survey

Computational Sustainability: A Socio-technical Perspective

Authors:
Deya Chatterjee

ZS Associates, Kharadi, Pune, India

ZS Associates, Kharadi, Pune, India
View Profile

,
Shrisha Rao

International Institute of Information Technology - Bangalore, Bangalore, India

International Institute of Information Technology - Bangalore, Bangalore, India
View Profile

Authors Info & Claims

ACM Computing Surveys Volume 53 Issue 5Article No.: 101pp 1–29https://doi.org/10.1145/3409797

Published:28 September 2020Publication History

ACM Computing Surveys

Abstract

This is a consolidated look at computational techniques for sustainability, and their limits and possibilities. Sustainability is already well established as a concern and a topic of study and practice, given the alarming increase of environmental degradation, pollution, and other adverse effects of industrialization and urbanization. Computational sustainability, which focuses on the use of effective computational models and computational approaches to help achieve the goal of sustainability, has attracted interest from computer science researchers worldwide. We review recent work on computational techniques applied to a range of domains related to sustainability, from bio-surveillance to poverty mapping, from renewable energy production forecasting to crop disease monitoring, and from agent-based modeling to stochastic network design. In sustainable computing, we discuss some directions that have recently been explored. Finally, we analyze research directions that could be explored in the future to achieve the goal of long-term environmental sustainability.

