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Finite and decreasing landfill space on Army installations is a significant concern. Efficient waste management is essential for achieving resiliency and extending the lifespan of remaining landfills. The purpose of this demonstration was to conduct independent performance tests of small unmanned aircraft systems (sUAS) and their utility for providing landfill assessments in remote areas where physical presence is either dangerous or inefficient. An active, near capacity construction and demolition (C&D) landfill at Fort Gordon, Georgia, was identified for the demonstration. The flights, data requirements, and outputs generated by the sUAS flyovers were analyzed for efficacy in detecting cell capacity and subsidence. Each flight took 1–2 hours for mobilization, ground marker placement, flight, and postflight analysis. Volumetric and topographic surveys were analyzed in less time than is typical for traditional surveying methods. After initial setup of ground markers and rectification, sUAS flights save a significant amount of time. However, skilled individuals are required for flights and for processing and maintaining data. The technology is widely relevant to the Army, is commercially available, and offers an average of 30% cost savings in terms of manpower, repeatability, and equipment. The use of sUAS technology is recommended for monitoring and surveying Army landfills.

Thurgood Canyon, located on White Sands Missile Range (WSMR), contains an alluvial fan that is bisected by a primary installation road and is in the proximity of sensitive fish habitats. This project was initiated to determine if and how sensitive fish habitats at the base of the fan are impacted by the existing drainage infrastructure and to assess the condition and sustainability of the existing transportation infrastructure. Findings show that the current drainage infrastructure maintains flow energy and sediment carrying capacity further down the fan than would occur in its absence. However, frequent to moderately rare (small to medium) flood events dissipate over 2 km from sensitive habitat, and overland flow and sediment do not reach the base of the fan. Controlled flow diversion is recommended upstream of the road to mitigate infrastructure or habitat impacts during very rare (very large) flood events. A comprehensive operation and management approach is presented to achieve sustainable transportation infrastructure and reduce the likelihood of impacts to the sensitive habitat.

State machine replication protocols such as Raft are widely used to build highly-available strongly-consistent services, maintaining liveness even if a minority of servers crash. As these systems are implemented and optimised for production, they accumulate many divergences from the original specification. These divergences are poorly documented, resulting in operators having an incomplete model of the system's characteristics, especially during failures. In this paper, we look at one such Raft model used to explain the November Cloudflare outage and show that etcd's behaviour during the same failure differs. We continue to show the specific optimisations in etcd causing this difference and present a more complete model of the outage based on etcd's behaviour in an emulated deployment using reckon. Finally, we highlight the upcoming PreVote optimisation in etcd, which might have prevented the outage from happening in the first place.

Quorum systems are a powerful mechanism for ensuring the consistency of replicated data. Production systems usually opt for majority quorums due to their simplicity and fault tolerance, but majority quorum systems provide poor throughput and scalability. Alternatively, researchers have invented a number of theoretically "optimal" quorum systems, but the underlying theory ignores many practical complexities such as machine heterogeneity and workload skew. In this paper, we conduct a pragmatic re-examination of quorum systems. We enrich the current theory on quorum systems with a number of practical refinements to find quorum systems that provide higher throughput, lower latency, and lower network load. We also develop a library Quoracle that precisely quantifies the available trade-offs between quorum systems to empower engineers to find optimal quorum systems, given a set of objectives for specific deployments and workloads. Our tool is available online at: https://github.com/mwhittaker/quoracle., To be published in PaPoC 2021 (https://papoc-workshop.github.io/2021/)

The Paxos algorithm is famously difficult to reason about and even more so to implement, despite having been synonymous with distributed consensus for over a decade. The recently proposed Raft protocol lays claim to being a new, understandable consensus algorithm, improving on Paxos without making compromises in performance or correctness. In this study, we repeat the Raft authors' performance analysis. We developed a clean-slate implementation of the Raft protocol and built an event-driven simulation framework for prototyping it on experimental topologies. We propose several optimizations to the Raft protocol and demonstrate their effectiveness under contention. Finally, we empirically validate the correctness of the Raft protocol invariants and evaluate Raft's understandability claims.

