We examine how to re-design the Internet for an energyconstrained future powered by diffuse, intermittent, and expensive power sources. We consider the types of constraints this might place upon the Internet architecture and the manner in which important network components can function in this new environment. We then attempt to chart a path forward for future research.

Computer-controlled hydroponics, vertical farms, and IoT-based precision agriculture are claimed to be sustainable, healthful, and humane methods of producing food. These so-called "smart" farming methods have arisen over the past decade and have received little scrutiny from a sustainability perspective. Meanwhile, they are attracting vast sums of both research and investment funding.We ask a simple question: how sustainable is the "smart farm"? We take a technical, ecological, and social view of the systems that comprise a smart farm. Our aim is to tease apart which, if any, of the practices are actually beneficial, and which are simply a substitution of resources or a mere shifting of (human and/or ecological) externalities in time or space. To evaluate the smart farm concept, we focus on two scenarios: indoor smart farms (controlledenvironment agriculture such as vertical farms), and outdoor smart farms (in which the environment is less controlled, but managed via precision agriculture). We also provide examples of the values that smart farms embody, who stands to gain from their operation, and what better alternatives might exist.

Agriculture is a designed system with the largest areal footprint of any human activity. In some cases, the designs within agriculture emerged over thousands of years, such as the use of rows for the spatial organization of crops. In others, designs were deliberately chosen and implemented over decades, as during the Green Revolution. Currently, much work in the agricultural sciences focuses on evaluating designs that could improve agriculture’s sustainability. However, approaches to agricultural system design are diverse and fragmented, relying on individual intuition and discipline-specific methods to meet stakeholders’ often semi-incompatible goals. This ad-hoc approach presents the risk that agricultural science will overlook non-obvious designs with large societal benefits. Here, we introduce a state space framework, a common approach from computer science, to address the problem of proposing and evaluating agricultural designs computationally. This approach overcomes limitations of current agricultural system design methods by enabling a general set of computational abstractions to explore, and then select from, a very large agricultural design space, which can then be empirically tested.

Agriculture is a designed system with the largest areal footprint of any human activity. In some cases, the designs within agriculture emerged over thousands of years, such as the use of rows for the spatial organization of crops. In others, designs were deliberately chosen and implemented over decades as occurred during the Green Revolution. Currently, much work in agricultural science is focused on evaluating designs that could improve agriculture's sustainability. However, approaches to agricultural system design are diverse and fragmented, relying on individual intuition and discipline-specific methods for how to meet stakeholders' often semi-incompatible goals. This presents a risk that agricultural science will overlook non-obvious designs with large societal benefits. Here, we introduce a state space framework, a common approach from computer science, for agriculture to address the problem of proposing and evaluating designs computationally. This approach overcomes current limitations of agricultural system design by enabling a general set of computational abstractions to explore, and then select from, a much larger agricultural design set, which can then be empirically tested.