References

Pragati Agrawal and Shrisha Rao. 2014. Energy-aware scheduling of distributed systems. IEEE Trans. Autom. Sci. Eng. 11, 4 (Oct. 2014), 1163--1175. DOI:https://doi.org/10.1109/TASE.2014.2308955Google ScholarCross Ref
Idawaty Ahmad. 2015. A survey of energy-aware real time scheduling tools. In Proceedings of the 3rd International Conference on Green Computing, Technology and Innovation (ICGCTI’15). 19--30.Google Scholar
Ishfaq Ahmad and Sanjay Ranka. 2016. Handbook of Energy-aware and Green Computing -- Two Volume Set. CRC Press.Google Scholar
Abdulla M. Al-Qawasmeh, Sudeep Pasricha, Anthony A. Maciejewski, and Howard Jay Siegel. 2015. Power and thermal-aware workload allocation in heterogeneous data centers. IEEE Trans. Comput. 64, 2 (Feb. 2015), 477--491. DOI:https://doi.org/10.1109/TC.2013.116Google ScholarCross Ref
Blake Alcott. 2005. Jevons’ paradox. Ecol. Econ. 54, 1 (July 2005), 9--21. DOI:10.1016/j.ecolecon.2005.03.020Google ScholarCross Ref
Francisco Almeida, Marcos D. Assunção, Jorge Barbosa, Vicente Blanco, Ivona Brandic, Georges Da Costa, Manuel F. Dolz, Anne C. Elster, Mateusz Jarus, Helen D. Karatza, et al. 2018. Energy monitoring as an essential building block towards sustainable ultrascale systems. Sustain. Comput. Inform. Syst. 17 (Mar. 2018), 27--42.Google Scholar
Ibtehaj AlMusbahi, Ola Anderkairi, Reem H. Nahhas, Bashair AlMuhammadi, and M. Hemalatha. 2017. Survey on green computing: Vision and challenges. Int. J. Comput. Applic. 167, 10 (2017).Google ScholarCross Ref
Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, Oscar Fontenla-Romero, J. Gary Polhill, Tony Craig, Javier Bajo, and Juan Manuel Corchado. 2017. Agent-based Modeling of Sustainable Behaviors. Springer.Google Scholar
Javier Alonso-Mora, Samitha Samaranayake, Alex Wallar, Emilio Frazzoli, and Daniela Rus. 2017. On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment. Proc. Nat. Acad. Sci. 114, 3 (2017), 462--467.Google ScholarCross Ref
Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, and Hwee-Pink Tan. 2015. Machine learning in wireless sensor networks: Algorithms, strategies, and applications. IEEE Commun. Surv. Tutor. 4 (Mar. 2015), 1996--2018.Google Scholar
Rudy Arthur, Chris A. Boulton, Humphrey Shotton, and Hywel T. P. Williams. 2018. Social sensing of floods in the UK. PLoS One 13, 1 (2018). DOI:10.1371/journal.pone.0189327Google Scholar
Hiroshi Asano, N. Hatziargyriou, R. Iravani, and C. Marnay. 2007. Microgrids: An overview of ongoing research, development, and demonstration projects. IEEE Power Energy Mag. (Jan. 2007), 78--94.Google Scholar
Jocelyn L. Aycrigg, Craig Groves, Jodi A. Hilty, J. Michael Scott, Paul Beier, D. A. Boyce Jr., Dennis Figg, Healy Hamilton, Gary Machlis, Kit Muller, et al. 2016. Completing the system: Opportunities and challenges for a national habitat conservation system. BioScience 66, 9 (2016), 774--784. DOI:10.1093/biosci/biw090Google ScholarCross Ref
Junwen Bai, Sebastian Ament, Guillaume Perez, John Gregoire, and Carla Gomes. 2018a. An efficient relaxed projection method for constrained non-negative matrix factorization with application to the phase-mapping problem in materials science. In Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR’18), Vol. 10848. Springer, 52--62.Google ScholarDigital Library
Junwen Bai, Yexiang Xue, Johan Bjorck, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein, Santosh K. Suram, R. Bruce van Dover, John M. Gregoire, and Carla P. Gomes. 2018b. Phase-mapper: Accelerating materials discovery with AI. AI Magazine 39, 1 (2018).Google Scholar
Prithviraj Banerjee, Chandrakant Patel, Cullen Bash, Amip Shah, and Martin Arlitt. 2012. Towards a net-zero data center. ACM Journal on Emerging Technologies in Computing Systems (JETC) 8, 4 (Oct. 2012). DOI:https://doi.org/10.1145/2367736.2367738Google Scholar
Chandrayee Basu and Mukesh Singhal. 2016. Trust dynamics in human autonomous vehicle interaction: A review of trust models. In Proceedings of the AAAI Spring Symposium Series.Google Scholar
Tanya Y. Berger-Wolf, Daniel I. Rubenstein, Charles V. Stewart, Jason A. Holmberg, Jason Parham, Sreejith Menon, Jonathan Crall, Jon Van Oast, Emre Kiciman, and Lucas Joppa. 2017. Wildbook: Crowdsourcing, computer vision, and data science for conservation. arXiv:1710.08880 (2017).Google Scholar
Frans Berkhout and Julia Hertin. 2001. Impacts of information and communication technologies on environmental sustainability: Speculations and evidence. Report to the OECD, Brighton 21 (2001).Google Scholar
Andrea Bianco, Reza Mashayekhi, and Michela Meo. 2017. On the energy consumption computation in content delivery networks. Sustain. Comput. Inform. Syst. 16 (Dec. 2017), 56--65. DOI:10.1016/j.suscom.2017.08.008Google Scholar
Najet Bichraoui-Draper. 2015. Computational Sustainability Assessment: Agent-based Models and Agricultural Industrial Ecology. Ph.D. Dissertation. Troyes.Google Scholar
Lorenz T. Biegler, Ignacio E. Grossmann, and Arthur W. Westerberg. 1997. Systematic Methods of Chemical Process Design. Prentice Hall, Old Tappan, NJ (United States).Google Scholar
E. Blevis. 2007. Sustainable interaction design: Invention 8 disposal, renewal 8 reuse. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 503--512.Google ScholarDigital Library
Eric Bonabeau. 2002. Agent-based modeling: Methods and techniques for simulating human systems. Proc. Nat. Acad. Sci. 99, suppl 3 (2002), 7280--7287. Retrieved from http://www.pnas.org/content/99/suppl_3/7280. DOI:10.1073/pnas.082080899Google ScholarCross Ref
Pierre Bourque, Richard E. Fairley, et al. 2014. Guide to the Software Engineering Body of Knowledge (SWEBOK(R)): Version 3.0. Retrieved from https://www.computer.org/web/swebok.Google ScholarDigital Library
Manuel Castelo Branco and Lúcia Lima Rodrigues. 2006. Corporate social responsibility and resource-based perspectives. J. Bus. Ethics - Springer 69, 2 (2006), 111--132. DOI:https://doi.org/10.1007/s10551-006-9071-zGoogle ScholarCross Ref
G. H. Brundtland. 1987. Our Common Future (“Brundtland report”). Report of the World Commission on Environment and Development. Published by the United Nations through the Oxford University Press, Oxford.Google Scholar
John Bruschi, Peter Rumsey, Robin Anliker, Larry Chu, and Stuart Gregson. 2011. Best Practices Guide for Energy-Efficient Data Center Design. Technical Report. National Renewable Energy Laboratory (NREL), U.S. Department of Energy.Google Scholar
Robert Bryce. 2011. Power Hungry: The Myths of “Green” Energy and the Real Fuels of the Future. PublicAffairs.Google Scholar
Coral Calero and Mario Piattini. 2015. Introduction to green in software engineering. In Green in Software Engineering. Springer, 3--27.Google Scholar
Coral Calero and Mario Piattini. 2017. Puzzling out software sustainability. Sustain. Comput. Inform. Syst. 16 (2017), 117--124. DOI:https://doi.org/10.1016/j.suscom.2017.10.011Google ScholarCross Ref
Michel Callon. 2009. Civilizing markets: Carbon trading between in vitro and in vivo experiments. Account. Organiz. Soc. 34, 3--4 (2009), 535--548.Google ScholarCross Ref
Simon Caney and Cameron Hepburn. 2011. Carbon trading: Unethical, unjust and ineffective? Royal Inst. Philos. Supplem. 69 (2011), 201--234.Google ScholarCross Ref
Swati V. Chande. 2014. Computational sustainability: An emerging research and academic discipline. Int. J. Adv. Comput. Sci. Technol. 3, 8 (Aug. 2014), 421--425.Google Scholar
Paul Chatterton. 2013. Towards an agenda for post-carbon cities: Lessons from Lilac, the UK’s first ecological, affordable cohousing community. Int. J. Urban Reg. Res. 37, 5 (2013), 1654--1674.Google ScholarCross Ref
R. Cheour, R. Urunela, Y. Trinquet, and M. Abid. 2013. Simulation of efficient real-time scheduling and power optimisation. Int. J. Comput. Sci. Iss. 10, 2 (Mar. 2013), 338--346.Google Scholar
Maurice Cheung, Julián Mestre, David B. Shmoys, and José Verschae. 2017. A primal-dual approximation algorithm for min-sum single-machine scheduling problems. SIAM J. Disc. Math. 31, 2 (2017), 825--838. DOI:10.1137/16M1086819Google ScholarCross Ref
William Clark and Nancy Dickson. 2003. Sustainability science: The emerging research program. Proc. Nat. Acad. Sci. 100, 14 (Aug. 2003), 8059--8061.Google ScholarCross Ref
Brian Clegg. 2009. Eco-logic: Cutting Through the Greenwash: Truth, Lies, and Saving the Planet. Eden Project, London.Google Scholar
Rosaria Conte and Mario Paolucci. 2014. On agent-based modeling and computational social science. Front. Psychol. 5 (2014), 668.Google ScholarCross Ref
Anthony Costello, Mustafa Abbas, Adriana Allen, Sarah Bell, Richard Bellamy, Sharon Friel, Nora Groce, Anne Johnson, Maria Kett, Maria Lee, Caren Levy, Mark Maslin, David McCoy, Bill McGuire, Hugh Montgomery, David Napier, Christina Pagel, Jinesh Patel, Jose Antonio Puppim de Oliveira, Nanneke Redclift, Hannah Rees, Daniel Rogger, Joanne Scott, Judith Stephenson, John Twigg, Jonathan Wolff, and Craig Patterson. 2009. Managing the health effects of climate change. Lancet 373, 9676 (May 2009). DOI:https://doi.org/10.1016/S0140-6736(09)60935-1Google ScholarCross Ref
Wolfgang Cramer, Alberte Bondeau, F. Ian Woodward, I. Colin Prentice, Richard A. Betts, Victor Brovkin, Peter M. Cox, Veronica Fisher, Jonathan A. Foley, Andrew D. Friend, et al. 2001. Global response of terrestrial ecosystem structure and function to CO2 and climate change: Results from six dynamic global vegetation models. Glob. Change Biol. 7, 4 (2001), 357--373.Google ScholarCross Ref
Peter Cramton and Suzi Kerr. 2002. Tradeable carbon permit auctions: How and why to auction not grandfather. Energy Policy 30, 4 (Mar. 2002). DOI:https://doi.org/10.1016/S0301-4215(01)00100-8Google ScholarCross Ref
Rosa M. Cuéllar-Franca and Adisa Azapagic. 2015. Carbon capture, storage and utilisation technologies: A critical analysis and comparison of their life cycle environmental impacts. J. CO2 Util. 9 (Mar. 2015), 82--102. DOI:https://doi.org/10.1016/j.jcou.2014.12.001Google Scholar
D. Curseu, M. Popa, D. Sirbu, and I. Stoian. 2010. Potential impact of climate change on pandemic influenza risk. In Global Warming, I. Dincer, A. Hepbasli, A. Midilli, and T. H. Karakoc (Eds.). Springer, Boston, MA, 643--657.Google Scholar
Samuel A. Cushman. 2006. Effects of habitat loss and fragmentation on amphibians: A review and prospectus. Biol. Conserv. 128, 2 (2006), 231--240.Google ScholarCross Ref
Fábio Andre Souto da Silva et al. 2017. Computational sustainability for smart city design. In Proceedings of the 13th International Conference on Intelligent Environments. 60--67.Google Scholar
L. Minh Dang, Syed Ibrahim Hassan, Im Suhyeon, Arun Kumar Sangaiah, Irfan Mehmood, Seungmin Rho, Sanghyun Seo, and Hyeonjoon Moon. 2018. UAV-based wilt detection system via convolutional neural networks. Sustain. Comput. Inform. Syst. (May 2018). DOI:10.1016/j.suscom.2018.05.010Google Scholar
