the risk of added latency in response to demand spikes. Some are underutilizing power capacity, due to conservative assumptions about
server peak power draw. For these cases, I would argue that the academic and industry solutions (certainly including those from VMware!) have not fully reached the bar of easy being green; the solutions require manual tuning or do not interoperate seamlessly with other key datacenter software.
To push datacenter resource efficiency forward from this point, I believe the following are crucial:
At VMware, we are working on using machine learning to manage resources to maintain application performance targets, which avoids manual tuning of low-level resource controls. We are exploring the use of analytics to automatically identify demand patterns to support proactive preparation for expected demand spikes. And we are continuing to deepen resource management interoperation, including investigating rack power budget management across a set of hosts running VM workloads in accordance with cloud resource management system.
I'd be interested to hear "easy to be green" examples from across the Sustainable Computing community, as well as particular examples where we've made strides but haven't yet completely reached the bar.
Personal webpage: https://profiles.stanford.edu/sven-beiker
The automotive industry has been leading the technology and innovation to reduce its environmental impact as well as minimizing the costs and resource usages. The major topics of sustainability in traditional automotive industry include but do not limit to improving the efficiencies of vehicles, vehicle recycling and real-time driving safety and comfort enhancements. Nowadays safety and efficiency in road traffic have been considered as top priorities. Automated driving technologies have the potential to make mobility optimally safe and sustainable in the future. We spoke to a distinguished researcher, Dr. Sven A. Beiker, in the automated driving research area to find out more about the field.
Favorite memory as a researcher/Executive Director of CARS
The most enjoyable part is to have the great opportunity to discuss with a diverse spectrum of people, including students, faculties, industry experts and top-level executives. It is a great experience to learn from them and discuss with them on what the future of automotive industry might be. This broad variety of people sometimes can bring innovative thoughts to the automated vehicle research.
Opinions and comments towards green vehicular systems; impact of automated driving towards a more sustainable vehicular systems
It is important to understand that there are different perspectives of sustainability, when we talk about vehicular systems. In my opinion, the most important two perspectives in this regard are safety and environment. Automated driving technologies and systems definitely help to improve the safety and driving experiences for drivers. There exist some concerns about the environmental perspective. If the driving can get much easier, people may end up with driving a lot more when they do not need to think much about the driving. It is not very clear at the current stage whether automated driving will help reduce or increase traffic overall. An existing challenge for us is to help propose solutions to achieve a balance between driving efforts and driving distances.
Most promising applications/research in autonomous driving for sustainability
As mentioned above, safety and environment are the most important two perspectives here. Collision avoidance technologies and distracted driving solutions are most important for safety. Traffic control and optimization technologies can be used to improve the environmental aspect. Good examples include methods to respond to traffic dynamics and enable closer follow distances among vehicles*.
Brief takeaways for students and young researchers
It is important to apply interdisciplinary thinking in doing automated driving research. Good researchers cannot only focus on traditional handbooks and theories of automotive research. Keep eyes more open and think broadly.
* Note: computer-assisted and networked driving systems can react to traffic dynamics and potentially dangerous situations much faster and more precisely than a human being, thus enabling closer following distances among vehicles to increase the road efficiency and at the same providing safety guarantees.
Since the Smart Meters location in the users household makes it an easy target for tampering attacks, a first security challenge is to provide them with security mechanisms capable of making the device tamper proof, in order to ensure that the gathered readings are not altered, leading to incorrect billing or to wrong estimations of the power usage. The goal of this kind of attack can range from monetary gains (it has been estimated that 6 billion of dollars worth of power is being stolen from the U.S. electrical power system ) to Denial of Service (DoS) or other terroristic attacks. The most widely adopted countermeasure is to include a Hardware Security Module (HSM) in the metering device, which can provide both physical and logical protection to cryptographic and sensitive data (e.g. cryptographic keys) and even execute specific algorithms which require a secure and controlled environment (e.g. a billing protocol).