We depend upon distributed systems in every aspect of life. Distributed consensus, the ability to reach agreement in the face of failures and asynchrony, is a fundamental and powerful primitive for constructing reliable distributed systems from unreliable components. For over two decades, the Paxos algorithm has been synonymous with distributed consensus. Paxos is widely deployed in production systems, yet it is poorly understood and it proves to be heavyweight, unscalable and unreliable in practice. As such, Paxos has been the subject of extensive research to better understand the algorithm, to optimise its performance and to mitigate its limitations. In this thesis, we re-examine the foundations of how Paxos solves distributed consensus. Our hypothesis is that these limitations are not inherent to the problem of consensus but instead specific to the approach of Paxos. The surprising result of our analysis is a substantial weakening to the requirements of this widely studied algorithm. Building on this insight, we are able to prove an extensive generalisation over the Paxos algorithm. Our revised understanding of distributed consensus enables us to construct a diverse family of algorithms for solving consensus; covering classical as well as novel algorithms to reach consensus where it was previously thought impossible. We will explore the wide reaching implications of this new understanding, ranging from pragmatic optimisations to production systems to fundamentally novel approaches to consensus, which achieve new tradeoffs in performance, scalability and reliability.

With the human genome project running from 1989 until its completion in 2003, and the incredible advances in sequencing technology and in bioinformatics during the last decade, there has been a shift towards an increase focus on studying common complex disorders which develop due to the interplay of many different genes as well as environmental factors. Although some susceptibility genes have been identified in some populations for disorders such as cancer, diabetes and cardiovascular diseases, the integration of this information into the health care system has proven to be much more problematic than for single gene disorders. Furthermore, with the 1000$ genome supposedly just around the corner, and whole genome sequencing gradually being integrated into research protocols as well as in the clinical context, there is a strong push for the uptake of additional genomic testing. Indeed, the advent of public health genomics, wherein genomics would be integrated in all aspects of health care and public health, should be taken seriously. Although laudable, these advances also bring with them a slew of ethical and social issues that challenge the normative frameworks used in clinical genetics until now. With this in mind, we highlight herein 5 principles that are used as a primer to discuss the ethical introduction of genome-based information and genome-based technologies into public health.

In recent years, the cost of generating genome information has shown a rapid decline.1, 2 High-throughput genomic technologies make it possible to sequence the whole exome or genome of a person at a price that is affordable for some health-care systems. More services based on these technologies are now becoming available for patients, raising the issue of how to ensure that these are provided appropriately. In order to determine both the clinical utility of genetic testing and assure a high quality of the analysis, the interpretation and communication of the results must be discussed so that patients can receive appropriate advice and genetic testing. The Public and Professional Policy Committee (PPPC) and the Quality Committee of the European Society of Human Genetics (ESHG) addressed these challenges at a joint workshop in Gothenburg, Sweden, in 2010.3 PPPC also organised workshops in Amsterdam, the Netherlands (January 2011 in collaboration with the EU-funded project TECHGENE, January 2012). A report for the Health Council of the Netherlands served as a background document for the PPPC's reflections.4 Focusing on the clinical diagnostics setting, this paper is intended to contribute to the discussion and the development of guidelines in this fast-moving field, and provide recommendations for health-care professionals. The paper and recommendations were posted on the ESHG website from 20 June to 1 August 2012 for comment by the membership. The final version was approved by the ESHG Board in December 2012.

In the last few decades, great progress has been made in both genetic and genomic research. The development of the Human Genome Project has increased our knowledge of the genetic basis of diseases and has given a tremendous momentum to the development of new technologies that make widespread genetic testing possible and has increased the availability of previously inaccessible genetic information. Two examples of this exponential evolution are the increasing implementation of next-generation sequencing technologies in the clinical context and the expanding commercial offer of genetic tests directly-to-consumers.Firstly, the rapid development of next generation sequencing technologies (i.e., high-throughput and massively parallel DNA sequencing technologies) has substantially reduced both the cost and the time required to sequence an entire human genome. These technologies are increasingly being used in the clinical setting with the goal of diagnosing conditions of presumed genetic origin that cannot be explained by targeted sequencing approaches.