Mohammad Dastbaz, Colin Pattinson, and Babak Akhgar. 2015. Green Information Technology: A Sustainable Approach (1st ed.). Morgan Kaufmann Publishers Inc., San Francisco, CA.Google Scholar
C. Delimitrou and C. Kozyrakis. 2013. Paragon: QoS-aware scheduling for heterogeneous datacenters. In Proceedings of the ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS’13). 77--88.Google Scholar
Dieter Deublein and Angelika Steinhauser. 2011. Biogas from Waste and Renewable Resources: An Introduction. John Wiley 8 Sons.Google Scholar
Thomas G. Dietterich. 2009. Machine learning in ecosystem informatics and sustainability. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’09). 8--13.Google Scholar
Bistra Dilkina. 2012. Computational Advances in Conservation Planning for Landscape Connectivity. Retrieved from http://www.computational-sustainability.org/compsust12/slides/Dilkina.pdf.Google Scholar
C. F. DiSalvo, P. Sengers, and H. Brynjarsdóttir. 2010. Mapping the landscape of sustainable HCI. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 1975--1984.Google Scholar
Yama Dixit, David A. Hodell, and Cameron A. Petrie. 2014. Abrupt weakening of the summer monsoon in northwest India &sim;4100 yr ago. Geology 42, 4 (Apr. 2014). DOI:https://doi.org/10.1130/G35236.1Google Scholar
Djamel Djenouri and Miloud Bagaa. 2017. Energy-aware constrained relay node deployment for sustainable wireless sensor networks. IEEE Trans. Sustain. Comput. 2, 1 (Mar. 2017), 30--42.Google ScholarCross Ref
Jacobus A. Du Pisani. 2006. Sustainable development—historical roots of the concept. Environ. Sci. 3, 2 (June 2006), 83--96. DOI:https://doi.org/10.1080/15693430600688831Google ScholarCross Ref
David Dudgeon, Angela H. Arthington, Mark O. Gessner, Zen-Ichiro Kawabata, Duncan J. Knowler, Christian Lévêque, Robert J. Naiman, Anne-Hélène Prieur-Richard, Doris Soto, Melanie L. J. Stiassny, et al. 2006. Freshwater biodiversity: Importance, threats, status and conservation challenges. Biol. Rev. 81, 2 (2006), 163--182.Google ScholarCross Ref
Steve Easterbrook. 2014. From computational thinking to systems thinking: A conceptual toolkit for sustainability computing. In Proceedings of the ICT for Sustainability Conference (ICT4S’14). Atlantis Press.Google ScholarCross Ref
Jochen Eisner, Stefan Funke, and Sabine Storandt. 2011. Optimal route planning for electric vehicles in large networks. In Proceedings of the 25th AAAI Conference on Artificial Intelligence.Google Scholar
Jane Elith, Steven J. Phillips, Trevor Hastie, Miroslav Dudík, Yung En Chee, and Colin J. Yates. 2011. A statistical explanation of MaxEnt for ecologists. Divers. Distrib. 17, 1 (2011), 43--57.Google ScholarCross Ref
John Elkington. 1998. Partnerships from cannibals with forks: The triple bottom line of 21st-century business. Environ. Qual. Manag. 8, 1 (1998), 37--51. DOI:https://doi.org/10.1002/tqem.3310080106Google ScholarCross Ref
S. Ellner and J. Guckenheimer. 2006. Dynamic Models in Biology. Princeton University Press, Princeton, NJ.Google Scholar
S. Ermon, J. Conrad, C. Gomes, and B. Selman. 2010. Playing games against nature: Optimal policies for renewable resource allocation. In Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI’10).Google Scholar
Stefano Ermon, Ronan Le Bras, Santosh K. Suram, John M. Gregoire, Carla P. Gomes, Bart Selman, and Robert Bruce van Dover. 2015. Pattern decomposition with complex combinatorial constraints: Application to materials discovery. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI’15). 636--643.Google Scholar
Geoff Evans and Liam Phelan. 2016. Transition to a post-carbon society: Linking environmental justice and just transition discourses. Energy Policy 99 (2016), 329--339.Google ScholarCross Ref
Fei Fang, Thanh H. Nguyen, Robert Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, Amandeep Singh, Brian C. Schwedock, Milind Tambe, and Andrew Lemieux. 2017. PAWS—A deployed game-theoretic application to combat poaching. AI Mag. 38, 1 (2017), 23.Google ScholarCross Ref
Daniel A. Farber. 2012. Pollution markets and social equity: Analyzing the fairness of cap and trade. Ecol. Law Quart. 39, 1 (2012).Google Scholar
Wu-chun Feng. 2014. The Green Computing Book: Tackling Energy Efficiency at Large Scale. CRC Press.Google Scholar
Daniel Fink, Theodoros Damoulas, and Jaimin Dave. 2013. Adaptive spatio-temporal exploratory models: Hemisphere-wide species distributions from massively crowdsourced eBird data. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI’13).Google Scholar
Douglas H. Fisher. 2017. A selected summary of AI for computational sustainability. In Proceedings of the AAAI Conference on Artificial Intelligence. 4852--4857. Retrieved from https://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14994.Google Scholar
Douglas H. Fisher, Zimei Bian, and Selina Chen. 2016. Incorporating sustainability into computing education. IEEE Intell. Syst. 31, 5 (Sep. 2016), 93--96.Google ScholarCross Ref
Douglas H. Fisher, Jacqueline Cameron, Tamara Clegg, and Stephanie August. 2018. Integrating social good into CS education. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE’18). ACM, New York, NY, 130--131. DOI:https://doi.org/10.1145/3159450.3159622Google ScholarDigital Library
Dr.-Ing. Thomas Fleissner. 2019. Artificial Intelligence and CSR—Implementation of new possibilities. Retrieved from https://dfge.de/en/sustainability-intelligence/artificial-intelligence-csr/.Google Scholar
Alcides Fonseca and Bruno Cabral. 2017. Understanding the impact of task granularity in the energy consumption of parallel programs. Sustain. Comput. Inform. Syst. (Nov. 2017). DOI:10.1016/j.suscom.2017.10.014Google Scholar
Kenneth M. Ford, Clark Glymour, and Patrick J. Hayes. 1997. On the other hand... Cognitive prostheses. AI Mag. 18, 3 (1997), 104.Google Scholar
Karen A. Frenkel. 2009. Computer science meets environmental science. In Communications of the ACM (9), Vol. 52. ACM, 23. DOI:https://doi.org/10.1145/1562164.1562174Google Scholar
A. Garchitorena, S. H. Sokolow, B. Roche, C. N. Ngonghala, M. Jocque, A. Lund, M. Barry, E. A. Mordecai, G. C. Daily, J. H. Jones, J. R. Andrews, E. Bendavid, S. P. Luby, A. D. LaBeaud, K. Seetah, J. F. Guégan, M. H. Bonds, and G. A. De Leo. 2017. Disease ecology, health and the environment: A framework to account for ecological and socio-economic drivers in the control of neglected tropical diseases. Philos. Trans. Roy. Soc. B 372 (2017). DOI:https://doi.org/10.1098/rstb.2016.0128Google Scholar
Lucas A. Garibaldi, Ingolf Steffan-Dewenter, Rachael Winfree, Marcelo A. Aizen, Riccardo Bommarco, Saul A. Cunningham, Claire Kremen, Luísa G. Carvalheiro, Lawrence D. Harder, Ohad Afik, Ignasi Bartomeus, Faye Benjamin, Virginie Boreux, Daniel Cariveau, Natacha P. Chacoff, Jan H. Dudenhöffer, Breno M. Freitas, Jaboury Ghazoul, Sarah Greenleaf, Juliana Hipólito, Andrea Holzschuh, Brad Howlett, Rufus Isaacs, Steven K. Javorek, Christina M. Kennedy, Kristin M. Krewenka, Smitha Krishnan, Yael Mandelik, Margaret M. Mayfield, Iris Motzke, Theodore Munyuli, Brian A. Nault, Mark Otieno, Jessica Petersen, Gideon Pisanty, Simon G. Potts, Romina Rader, Taylor H. Ricketts, Maj Rundlöf, Colleen L. Seymour, Christof Schüepp, Hajnalka Szentgyörgyi, Hisatomo Taki, Teja Tscharntke, Carlos H. Vergara, Blandina F. Viana, Thomas C. Wanger, Catrin Westphal, Neal Williams, and Alexandra M. Klein. 2013. Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science 339, 6127 (2013), 1608--1611. DOI:https://doi.org/10.1126/science.1230200Google Scholar
Shahrzad Gholami, Benjamin Ford, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, and Joshua Mabonga. 2017. Taking it for a test drive: A hybrid spatio-temporal model for wildlife poaching prediction evaluated through a controlled field test. In Proceedings of the European Conference on Machine Learning 8 Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’17). Springer, 292--304.Google ScholarCross Ref
James P. Gibbs. 2001. Wetland loss and biodiversity conservation. Conserv. Biol. 14, 1 (Dec. 2001), 314--317. DOI:10.1046/j.1523-1739.2000.98608.xGoogle Scholar
Tamra Gilbertson, Oscar Reyes, and Larry Lohmann. 2009. Carbon Trading: How It Works and Why It Fails. Vol. 7. Dag Hammarskjöld Foundation Uppsala.Google Scholar
A. Gitelson, G. Garbuzov, F. Szilagyi, K. H. Mittenzwey, A. Karnieli, and A. Kaiser. 1993. Quantitative remote sensing methods for real-time monitoring of inland waters quality. Int. J. Rem. Sens. 14, 7 (1993), 1269--1295.Google ScholarCross Ref
James Glanz. 2012. Power, Pollution and the Internet. Retrieved from http://nyti.ms/VqS2fY.Google Scholar
A. K. Goel. 2013. Biologically inspired design: A new program for computational sustainability. IEEE Intell. Syst. 28, 3 (May--June 2013), 80--84. DOI:https://doi.org/10.1109/MIS.2013.58Google ScholarDigital Library
Carla Gomes, Thomas Dietterich, Christopher Barrett, Jon Conrad, Bistra Dilkina, Stefano Ermon, Fei Fang, Andrew Farnsworth, Alan Fern, Xiaoli Fern, et al. 2019. Computational sustainability: Computing for a better world and a sustainable future. Commun. ACM 62, 9 (2019), 56--65.Google ScholarDigital Library
C. Gomes and B. Selman. 2007. Science of constraints. Constr. Program. Lett. 1 (2007), 15--20.Google Scholar
Carla P. Gomes. 2011. Computational sustainability. In Proceedings of the International Symposium on Intelligent Data Analysis (IDA’11). 8. DOI:10.1.1.158.2293Google Scholar
Luis F. Gonzalez, Glen A. Montes, Eduard Puig, Sandra Johnson, Kerrie Mengersen, and Kevin J. Gaston. 2016. Unmanned aerial vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation. Sensors 16, 1 (2016). Retrieved from http://www.mdpi.com/1424-8220/16/1/97. DOI:10.3390/s16010097Google Scholar
Meredith L. Gore. 2017. Global risks, conservation, and criminology. Conserv. Criminol. (May 2017), 1--23.Google Scholar
Neil S. Grigg. 2005. Water Resources Management. Wiley Online Library.Google Scholar
Diarmuid Grimes, Helmut Simonis, Annabelle Pratt, and Charles Sheridan. 2012. Automated energy usage optimization for the residential sector: Impact of price tariffs. In Proceedings of the 3rd International Conference on Computational Sustainability (CompSust’12).Google Scholar
Sandeep K. S. Gupta, Tridib Mukherjee, Georgios Varsamopoulos, and Ayan Banerjee. 2011. Research directions in energy-sustainable cyber-physical systems. Sustain. Comput. Inform. Syst. 1, 1 (Mar. 2011), 57--74.Google Scholar
G. Hardin. 1968. The tragedy of the commons. Science 162, 3859 (1968), 1243--1248.Google Scholar
Robert R. Harmon and Nora Auseklis. 2009. Sustainable IT services: Assessing the impact of green computing practices. In Proceedings of the Portland International Conference on Management of Engineering 8 Technology (PICMET’09).. IEEE, 1707--1717.Google Scholar