In addition to integrity, data confidentiality must also be ensured. Since Smart Meters are connected to the Smart Grid communication network to send their readings to the power suppliers, external subjects might access these data and infer private information about the users. To tackle such privacy issues, Cavoukian et al.  propose the Privacy by design paradigm and suggest several guidelines to utilities and operators dealing with smart metering data. The underlying basic criterion is that any entity providing personal information related to energy consumption data to a third party must obtain in advance the express consent of the individuals whose meter readings are collected.
However, designing a privacy-friendly infrastructure for metering data collection is still an open issue, due to the criticalities of the Smart Grid environment, including scalability, reliability and fault resiliency.
Several approaches have been proposed by the scientific community (the reader is referred to  for a comprehensive overview). The most widely investigated are:
It follows that none of the above mentioned techniques can be considered as a panacea for the privacy issues of the Smart Grid scenario: only combining such methods in a comprehensive framework can provide a sufficient level of privacy protection for the users without compromising the effectiveness of the management of the electricity grid of the future.
 P. McDaniel and S. McLaughlin. Security and privacy challenges in the smart grid. Security
Privacy, IEEE, 7(3):75 77, may-june 2009.
 Ann Cavoukian, Jules Polonetsky, and Christopher Wolf. Smartprivacy for the smart grid:
embedding privacy into the design of electricity conservation. Identity in the Information
Society, 3:275294, 2010.
 M. Jawurek, F. Kerschbaum, and G. Danezis. Sok: Privacy technologies for smart grids a
survey of options., 2012.
In 2010, HP Labs' "Design of Farm Waste-Driven Supply Side Infrastructure for Data Centers"  drew the attention of the sustainable computing community to the potential of farms to drive computing in a more sustainable direction. The paper studied how a bio-digester fed with farm waste could be used to power a data centre. This article highlights another facet of the link between information technology and farming: the significant potential for computing to improve the sustainability of the agricultural and broader food-related sectors of the economy.
As addicted as many of us are to computers and computing services in their various shapes and forms, food is even more difficult to abandon. Unfortunately, the agricultural sector is also one of the largest sources of emissions, estimated to account for 10-12% of global anthropogenic emissions in a recent IPCC report . With the population anticipated to continue increasing for the next few decades and individuals on average consuming more animal products as their wealth increases, agriculture faces significant challenges in the coming years. Expert testimony to the UN predicts that food production will need to double by 2050 .
The use of information technology is not alien to the agricultural sector. There's been significant technological development in the agricultural sector over the past decade though it has happened largely disconnected from the sustainable computing community. In spite of stereotypes of farmers being technologically backwards, technologies such as auto steering of farm vehicles have become relatively common  far in advance of self-driving cars, and these aren't the only ways in which this sector has advanced.
If you have not given too much thought to agriculture as a problem with computing aspects, take a look at the following excerpt from a report by the Kauffman Foundation on agricultural technology investment opportunities , which also outlines some of the startups active in this sector (p. 17, 25):
"... the most disruptive breakthroughs in AgTech may come from combining innovations in multiple areas. One particular exciting illustration of this combination is an idea known as "integrated farming systems" that will integrate genetics, physical inputs, IT sensing, and smart machinery. Through advances in software and environmental testing, farmers will be able to create custom field prescriptions for seeds, fertilizer, pest controls. Smart machinery then will carry out the prescribed treatment, all the while collecting further data that will provide feedback to the farmer."
"... Over the past five years, innovations in agriculture technology (precision ag innovations, data analytics and processing, platforms for the collection and distribution of complex data streams, and IT-driven extensions) are on the rise."
Data-driven agriculture fed by sensor networks and smart machinery may reduce the need for pesticides, decrease fertilizer consumption, limit nitrogen runoff problems  impacting marine ecosystems, address aquifer depletion , increase yields, and potentially also combat deforestation and desertification.
Incorporating computing more extensively in the food sector might improve sustainability more broadly. Consider, for example, the potential for improvements discussed by IBM , which can reduce the 30-40% of food production that goes to waste by improving traceability throughout the supply chain and enabling the sources of food-related infections to be isolated.
