The Role of Agriculture and Food Consumption in Tropical Conservation

A growing human population, shifting human dietary habits, and climate change are negatively affecting global ecosystems on a massive scale. Expanding agricultural areas to feed a growing population drives extensive habitat loss, and climate change compounds stresses on both food security and ecosystems. Understanding the negative effects of human diet and climate change on agricultural and natural ecosystems provides a context within which potential technological and behavioral solutions can be proposed to help maximize conservation. The purpose of this research was to (1) examine the potential effects of climate change on the suitability of areas for commercial banana plantations in Latin America in the 2050s and how shifts in growing areas could affect protected areas; (2) test the ability of small unmanned aerial vehicles (UAVs) to map productivity of banana plantations as a potential tool for increasing yields and decreasing future plantation expansions; (3) project the effects on biodiversity of increasing rates of animal product consumption in developing megadiverse countries; and (4) estimate the capacity of global pasture biomass production and Fischer-Tropsch hydrocarbon synthesis (IGCC-FT) processing to meet electricity, gasoline and diesel needs. The results indicate that (1) the overall extent of areas suitable for conventional banana cultivation is predicted to decrease by 19% by 2050 because of a hotter and drier climate, but all current banana exporting countries are predicted to maintain some suitable areas with no effects on protected areas; (2) Spatial patterns of NDVI and ENDVI were significantly positively correlated with several metrics of fruit yield and quality, indicating that UAV systems can be used in banana plantations to map spatial patterns of fruit yield; (3) Livestock production is the single largest driver of habitat loss, and both livestock and feedstock production are increasing in developing biodiverse tropical countries. Reducing global animal product consumption should therefore be at the forefront of strategies aimed at reducing biodiversity loss; (4) Removing livestock from global pasture lands and instead utilizing the biomass production could produce enough energy to meet 100% of the electricity, gasoline, and diesel needs of over 40 countries with extensive grassland ecosystems, primarily in tropical developing countries.

The role of agriculture and food consumption in tropical conservation

A growing human population, shifting human dietary habits, and climate change are negatively affecting global ecosystems on a massive scale. Expanding agricultural areas to feed a growing population drives extensive habitat loss, and climate change compounds stresses on both food security and ecosystems. Understanding the negative effects of human diet and climate change on agricultural and natural ecosystems provides a context within which potential technological and behavioral solutions can be proposed to help maximize conservation. The purpose of this research was to (1) examine the potential effects of climate change on the suitability of areas for commercial banana plantations in Latin America in the 2050s and how shifts in growing areas could affect protected areas; (2) test the ability of small unmanned aerial vehicles (UAVs) to map productivity of banana plantations as a potential tool for increasing yields and decreasing future plantation expansions; (3) project the effects on biodiversity of increasing rates of animal product consumption in developing megadiverse countries; and (4) estimate the capacity of global pasture biomass production and Fischer-Tropsch hydrocarbon synthesis (IGCC-FT) processing to meet electricity, gasoline and diesel needs. The results indicate that (1) the overall extent of areas suitable for conventional banana cultivation is predicted to decrease by 19% by 2050 because of a hotter and drier climate, but all current banana exporting countries are predicted to maintain some suitable areas with no effects on protected areas; (2) Spatial patterns of NDVI and ENDVI were significantly positively correlated with several metrics of fruit yield and quality, indicating that UAV systems can be used in banana plantations to map spatial patterns of fruit yield; (3) Livestock production is the single largest driver of habitat loss, and both livestock and feedstock production are increasing in developing biodiverse tropical countries. Reducing global animal product consumption should therefore be at the forefront of strategies aimed at reducing biodiversity loss; (4) Removing livestock from global pasture lands and instead utilizing the biomass production could produce enough energy to meet 100% of the electricity, gasoline, and diesel needs of over 40 countries with extensive grassland ecosystems, primarily in tropical developing countries.^

Host and network optimizations for performance enhancement and energy efficiency in data center networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

Host and Network Optimizations for Performance Enhancement and Energy Efficiency in Data Center Networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.