Kyle Harper. 2017. The Fate of Rome: Climate, Disease, and the End of an Empire. Princeton University Press.Google Scholar
Arnd Hartmanns, Holger Hermanns, and Pascal Berrang. 2012. A comparative analysis of decentralized power grid stabilization strategies. In Proceedings of the Winter Simulation Conference (WSC’12). IEEE, 1--13.Google ScholarDigital Library
Richard Heinberg. 2015. Afterburn: Society Beyond Fossil Fuels. New Society Publishers.Google Scholar
Richard Heinberg and Daniel Lerch. 2010. The Post Carbon Reader: Managing the 21st Century’s Sustainability Crises. Watershed Media.Google Scholar
Holger Hermanns and Arnd Hartmanns. 2013. An Internet-inspired approach to power grid stability/Internet-Konzepte für Stromnetzstabilität. IT-Inf. Technol. 55, 2 (2013), 45--51.Google Scholar
Edgar G. Hertwich and Glen P. Peters. 2009. Carbon footprint of nations: A global, trade-linked analysis. Environ. Sci. Technol. 43, 16 (2009), 6414--6420.Google ScholarCross Ref
Trevor T. Hill. 2007. Managing scarcity: Changing the paradigm for sustainable resource management. Proc. Water Environ. Fed. 16 (2007), 2659--2665. DOI:10.2175/193864707787960107Google ScholarCross Ref
J. Hilton. 1984. Airborne remote sensing for freshwater and estuarine monitoring. Water Res. 18, 10 (1984), 1195--1223. DOI:https://doi.org/10.1016/0043-1354(84)90026-5Google ScholarCross Ref
Lorenz M. Hilty. 2011. Information Technology and Sustainability: Essays on the Relationship between Information Technology and Sustainable Development. BoD--Books on Demand.Google Scholar
Lorenz M. Hilty. 2015. Computing efficiency, sufficiency, and self-sufficiency: A model for sustainability. In Proceedings of the 1st Workshop on Computing within Limits (LIMITS’15).Google Scholar
Lorenz M. Hilty and Bernard Aebischer. 2015. ICT for sustainability: An emerging research field. In ICT Innovations for Sustainability, Advances in Intelligent Systems and Computing, Vol 310. Springer, 3--36.Google Scholar
Lorenz M. Hilty and Wolfgang Lohmann. 2011. The five most neglected issues in green IT. CEPIS UPGRADE 12, 4 (2011), 11--15.Google Scholar
M. Shahriar Hossain, Manish Marwah, Amip Shah, Layne T. Watson, and Naren Ramakrishnan. 2014. AutoLCA: A framework for sustainable redesign and assessment of products. ACM Trans. Intell. Syst. Technol. 5, 2 (Apr. 2014), 34:1--34:21. DOI:http://doi.acm.org/10.1145/2505270Google ScholarDigital Library
Hsu-Chieh Hu, Stephen F. Smith, and Rick Goldstein. 2019. Cooperative schedule-driven intersection control with connected and autonomous vehicles. arXiv preprint arXiv:1907.01984 (2019).Google Scholar
Xiaolong Hu, Liangsheng Shi, Jicai Zeng, Jinzhong Yang, Yuanyuan Zha, Yunjun Yao, and Guoliang Cao. 2016. Estimation of actual irrigation amount and its impact on groundwater depletion: A case study in the Hebei Plain, China. J. Hydrol. 543 (2016), 433--449. DOI:https://doi.org/10.1016/j.jhydrol.2016.10.020Google ScholarCross Ref
J. Huckel. 2008. An analysis of new labour’s policy on education for sustainable development with particular reference to socially critical approaches. Environ. Educ. Res. 14, 1 (2008), 65--75.Google ScholarCross Ref
Lynn Hulsey. 2017. “Smart Car” Technology May Make Roads Safer, but Some Fear Data Hacks. Retrieved from http://www.ttnews.com/articles/smart-car-technology-may-make-roads-safer-some-fear-data-hacks.Google Scholar
Winifred L. Ijomah. 2010. The application of remanufacturing in sustainable manufacture. In Proceedings of the Institution of Civil Engineers-Waste and Resource Management, Vol. 163. Thomas Telford Ltd, 157--163.Google ScholarCross Ref
Winifred L. Ijomah, Christopher A. McMahon, Geoffrey P. Hammond, and Stephen T. Newman. 2007. Development of design for remanufacturing guidelines to support sustainable manufacturing. Robot. Comput.-Integ. Manuf. 23, 6 (2007), 712--719.Google ScholarDigital Library
International Intrasoft. 2018. In-Depth Report: Indicators for Sustainable Cities. Technical Report. European Commission DG Environment by the Science Communication Unit, UWE, Bristol. Retrieved from http://ec.europa.eu/science-environment-policy.Google Scholar
Sandy Irani, Sandeep Shukla, and Rajesh Gupta. 2007. Algorithms for power savings. ACM Trans. Alg. 3, 4 (2007), 41. DOI:https://doi.org/10.1145/1290672.1290678Google ScholarDigital Library
IUCN and WWF. 1980. World Conservation Strategy: Living Resource Conservation for Sustainable Development. Gland, Switzerland: IUCN. Retrieved from https://portals.iucn.org/library/efiles/documents/wcs-004.pdf.Google Scholar
Jae-Wan Jang, Myeongjae Jeon, Hyo-Sil Kim, Heeseung Jo, Jin-Soo Kim, and Seungryoul Maeng. 2010. Energy reduction in consolidated servers through memory-aware virtual machine scheduling. IEEE Trans. Comput. 60, 4 (Apr. 2010), 552--564.Google Scholar
Neal Jean, Marshall Burke, Michael Xie, W. Matthew Davis, David B. Lobell, and Stefano Ermon. 2016. Combining satellite imagery and machine learning to predict poverty. Science 353, 6301 (2016), 790--794.Google ScholarCross Ref
William Stanley Jevons. 1865. The Coal Question: An Inquiry Concerning the Progress of the Nation, and the Probable Exhaustion of Our Coal-Mines. Macmillan and Company, London.Google Scholar
Akshay Jindal and Shrisha Rao. 2017. Agent-based modeling and simulation of mosquito-borne disease transmission. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’17). 426--435.Google ScholarDigital Library
Nicola Jones. 2017. How the World Passed a Carbon Threshold and Why It Matters. Retrieved from https://e360.yale.edu/features/how-the-world-passed-a-carbon-threshold-400ppm-and-why-it-matters.Google Scholar
Debarun Kar, Benjamin Ford, Shahrzad Gholami, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, et al. 2017. Cloudy with a chance of poaching: Adversary behavior modeling and forecasting with real-world poaching data. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS’17). International Foundation for Autonomous Agents and Multiagent Systems, 159--167. Retrieved from http://dl.acm.org/citation.cfm?id=3091125.3091153.Google Scholar
Thomas R. Karl and Kevin E. Trenberth. 2003. Modern global climate change. Science 302, 5651 (2003), 1719--1723. DOI:10.1126/science.1090228Google Scholar
Anuj Karpatne, Ankush Khandelwal, Xi Chen, Varun Mithal, James Faghmous, and Vipin Kumar. 2016. Global monitoring of inland water dynamics: State-of-the-art, challenges, and opportunities. In Computational Sustainability. Studies in Computational Intelligence, Vol 645. Springer, Cham, 121--147. DOI:10.1007/978-3-319-31858-5_7Google Scholar
Robert W. Kates. 2011. What kind of a science is sustainability science? Proc. Nat. Acad. Sci. 108, 49 (Dec. 2011), 19449--19450. DOI:10.1073/pnas.1116097108Google ScholarCross Ref
Robert W. Kates, William C. Clark, Robert Corell, J. Michael Hall, Carlo C. Jaeger, Ian Lowe, James J. McCarthy, Hans Joachim Schellnhuber, Bert Bolin, Nancy M. Dickson, et al. 2001. Sustainability science. Science 292, 5517 (Apr. 2001), 641--642. DOI:10.1126/science.1059386Google ScholarCross Ref
Tarandeep Kaur and Inderveer Chana. 2017. GreenSched: An intelligent energy-aware scheduling for deadline-and-budget constrained cloud tasks. Simul. Modell. Pract. Theor. 82 (Nov. 2017), 55--83. DOI:10.1016/j.simpat.2017.11.008Google Scholar
Kristian Kersting, Christian Bauckhage, Mirwaes Wahabzada, Anne-Kathrin Mahlein, Ulrike Steiner, Erich-Christian Oerke, Christoph Römer, and Lutz Plümer. 2016. Feeding the world with big data: Uncovering spectral characteristics and dynamics of stressed plants. In Computational Sustainability. Studies in Computational Intelligence, Vol. 645. Springer, Cham, 99--120. DOI:https://doi.org/10.1007/978-3-319-31858-5_6Google Scholar
Madhu Khanna and Cameron Speir. 2013. Motivations for proactive environmental management. Sustainability 5, 6 (2013), 2664--2692. DOI:https://doi.org/10.3390/su5062664Google ScholarCross Ref
Himanshu Khurana, Mark Hadley, Ning Lu, and Deborah A. Frincke. 2010. Smart-grid security issues. IEEE Sec. Priv. 8, 1 (Mar. 2010), 81--85.Google ScholarDigital Library
Rob Kitchin. 2014. The real-time city? Big data and smart urbanism. GeoJournal 79, 1 (2014), 1--14.Google ScholarCross Ref
Rudolf Klein, Patricia Day, and Sharon Redmayne. 1996. Managing Scarcity: Priority Setting and Rationing in the National Health Service (State of Health). Open University Press.Google Scholar
J. Zico Kolter. 2012. Future Directions in Sustainable Energy. Retrieved from http://www.cs.cmu.edu/ zkolter/course/15-830-f12/se_directions.pdf.Google Scholar
Leonard F. Konikow. 2015. Long-term groundwater depletion in the United States. Groundwater 53, 1 (Jan./Feb. 2015), 2--9. DOI:https://doi.org/10.1111/gwat.12306Google ScholarCross Ref
Andreas Krause, Daniel Golovin, and Sarah J. Converse. 2014. Sequential decision making in computational sustainability through adaptive submodularity. AI Mag. 35 (June 2014), 8--18.Google Scholar
Petra M. Kuhnert, Tara G. Martin, and Shane P. Griffiths. 2010. A guide to eliciting and using expert knowledge in Bayesian ecological models. Ecol. Lett. 13, 7 (2010), 900--914.Google ScholarCross Ref
Chamil Kulatunga, Kriti Bhargava, Dixon Vimalajeewa, and Stepan Ivanov. 2017. Cooperative in-network computation in energy harvesting device clouds. Sustain. Comput. Inform. Syst. 16 (Dec. 2017), 106--116.Google Scholar
Julian Kunkel and Manuel F. Dolz. 2018. Understanding hardware and software metrics with respect to power consumption. Sustain. Comput. Inform. Syst. 17 (Mar. 2018), 43--54. DOI:10.1016/j.suscom.2017.10.016Google Scholar
Michael D. LaGrega, Phillip L. Buckingham, and Jeffrey C. Evans. 2010. Hazardous Waste Management (reissue ed.). Waveland Press Inc.Google Scholar
Rattan Lal. 2004. Soil carbon sequestration impacts on global climate change and food security. Science 304, 5677 (2004), 1623--1627. DOI:https://doi.org/10.1126/science.1097396Google Scholar
Joleah B. Lamb, Bette L. Willis, Evan A. Fiorenza, Courtney S. Couch, Robert Howard, Douglas N. Rader, James D. True, Lisa A. Kelly, Awaludinnoer Ahmad, Jamaluddin Jompa, et al. 2018. Plastic waste associated with disease on coral reefs. Science 359, 6374 (2018), 460--462. DOI:10.1126/science.aar3320Google Scholar
R. H. Lasseter and P. Paigi. 2004. Microgrid: A conceptual solution. In Proceedings of the IEEE 35th Annual Power Electronics Specialists Conference (PESC’04), Vol. 6. IEEE, 4285--4290.Google Scholar
Jörg Lässig. 2016. Sustainable development and computing—An introduction. In Computational Sustainability. Studies in Computational Intelligence, Vol. 645. Springer, Cham, 1--12.Google Scholar