As you move closer to the plate, still further opportunities arise. Databases of the properties of foods can be analyzed to suggest [9, 10] promising flavour combinations that might result in more sustainable and affordable meals. Environmental impacts can vary significantly  from one type of food to another, and improving the taste and nutritional quality of low-cost food can be of particular benefit to those living in extreme poverty , who may choose to spend some of their scarce dollars elsewhere in search of some small pleasures and thus remain caught in a poverty trap. Malnutrition has been estimated  as a contributing factor in a majority of the deaths of children in the developing world, with some arguing  that high rates of child mortality contribute to high fertility rates thereby placing stress on the sustainability of communities.
From farm to fork opportunities remain for computing researchers to play a role in making the food system more sustainable.
 "Design of farm waste-driven supply side infrastructure for data centers," Sharma, Ratnesh et al, in: Proceedings of ASME 2010 4th International Conference on Energy Sustainability, Phoenix, USA, 2010, http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=1607271
 "Agriculture, Forestry and Other Land Use (AFOLU)", in: Climate Change 2014: Mitigation of Climate Change, Intergovernmental Panel on Climate Change, 2013, http://www.ipcc.ch/report/ar5/wg3/
 "Food production must double by 2050 to meet demand from world's growing population, innovative strategies needed to combat hunger, experts tell second committee", http://www.un.org/News/Press/docs/2009/gaef3242.doc.htm
 “Looking Forward from Two Decades of Precision Agriculture: The CropLife/Purdue University Survey”, Erickson, Bruce, in: InfoAg 2013, http://www.infoag.org/presentation/3/186/
 “AgTech: Challenges and Opportunities for Sustainable Growth,” Dutia, Suren, Kauffman Foundation, 2014, http://www.kauffman.org/newsroom/2014/04/agriculture-tech-advances-opportunities-for-entrepreneurs
 "Agricultural runoff fuels large phytoplankton blooms in vulnerable areas of the ocean," Beman, Michael J., Arrigo, Kevin R. and Matson, Pamela A. (2005), in: Nature, 434:7030 (211-214), http://dx.doi.org/10.1038/nature03370
 “Global depletion of groundwater resources,” Wada, Yoshihide, van Beek, Ludovicus P. H., van Kempen, Cheryl M., Reckman, Josef W. T. M., Vasak, Slavek and Bierkens, Marc F. P. (2010), in: Geophysical Research Letters, 37:20, http://dx.doi.org/10.1029/2010gl044571
 “Smarter Food,” IBM, http://www.ibm.com/smarterplanet/us/en/food_technology/article/food_technology.html
 “How A Former Google Data Guy Could Change What We Eat For Breakfast,” TechCrunch, July 2014, http://techcrunch.com/2014/07/03/how-a-former-google-data-guy-could-change-what-we-eat-for-breakfast/
 “We Put a Computer in Charge of Our Test Kitchen for a Day, and Here's What Happened,” Bon Appetit, June 2014, http://www.bonappetit.com/test-kitchen/inside-our-kitchen/article/chef-watson-in-the-ba-test-kitchen
 “Climate and Environmental Impacts,” A Meat Eater's Guide to Climate Change and Health, Environmental Working Group, 2011, http://www.ewg.org/meateatersguide/a-meat-eaters-guide-to-climate-change-health-what-you-eat-matters/climate-and-environmental-impacts/
 Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty, Banerjee, Abhijit and Duflo, Esther, PublicAffairs, 2011. See also http://pooreconomics.com/chapters/2-billion-hungry-people
 “The effects of malnutrition on child mortality in developing countries,” Pelletier, D. L. et al. (1995), in: Bulletin of the World Health Organization, 73:4 (443-448), http://libdoc.who.int/bulletin/1995/Vol73-No4/bulletin_1995_73(4)_443-448.pdf
 “Parental investment and the optimization of human family size,” Lawson, David W and Mace, Ruth (2011), in: Philosophical Transactions of the Royal Society B: Biological Sciences, 366:1563 (333-343), http://dx.doi.org/10.1098/rstb.2010.0297