Jörg Lässig, Kristian Kersting, and Katharina Morik. 2016. Computational Sustainability. Studies in Computational Intelligence, Vol. 645. Springer, Cham.Google Scholar
Chandrashekhar Lavania, Shrisha Rao, and Eswaran Subrahmanian. 2012. Reducing variation in solar energy supply through frequency domain analysis. IEEE Syst. J. 6, 2 (June 2012), 196--204. DOI:10.1109/JSYST.2011.2162796Google ScholarCross Ref
Etienne Le Sueur and Gernot Heiser. 2010. Dynamic voltage and frequency scaling: The laws of diminishing returns. In Proceedings of the International Conference on Power Aware Computing and Systems (HotPower’10). 1--8.Google Scholar
H. M. Lee, R. Gay, W. F. Lu, and B. Song. 2006. The framework of information sharing in end-of-life for sustainable product development. In Proceedings of the 4th IEEE International Conference on Industrial Informatics. 73--78. DOI:https://doi.org/10.1109/INDIN.2006.275720Google Scholar
Laurent Lefèvre and Jean-Marc Pierson. 2018. Introduction to Special Issue on Sustainable Computing for Ultrascale Computing. Retrieved from https://www.sciencedirect.com/science/article/pii/S2210537918300465.Google Scholar
Nancy G. Leveson. 1995. Safeware: System Safety and Computers: A Guide to Preventing Accidents and Losses Caused By Technology. Addison-Wesley.Google Scholar
Qilin Li and Mingtian Zhou. 2011. The survey and future evolution of green computing. In Proceedings of the IEEE/ACM International Conference on Green Computing and Communications. IEEE Computer Society, 230--233.Google ScholarDigital Library
Larry Lohmann, Niclas Hällström, Robert Österbergh, and Olle Nordberg. 2006. Carbon Trading: A Critical Conversation on Climate Change, Privatisation and Power. Dag Hammarskjöld Foundation, Uppsala, Sweden.Google Scholar
Xiangyong Lu, Kaoru Ota, Mianxiong Dong, Chen Yu, and Hai Jin. 2017. Predicting transportation carbon emission with urban big data. IEEE Trans. Sustain. Comput. 2, 4 (July 2017), 333--344.Google ScholarCross Ref
Shuo Ma, Yu Zheng, and Ouri Wolfson. 2014. Real-time city-scale taxi ridesharing. IEEE Trans. Knowl. Data Eng. 27, 7 (2014), 1782--1795.Google ScholarCross Ref
Alessio Maffei, Seshadhri Srinivasan, Daniela Meola, Giovanni Palmieri, Luigi Iannelli, Øystein Hov Holhjem, Giancarlo Marafioti, Geir Mathisen, and Luigi Glielmo. 2017. A cyber-physical systems approach for implementing the receding horizon optimal power flow in smart grids. IEEE Trans. Sustain Comput. 3, 2 (Apr.--June 2017), 98--111. DOI:https://doi.org/10.1109/TSUSC.2017.2737144Google Scholar
Natalie M. Mahowald, James T. Randerson, Keith Lindsay, Ernesto Munoz, Scott C. Doney, Peter Lawrence, Sarah Schlunegger, Daniel S. Ward, David Lawrence, and Forrest M. Hoffman. 2017a. Interactions between land use change and carbon cycle feedbacks. Global Biogeochem. Cycles 31, 1 (2017), 96--113. DOI:10.1002/2016GB005374Google ScholarCross Ref
Natalie M. Mahowald, Rachel Scanza, Janice Brahney, Christine L. Goodale, Peter G. Hess, J. Keith Moore, and Jason Neff. 2017b. Aerosol deposition impacts on land and ocean carbon cycles. Curr. Clim. Change Rep. 3, 1 (Mar. 2017), 16--31. DOI:10.1007/s40641-017-0056-zGoogle ScholarCross Ref
Indrani Maity and Shrisha Rao. 2010. Simulation and pricing mechanism analysis of a solar-powered electrical microgrid. IEEE Syst. J. 4, 3 (Sep. 2010), 275--284. DOI:https://doi.org/10.1109/JSYST.2010.2059110Google ScholarCross Ref
Mohammad-Hossein Malekloo, Nadjia Kara, and May El Barachi. 2018. An energy-efficient and SLA compliant approach for resource allocation and consolidation in cloud computing environments. Sustain. Comput. Inform. Syst. 17 (Mar. 2018), 9--24. DOI:10.1016/j.suscom.2018.02.001Google Scholar
Helena Mälkki and Kari Alanne. 2017. An overview of life cycle assessment (LCA) and research--based teaching in renewable and sustainable energy education. Renew. Sustain. Energy Rev. 69 (2017), 218--231.Google ScholarCross Ref
Jens Malmodin and Dag Lundén. 2018. The energy and carbon footprint of the global ICT and E8M sectors 2010--2015. Sustainability 10, 9 (Aug. 2018). DOI:https://doi.org/10.3390/su10093027Google ScholarCross Ref
Helen Mayfield, Carl Smith, Marcus Gallagher, and Marc Hockings. 2017. Use of freely available datasets and machine learning methods in predicting deforestation. Environ. Modell. Softw. 87 (Jan. 2017), 17--28. DOI:https://doi.org/10.1016/j.envsoft.2016.10.006Google Scholar
N. McCullar, B. Blackmore, A. Goh, G. King, N. Kowalski, and M. Rau. 2004. Bridging the information gap: Material tracking and consumer labels to encourage sustainable computing. In Proceedings of the IEEE International Symposium on Electronics and the Environment. 275--280. DOI:https://doi.org/10.1109/ISEE.2004.1299729Google Scholar
Patrick McDaniel and Stephen McLaughlin. 2009. Security and privacy challenges in the smart grid. IEEE Sec. Priv. 7, 3 (May 2009), 75--77. DOI:10.1109/MSP.2009.76Google ScholarDigital Library
Matthias S. Meier, Franziska Stoessel, Niels Jungbluth, Ronnie Juraske, Christian Schader, and Matthias Stolze. 2015. Environmental impacts of organic and conventional agricultural products—Are the differences captured by life cycle assessment? J. Environ. Manag. 149 (2015), 193--208.Google ScholarCross Ref
Cory Merow, Matthew J. Smith, and John A. Silander Jr. 2013. A practical guide to MaxEnt for modeling species’ distributions: What it does, and why inputs and settings matter. Ecography 36, 10 (2013), 1058--1069.Google ScholarCross Ref
Microsoft. 2018. Microsoft 2018 Corporate Social Responsibility report. Retrieved from https://query.prod.cms.rt.microsoft.com/cms/api/am/binary/RE2IDuR.Google Scholar
Wang Mingrong, Wang Mingxi, and Lang Lihua. 2017. Reconsidering carbon permits auction mechanism: An efficient dynamic model. World Econ. 40, 8 (Aug. 2017), 1624--1645. DOI:https://doi.org/10.1111/twec.12436Google Scholar
Julio C. Rivera, Bernabé Hernandis, Sheila Cordeiro, José R. González, and Omar Miranda. 2015. An understanding of lifetime optimisation through sustainable strategies and intangibility in product and services. In Product Lifetimes and The Environment (PLATE'15) Conference. Nottingham Trent University. Retrieved from https://www.plateconference.org/understanding-lifetime-optimisation-sustainable-strategies-intangibility-product-services/.Google Scholar
Mina Mirhosseini, Fatemeh Barani, and Hossein Nezamabadi-pour. 2017. Design optimization of wireless sensor networks in precision agriculture using improved BQIGSA. Sustain. Comput. Inform. Syst. 16 (Dec. 2017), 38--47. DOI:10.1016/j.suscom.2017.08.006Google Scholar
Aditya Mishra, David Irwin, Prashant Shenoy, Jim Kurose, and Ting Zhu. 2013. GreenCharge: Managing renewable energy in smart buildings. IEEE J. Sel. Areas Commun. 31, 7 (July 2013), 1281--1293. DOI:10.1109/JSAC.2013.130711Google ScholarCross Ref
Krishna B. Misra. 2008. Sustainability: Motivation and pathways for implementation. In Handbook of Performability Engineering. Springer, 843--856.Google ScholarCross Ref
Sparsh Mittal. 2012. A survey of architectural techniques for DRAM power management. Int. J. High Perf. Syst. Archit. 4, 2 (Dec. 2012), 110--119.Google ScholarDigital Library
Sparsh Mittal. 2014. Power management techniques for data centers: A survey. arXiv:1404.6681 (April 2014).Google Scholar
Santiago Molina, Angela K. Fuller, Dana J. Morin, and J. Andrew Royle. 2017. Use of spatial capture—Recapture to estimate density of Andean bears in Northern Ecuador. Ursus 28, 1 (2017), 117--126.Google ScholarCross Ref
Andres Molina-Markham, George Danezis, Kevin Fu, Prashant J. Shenoy, and David E. Irwin. 2011. Designing privacy—Preserving smart meters with low-cost microcontrollers. In Proceedings of the International Conference on Financial Cryptography and Data Security. 239--253.Google Scholar
M. Momtazpour, M. C. Bozchalui, N. Ramakrishnan, and R. Sharma. 2016. Installing electric vehicle charging stations city-scale: How many and where? In Computational Sustainability. Studies in Computational Intelligence, Vol 645. Springer, Cham, 149--170. DOI:10.1007/978-3-319-31858-5_8Google Scholar
Hemanta Kumar Mondal, Sri Harsha Gade, Shashwat Kaushik, and Sujay Deb. 2017a. Adaptive multi-voltage scaling with utilization prediction for energy-efficient wireless NoC. 2, 4 (Aug. 2017), 382--395. DOI:10.1109/TSUSC.2017.2742219Google Scholar
Hemanta Kumar Mondal, Sri Harsha Gade, Raghav Kishore, and Sujay Deb. 2017b. P2NoC: Power- and performance-aware NoC architectures for sustainable computing. Sustain. Comput. Inform. Syst. 16 (Dec. 2017), 25--37.Google Scholar
Ivan Montiel. 2008. Corporate social responsibility and corporate sustainability: Separate pasts, common futures. Organiz. Environ. 21, 3 (2008), 245--269.Google ScholarCross Ref
Dana J. Morin, Angela K. Fuller, J. Andrew Royle, and Chris Sutherland. 2017. Model-based estimators of density and connectivity to inform conservation of spatially structured populations. Ecosphere 8, 1 (2017). DOI:https://doi.org/10.1002/ecs2.1623Google Scholar
Dustin Mulvaney. 2014. Solar’s green dilemma. Must cheaper photovoltaics come with a higher environmental price tag?IEEE Spectr. (Sep. 2014), 30--33. Retrieved from http://spectrum.ieee.org/green-tech/solar/solar-energy-isnt-always-as-green-as-you-think.Google Scholar
Amrutha Muralidharan, Horia A. Maior, and Shrisha Rao. 2018. A self-governing and decentralized network of smart objects to share electrical power autonomously. In Sustainable Cloud and Energy Services: Principles and Practice, Wilson Rivera (Ed.). Springer International Publishing, Cham, 25--48. DOI:https://doi.org/10.1007/978-3-319-62238-5_2Google Scholar
S. Murugesan. 2008. Harnessing green IT: Principles and practices. IT Professional 10, 1 (2008), 24--32.Google ScholarDigital Library
Norman Myers. 1988. Tropical deforestation and remote sensing. Forest Ecol. Manag. 23, 2--3 (Feb. 1988), 215--225. DOI:https://doi.org/10.1016/0378-1127(88)90083-7Google ScholarCross Ref
A. Nagurney and M. Yu. 2011. Sustainable fashion supply chain management under oligopolistic competition and brand differentiation. Int. J. Prod. Econ. Spec. Iss. Green Manuf. Distrib. Fash. Appar. Industr. 135, 2 (2011), 532--540.Google Scholar
Stefan Naumann, Markus Dick, Eva Kern, and Timo Johann. 2011. The GREENSOFT model: A reference model for green and sustainable software and its engineering. Sustain. Comput. Inform. Syst. 1, 4 (Dec. 2011), 294--304. DOI:10.1016/j.suscom.2011.06.004Google ScholarCross Ref
Robert J. Nicholls, Frank M. J. Hoozemans, and Marcel Marchand. 1999. Increasing flood risk and wetland losses due to global sea-level rise: Regional and global analyses. Global Environ. Change 9 (1999), 69--87.Google ScholarCross Ref
Martin A. Nuñez, Anibal Pauchard, and Anthony Ricciardi. 2020. Invasion science and the global spread of SARS-CoV-2. Trends. Ecol. Evol. 35, 8 (2020), 642--645. DOI:https://doi.org/10.1016/j.tree.2020.05.004Google ScholarCross Ref
Marc Orlitzky, Donald S. Siegel, and David A. Waldman. 2011. Strategic corporate social responsibility and environmental sustainability. Bus. Soc. 50, 1 (2011), 6--27.Google ScholarCross Ref
Claudia Pahl-Wostl. 2007. Transitions towards adaptive management of water facing climate and global change. Water Res. Manag. 21, 1 (2007), 49--62.Google ScholarCross Ref
Thanos Papadopoulos, Angappa Gunasekaran, Rameshwar Dubey, Nezih Altay, Stephen J. Childe, and Samuel Fosso-Wamba. 2016. The role of big data in explaining disaster resilience in supply chains for sustainability. J. Clean. Prod. 142 (2016), 1108--1118. DOI:10.1016/j.jclepro.2016.03.059Google ScholarCross Ref
Jong Hyuk Park and Han-Chieh Chao. 2017. Advanced IT-based future sustainable computing. Sustainability 9, 5 (May 2017). DOI:10.3390/su9050757Google Scholar
Simon Parsons, Juan A. Rodriguez-Aguilar, and Mark Klein. 2011. Auctions and bidding: A guide for computer scientists. Comput. Surv. 43, 2 (Jan. 2011). DOI:10.1145/1883612.1883617Google ScholarDigital Library
Debprakash Patnaik, Manish Marwah, Ratnesh Sharma, and Naren Ramakrishnan. 2009. Sustainable operation and management of data center chillers using temporal data mining. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’09). ACM, 1305--1314.Google ScholarDigital Library
J. Jeffrey Peirce, P. Aarne Vesilind, and Ruth Weiner. 1998. Environmental Pollution and Control. Butterworth-Heinemann.Google Scholar
Steven Pelley, David Meisner, Thomas F. Wenisch, and James W. VanGilder. 2009. Understanding and abstracting total data center power. In Proceedings of the Workshop on Energy-Efficient Design (WEED’09), Vol. 11.Google Scholar
Birgit Penzenstadler, Ankita Raturi, Debra Richardson, and Bill Tomlinson. 2014. Safety, security, now sustainability: The non-functional requirement for the 21st century. IEEE Softw. 31, 3 (2014), 40--47.Google ScholarCross Ref
Steven J. Phillips and Miroslav Dudík. 2008. Modeling of species distributions with Maxent: New extensions and a comprehensive evaluation. Ecography 31, 2 (2008), 161--175.Google ScholarCross Ref
Jean-Marc Pierson. 2015. Large Scale Distributed Systems and Energy Efficiency: A Holistic View. John Wiley 8 Sons.Google Scholar
Michael Pinedo. 2009. Planning and Scheduling in Manufacturing and Services (2nd ed.). Springer.Google Scholar
Michael L. Pinedo. 2012. Scheduling: Theory, Algorithms, and Systems (4th ed.). Springer.Google ScholarCross Ref
John M. Polimeni. 2012. The Jevon’s Paradox and the Myth of Resource Efficiency Improvements. Earthscan.Google Scholar
Kathleen L. Prudic, Kent P. McFarland, Jeffrey C. Oliver, Rebecca A. Hutchinson, Elizabeth C. Long, Jeremy T. Kerr, and Maxim Larrivée. 2017. eButterfly: Leveraging massive online citizen science for butterfly conservation. Insects 8, 2 (2017), 53.Google ScholarCross Ref
Reid Pryzant, Stefano Ermon, and David Lobell. 2017. Monitoring Ethiopian wheat fungus with satellite imagery and deep feature learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW’17). IEEE, 1524--1532. DOI:https://doi.org/10.1109/CVPRW.2017.196Google ScholarCross Ref
John Alexander Quinn, Kevin Leyton-Brown, and Ernest Mwebaze. 2011. Modeling and monitoring crop disease in developing countries. In Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI’11).Google Scholar
Naren Ramakrishnan, Manish Marwah, Amip Shah, Debprakash Patnaik, M. Hossain, Naren Sundaravaradan, and Chandrakant Patel. 2012. Data mining solutions for sustainability problems. IEEE Potent. 31, 6 (Nov. 2012), 28--34.Google ScholarCross Ref
Sarvapali D. Ramchurn, Perukrishnen Vytelingum, Alex Rogers, and Nicholas R. Jennings. 2012. Putting the “Smarts” into the smart grid: A grand challenge for artificial intelligence. Commun. ACM 55, 4 (Apr. 2012), 86--97. DOI:10.1145/2133806.2133825Google ScholarDigital Library
Thomas Rauber, Gudula Rünger, and Matthias Stachowski. 2018. Performance and energy metrics for multi-threaded applications on DVFS processors. Sustain. Comput. Inform. Syst. 17 (Mar. 2018), 55--68.Google Scholar
D. A. Relman, M. A. Hamburg, E. R. Choffnes, and A. Mack, Eds. 2008. Global Climate Change and Extreme Weather Events: Understanding the Contributions to Infectious Disease Emergence: Workshop Summary. The National Academies Press, Washington, DC. Retrieved from https://www.nap.edu/catalog/12435/global-climate-change-and-extreme-weather-events-understanding-the-contributions.Google Scholar
Mark D. Reynolds, Brian L. Sullivan, Eric Hallstein, Sandra Matsumoto, Steve Kelling, Matthew Merrifield, Daniel Fink, Alison Johnston, Wesley M. Hochachka, Nicholas E. Bruns, et al. 2017. Dynamic conservation for migratory species. Sci. Adv. 3, 8 (2017). DOI:10.1126/sciadv.1700707Google Scholar
Emmanouil S. Rigas, Sarvapali D. Ramchurn, and Nick Bassiliades. 2014. Managing electric vehicles in the smart grid using artificial intelligence: A survey. IEEE Trans. Intell. Transport. Syst. 16, 4 (2014), 1619--1635.Google ScholarCross Ref
Caleb Robinson, Bistra Dilkina, Jeffrey Hubbs, Wenwen Zhang, Subhrajit Guhathakurta, Marilyn A. Brown, and Ram M. Pendyala. 2017. Machine learning approaches for estimating commercial building energy consumption. Appl. Energy 208 (Dec. 2017), 889--904.Google Scholar
Sandra I. Rodriguez, Matthew S. Roman, Samantha C. Sturhahn, and Elizabeth H. Terry. 2002. Sustainability Assessment and Reporting for the University of Michigan’s Ann Arbor Campus. Center for Sustainable Systems, Report No. CSS02-04. University of Michigan, Ann Arbor, Michigan.Google Scholar
David Rojas-Rueda. 2020. New transport technologies and health. In Transportation and Health: Tools, Technologies, Policies, and Developments, Mark J. Nieuwenhuijsen and Haneen Khreis (Eds.). Elsevier, 225--237. DOI:https://doi.org/10.1016/B978-0-12-819136-1.00009-7Google Scholar
Daniel H. Rothman. 2015. The Earth’s carbon cycle: A mathematical perspective. Bull. Amer. Math. Soc. 52, 1 (Jan. 2015), 47--64. DOI:https://doi.org/10.1090/S0273-0979-2014-01471-5Google Scholar
Cynthia Rudin, David Waltz, Roger N. Anderson, Albert Boulanger, Ansaf Salleb-Aouissi, Maggie Chow, Haimonti Dutta, Philip N. Gross, Bert Huang, Steve Ierome, et al. 2012. Machine learning for the New York City power grid. IEEE Trans. Pattern Anal. Mach. Intell. 34, 2 (2012), 328--345.Google ScholarDigital Library
Martin Sachenbacher, Martin Leucker, Andreas Artmeier, and Julian Haselmayr. 2011. Efficient energy-optimal routing for electric vehicles. In Proceedings of the AAAI Conference on Artificial Intelligence, Special Track on Computational Sustainability. 1402--1407.Google Scholar
Kali E. Sawaya, Leif G. Olmanson, Nathan J. Heinert, Patrick L. Brezonik, and Marvin E. Bauer. 2003. Extending satellite remote sensing to local scales: Land and water resource monitoring using high-resolution imagery. Rem. Sens. Environ. 88, 1-2 (2003), 144--156.Google ScholarCross Ref
R. Schainker, P. Miller, W. Dubbelday, P. Hirsch, and Guorui Zhang. 2006. Real-time dynamic security assessment: Fast simulation and modeling applied to emergency outage security of the electric grid. IEEE Power Energy Mag. 4 (Apr. 2006), 51--58.Google Scholar
Hartmut Schmeck. 2012. Challenges for ICT in Smart Energy and Electric Mobility. Retrieved from http://www.computational-sustainability.org/compsust12/slides/Schmeck.pdf.Google Scholar
René Schönfelder and Martin Leucker. 2012. State-based routing for computational sustainability. In Proceedings of the 3rd International Conference on Computational Sustainability (CompSust’12).Google Scholar
Abigail J. Sellen and Richard H. R. Harper. 2003. The Myth of the Paperless Office. The MIT Press.Google ScholarDigital Library
T. P. Shabeera, S. D. Madhu Kumar, Sameera M. Salam, and K. Murali Krishnan. 2017. Optimizing VM allocation and data placement for data-intensive applications in cloud using ACO metaheuristic algorithm. Eng. Sci. Technol. Int. J. 20, 2 (Apr. 2017), 616--628. DOI:10.1016/j.jestch.2016.11.006Google Scholar
Mihir Shah and Himanshu Kulkarni. 2015. Urban water systems in India: Typologies and hypotheses. Econ. Polit. Weekly L, 30 (July 2015). Retrieved from http://www.indiawaterportal.org/sites/indiawaterportal.org/files/urban_water_systems_in_india_typologies_and_hypothesis_epw_2015.pdf.Google Scholar
Daniel Sheldon, Bistra Dilkina, Adam N. Elmachtoub, Ryan Finseth, Ashish Sabharwal, Jon Conrad, Carla P. Gomes, David Shmoys, William Allen, Ole Amundsen, et al. 2012. Maximizing the spread of cascades using network design. arXiv:1203.3514 (2012).Google Scholar
Roger A. Sheldon. 2014. Green and sustainable manufacture of chemicals from biomass: State of the art. Green Chem. 16, 3 (2014), 950--963.Google ScholarCross Ref
Bhagya Nathali Silva, Murad Khan, and Kijun Han. 2018. Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities. Sustain. Cities Soc. 38 (Apr. 2018), 697--713.Google Scholar
Stefan G. H. Simis, Steef W. M. Peters, and Herman J. Gons. 2005. Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water. Limnol. Oceanog. 50, 1 (2005), 237--245.Google ScholarCross Ref
Rahul Singh, David Irwin, Prashant Shenoy, and K. K. Ramakrishnan. 2013. Yank: Enabling green data centers to pull the plug. In Proceedings of the Symposium on Networked Systems Design and Implementation (NSDI’13). 143--156.Google Scholar
Johan Six, Stephen M. Ogle, F. Jay Breidt, Rich T. Conant, Arvin R. Mosier, and Keith Paustian. 2004. The potential to mitigate global warming with no-tillage management is only realized when practised in the long term. Glob. Change Biol. 10, 2 (2004), 155--160.Google ScholarCross Ref
Brad Smith. 2017. AI for Earth can be a game-changer for our planet. Retrieved from https://blogs.microsoft.com/on-the-issues/2017/12/11/ai-for-earth-can-be-a-game-changer-for-our-planet/.Google Scholar
Malin Song, Ling Cen, Zhixia Zheng, Ron Fisher, Xi Liang, Yutao Wang, and Donald Huisingh. 2016. How would big data support societal development and environmental sustainability? Insights and practices. J. Clean. Prod. 142 (2016), 489--500.Google ScholarCross Ref
Clive L. Spash. 2010. The brave new world of carbon trading. New Polit. Econ. 15, 2 (2010), 169--195.Google ScholarCross Ref
Nanda Kishore Sreenivas and Shrisha Rao. 2019. Egocentric bias and doubt in cognitive agents. In Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’19).Google ScholarDigital Library
Robert N. Stavins. 2003. Experience with market-based environmental policy instruments. In Handbook of Environmental Economics. Vol. 1. Elsevier, 355--435.Google Scholar
Thanos G. Stavropoulos, Efstratios Kontopoulos, Nick Bassiliades, John Argyriou, Antonis Bikakis, Dimitris Vrakas, and Ioannis Vlahavas. 2015. Rule-based approaches for energy savings in an ambient intelligence environment. Pervas. Mob. Comput. 19 (2015), 1--23.Google ScholarDigital Library
M. Stolpe, H. Blom, and K. Morik. 2016. Sustainable industrial processes by embedded real-time quality prediction. In Computational Sustainability. Studies in Computational Intelligence, Vol 645. Springer, Cham, Springer, 201--243. DOI:10.1007/978-3-319-31858-5_10Google Scholar
Brian Stone Jr., Adam C. Mednick, Tracey Holloway, and Scott N. Spak. 2009. Mobile source CO₂ mitigation through smart growth development and vehicle fleet hybridization. Environ. Sci. Technol. 43, 6 (2009), 1704--1710. DOI:10.1021/es8021655Google ScholarCross Ref
Brian L. Sullivan, Jocelyn L. Aycrigg, Jessie H. Barry, Rick E. Bonney, Nicholas Bruns, Caren B. Cooper, Theo Damoulas, André A. Dhondt, Tom Dietterich, Andrew Farnsworth, et al. 2014. The eBird enterprise: An integrated approach to development and application of citizen science. Biol. Conserv. 169 (Jan. 2014), 31--40.Google Scholar
Brian L. Sullivan, Christopher L. Wood, Marshall J. Iliff, Rick E. Bonney, Daniel Fink, and Steve Kelling. 2009. eBird: A citizen-based bird observation network in the biological sciences. Biol. Conserv. 142, 10 (2009), 2282--2292.Google ScholarCross Ref
Piling Sun, Yueqing Xu, Zhonglei Yu, Qingguo Liu, Baopeng Xie, and Jia Liu. 2016b. Scenario simulation and landscape pattern dynamic changes of land use in the poverty belt around Beijing and Tianjin: A case study of Zhangjiakou city, Hebei Province. J. Geog. Sci. 26, 3 (2016), 272--296. DOI:10.1007/s11442-016-1268-1Google ScholarCross Ref
Yunchuan Sun, Houbing Song, Antonio J. Jara, and Rongfang Bie. 2016a. Internet of Things and big data analytics for smart and connected communities. IEEE Access 4 (2016), 766--773.Google ScholarCross Ref
V. Todorov and D. Marinova. 2011. Modelling sustainability. Math. Comput. Simul. 81, 7 (2011), 1397--1408.Google ScholarDigital Library
Brian Tokar. 1997. Earth for Sale: Reclaiming Ecology in the Age of Corporate Greenwash. South End Press, Boston.Google Scholar
N. A. Treiber, J. Heinermann, and O. Kramer. 2016. Wind power prediction with machine learning. In Computational Sustainability. Studies in Computational Intelligence, Vol 645. Springer, Cham. DOI:10.1007/978-3-319-31858-5_2Google Scholar
Ashutosh Trivedi and Shrisha Rao. 2018. Agent-based modeling of emergency evacuations considering human panic behavior. IEEE Trans. Comput. Soc. Syst. 5, 1 (Mar. 2018), 277--288. DOI:https://doi.org/10.1109/TCSS.2017.2783332Google ScholarCross Ref
B. L. Turner and Jeremy A. Sabloff. 2012. Classic Period collapse of the Central Maya Lowlands: Insights about human environment relationships for sustainability. Proc. Nat. Acad. Sci. (2012). DOI:https://doi.org/10.1073/pnas.1210106109Google Scholar
United Nations Department of Economic and Social Affairs. 2006. Sustainable Consumption and Production: Energy and Industry. Retrieved from http://www.un.org/esa/sustdev/csd/csd14/documents/bp3_2006.pdf.Google Scholar
United Nations Department of Economic and Social Affairs. 2007. Sustainable Consumption and Production: Promoting Climate-friendly Household Consumption Patterns. Retrieved from http://www.un.org/esa/sustdev/publications/household_consumption.pdf.Google Scholar
United Nations Sustainable Development. 2015. Hunger and Food Security. Retrieved from https://www.un.org/sustainabledevelopment/hunger/.Google Scholar
Konstantina Valogianni, Wolfgang Ketter, John Collins, and Dmitry Zhdanov. 2014. Effective management of electric vehicle storage using smart charging. In Proceedings of the 28th AAAI Conference on Artificial Intelligence.Google Scholar
Guido R. Van der Werf, Douglas C. Morton, Ruth S. DeFries, Jos G. J. Olivier, Prasad S. Kasibhatla, Robert B. Jackson, G. James Collatz, and James T. Randerson. 2009. CO₂ emissions from forest loss. Nat. Geosci. 2, 11 (2009), 737.Google ScholarCross Ref
Vasanth Venkatachalam and Michael Franz. 2005. Power reduction techniques for microprocessor systems. Comput. Surv. 37, 3 (Sep. 2005), 195--237. DOI:10.1145/1108956.1108957Google ScholarDigital Library
Colin C. Venters, Norbert Seyff, Christoph Becker, Stefanie Betz, Ruzanna Chitchyan, Leticia Duboc, Dan McIntyre, and Birgit Penzenstadler. 2017. Characterising sustainability requirements: A new species red herring or just an odd fish? In Proceedings of the IEEE/ACM 39th International Conference on Software Engineering: Software Engineering in Society Track (ICSE-SEIS’17). IEEE, 3--12.Google ScholarDigital Library
Danny Verboekend and Javier Pérez-Ramírez. 2014. Towards a sustainable manufacture of hierarchical zeolites. ChemSusChem 7, 3 (2014), 753--764.Google ScholarCross Ref
M. Wackernagel and W. E. Rees. 1996. Our Ecological Footprint: Reducing Human Impact on the Earth. Gabriola Press New Society Publishing, B.C.Google Scholar
David Wagman. 2018. This power plant runs on CO₂. IEEE Spectr. 77 (June 2018), 27--29.Google Scholar
Matthew A. Waller and Stanley E. Fawcett. 2013. Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management. J. Bus. Logist. 34, 2 (2013), 77--84.Google ScholarCross Ref
Kun Wang, Xiaoxuan Hu, Huining Li, Peng Li, Deze Zeng, and Song Guo. 2017. A survey on energy Internet communications for sustainability. IEEE Trans. Sustain. Comput. 2, 3 (2017), 231--254.Google ScholarCross Ref
D. Patrick Webb, David A. Hutt, David C. Whalley, and Paul J. Palmer. 2008. A substrateless process for sustainable manufacture of electronic assemblies. In Proceedings of the 2nd Electronics System-Integration Technology Conference (ESTC’08). IEEE, 511--516.Google Scholar
Lai Wei, Wei Tian, Elisabete A. Silva, Ruchi Choudhary, QingXin Meng, and Song Yang. 2015. Comparative study on machine learning for urban building energy analysis. In Proceedings of the 9th International Symposium on Heating, Ventilation and Air Conditioning (ISHVAC) joint with the 3rd International Conference on Building Energy and Environment (COBEE) DOI:10.1016/j.proeng.2015.08.1070Google ScholarCross Ref
Caitlin E. Werrell and Francesco Femia (Eds.). 2017. Epicenters of climate and security: The new geostrategic landscape of the Anthropocene. Center Clim. Sec. (June 2017). Retrieved from https://climateandsecurity.files.wordpress.com/2017/06/epicenters-of-climate-and-security_the-new-geostrategic-landscape-of-the-anthropocene_2017_06_091.pdf.Google Scholar
Jörg Wicker, Kathrin Fenner, and Stefan Kramer. 2016. A hybrid machine learning and knowledge based approach to limit combinatorial explosion in biodegradation prediction. In Computational Sustainability. Studies in Computational Intelligence, Vol. 645. Springer, Cham, 75--97. DOI:10.1007/978-3-319-31858-5_5Google Scholar
Thomas Wiedmann and Jan Minx. 2008. A definition of “carbon footprint.” Ecol. Econ. Res. Trends 1 (2008), 1--11.Google Scholar
Bryan Wilder, Sze-Chuan Suen, and Milind Tambe. 2018. Preventing infectious disease in dynamic populations under uncertainty. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence. Retrieved from https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16714/15766.Google Scholar
Eric Williams. 2011. Environmental effects of information and communications technologies. Nature 479, 7373 (2011), 354.Google Scholar
Björn Wolff, Elke Lorenz, and Oliver Kramer. 2016. Statistical learning for short-term photovoltaic power predictions. In Computational Sustainability. Studies in Computational Intelligence, Vol. 645. Springer, Cham, 31--45. DOI:10.1007/978-3-319-31858-5_3Google Scholar
Warren W. Wood and David W. Hyndman. 2017. Groundwater depletion: A significant unreported source of atmospheric carbon dioxide. Earth’s Fut. 5, 11 (Nov. 2017). DOI:https://doi.org/10.1002/2017EF000586Google Scholar
Xiaojian Wu, Akshat Kumar, Daniel Sheldon, and Shlomo Zilberstein. 2016. Robust optimization for tree-structured stochastic network design. arXiv:1612.00104 (2016).Google Scholar
Zhen Xiao, Weijia Song, and Qi Chen. 2013. Dynamic resource allocation using virtual machines for cloud computing environment. IEEE Trans. Parallel Distrib. Syst. 24, 6 (June 2013), 1107--1117.Google ScholarDigital Library
Michael Xie, Neal Jean, Marshall Burke, David Lobell, and Stefano Ermon. 2016. Transfer learning from deep features for remote sensing and poverty mapping. In Proceedings of the 30th AAAI Conference on Artificial Intelligence arXiv:1510.00098 (2016).Google Scholar
Yexiang Xue, Xiaojian Wu, Dana Morin, Bistra Dilkina, Angela Fuller, J. Andrew Royle, and Carla P. Gomes. 2017. Dynamic optimization of landscape connectivity embedding spatial capture--recapture information. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI’17). 4552--4558.Google Scholar
Peng Yang, Randy A. Freeman, Geoffrey J. Gordon, Kevin M. Lynch, Siddhartha S. Srinivasa, and Rahul Sukthankar. 2010. Decentralized estimation and control of graph connectivity for mobile sensor networks. Automatica 46, 2 (2010), 390--396.Google ScholarDigital Library
Jagadeesh B. Yeluripati, Marcel Van Oijen, Martin Wattenbach, A. Neftel, A. Ammann, W. J. Parton, and Pete Smith. 2009. Bayesian calibration as a tool for initialising the carbon pools of dynamic soil models. Soil Biol. Biochem. 41, 12 (2009), 2579--2583.Google ScholarCross Ref
Norman Yoffee. 1979. The decline and rise of Mesopotamian civilization: An ethnoarchaeological perspective on the evolution of social complexity. Amer. Antiq. 44, 1 (Jan. 1979), 5--35. DOI:https://doi.org/10.2307/279187Google ScholarCross Ref
Jiaxuan You, Xiaocheng Li, Melvin Low, David Lobell, and Stefano Ermon. 2017. Deep Gaussian process for crop yield prediction based on remote sensing data. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI’17). Retrieved from https://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14435.Google Scholar
Ting Yu, Nitesh Chawla, and Simeon Simoff. 2013. Computationally Intelligent Data Analysis for Sustainable Development. CRC Press.Google Scholar
Atefe Zakeri, Farzad Dehghanian, Behnam Fahimnia, and Joseph Sarkis. 2015. Carbon pricing versus emissions trading: A supply chain planning perspective. Int. J. Prod. Econ. 164 (2015), 197--205.Google ScholarCross Ref
Qingchen Zhang, Man Lin, Laurence T. Yang, Zhikui Chen, and Peng Li. 2017. Energy-efficient scheduling for real-time systems based on deep Q-learning model. IEEE Trans. Sustain. Comput. 4, 1 (Aug. 2017). DOI:10.1109/TSUSC.2017.2743704Google Scholar
F. Liu Zheng and H.-P. Hsieh. 2013. U-air: When urban air quality inference meets big data. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 1436--1444.Google ScholarDigital Library
Albert Y. Zomaya and Young Choon Lee (Eds.). 2012. Energy-efficient Distributed Computing Systems. Wiley-IEEE Computer Society.Google Scholar

Index Terms

Computational Sustainability: A Socio-technical Perspective

Recommendations

Computational sustainability
IDA'11: Proceedings of the 10th international conference on Advances in intelligent data analysis X

Computational sustainability [1] is a new interdisciplinary research field with the overall goal of developing computational models, methods, and tools to help manage the balance between environmental, economic, and societal needs for sustainable ...
Read More
Feature Information Recognition of Waste Recycling Resource Set Based on Data Mining

Based on data mining, this paper analyzes the development characteristics of waste recycling resources, classifies the characteristics of waste recycling resources, constructs the evaluation level of characteristic information of waste recycling ...
Read More
Decision Analysis to Advance Environmental Sustainability
Decision analysis provides a robust framework for complex decisions related to environmental sustainability and conservation, including for energy and water, fisheries and wildlife management, agriculture, and climate change response. The complexities of ...
Read More

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

Published in
ACM Computing Surveys Volume 53, Issue 5
September 2021
782 pages
ISSN:0360-0300
EISSN:1557-7341
DOI:10.1145/3426973
Editor:
Albert Zomaya
University of Sydney, Austraila
Issue’s Table of Contents
Copyright © 2020 ACM
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Sponsors
In-Cooperation
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
- Published: 28 September 2020
- Accepted: 1 June 2020
- Revised: 1 September 2019
- Received: 1 August 2018
Published in csur Volume 53, Issue 5

Permissions
Request permissions about this article.
Request Permissions

Check for updates
Author Tags
Conservation
renewable resources
smart systems
Qualifiers
- survey
- Research
- Refereed
Conference
Funding Sources
Other Metrics
View Article Metrics

Article Metrics
- 4
  Total Citations
  View Citations
- 603
  Total Downloads
- Downloads (Last 12 months)121
- Downloads (Last 6 weeks)15
Other Metrics
View Author Metrics
Cited By
View all

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format .

View HTML Format

Computational Sustainability: A Socio-technical Perspective

ACM Computing Surveys

Abstract

References

Cited By

Index Terms

Recommendations

Computational sustainability

Feature Information Recognition of Waste Recycling Resource Set Based on Data Mining

Decision Analysis to Advance Environmental Sustainability