We consider methods for finding a simple polygon of minimum (Min-Area) or maximum (Max-Area) possible area for a given set of points in the plane. Both problems are known to be NP-hard; at the center of the recent CG Challenge, practical methods have received considerable attention. However, previous methods focused on heuristic methods, with no proof of optimality. We develop exact methods, based on a combination of geometry and integer programming. As a result, we are able to solve instances of up to \( n=25 \) points to provable optimality. While this extends the range of solvable instances by a considerable amount, it also illustrates the practical difficulty of both problem variants.

This is the first of two companion papers that investigate the operations of distributed satellite systems. This first article presents a survey of conventional methods of operations of spacecraft constellations, investigates its scalability for growing number of spacecraft, and identifies operational paradigm shifts. The second article focuses on the classification of distributed satellite systems and evaluates commercial tools for automated spacecraft operations. The trend of using distributed space systems such as satellite constellation instead of monolithic systems has been growing in the last decade. Recently, a variety of large satellite constellations were announced and the production of some has started. Several of these announced constellations feature more than 1000 satellites. While the "mass production" of satellites is feasible and has already started, there are no effective solutions existing for the "mass operations" of satellites. In some instances, conventional spacecraft operations involve manual control by skilled human operators, following at least a 4-eyes principle. Even when operators batch multiple telecommands together, the scheduling process is still challenging for growing spacecraft numbers. This approach is not (linearly) scalable to large satellite constellations: new operational methods need to be established and the automation level of the constellation increased. To motivate the research activities in this framework and pave the way for automated management of large distributed satellite systems, this paper gives an overview of some conventional methods of spacecraft operations. From this description, the weakness areas in terms of scalability are deduced, identifying potential bottlenecks for the operations of such systems. Following, based on three use case studies, the operational paradigm shifts related to the operation of large distributed satellite systems are identified. (C) 2020 COSPAR. Published by Elsevier Ltd. All rights reserved.

Recent developments have seen a trend towards larger constellations of spacecraft, with some proposals featuring constellations of more than 10.000 satellites. While similar concepts for large constellations already existed in the past, traditional satellite deployments hardly ever feature groups of more than 100 satellites. This trend towards considerably larger satellite numbers originates from non-traditional design and operations of spacecraft by non-traditional space companies. The evolution in the space sector, precipitated by new players, is often referred to as "Space 4.0" or "New Space". It necessitates a rethinking of the way satellites and satellite constellations are planned, designed, and operated. New operational paradigms are needed to enable automatic, optimal task definition, and scheduling in a holistic approach. This is the second of two companion papers that investigate the operations of distributed satellite systems. This second article investigates the classification of distributed satellite systems and evaluates commercial tools for automated spacecraft operations, whereas the first article performed a survey of conventional and "new space"operations of spacecraft constellations. Classification metrics for constellations are derived and evaluated with respect to their informative value concerning the operation, the automation, and the scalability of the constellation. The proposed classification system is applied to the Dove and RapidEye constellation and allows for a comparison between the presented automation approaches. Commercial tools for automated spacecraft operations are evaluated for several mission task elements, such as orbit control, orbit maintenance, and collision avoidance. Subsequently, the trends, benefits, and standardization needs for operational automation are identified. (C) 2020 COSPAR. Published by Elsevier Ltd. All rights reserved.

We present a study on the practical nature of the NP-hard problem of finding a Minimum Weight Triangulation (MWT) of a planar point set: Can we deliberately construct practically difficult instances? This requires identifying point sets for which all of a number of previously developed exact and heuristic methods simultaneously encounter a combination of pitfalls. We show that for instances of medium size, this seems unlikely, implying that one of several alternative methods may offer a path to an optimal solution. This complements recent work on the practical performance of these heuristic methods for specific classes of large benchmark instances, indicating that MWT problems may indeed be practically easier to solve than implied by its NP-hard complexity.

We consider a central challenge that is mission critical for the successful operation of large-scale satellite constellations in Low-Earth Orbit: How can we coordinate the short-term download operations for the enormous amounts of generated data, based on wireless line-of-sight connections to a limited number of stationary ground station? These issues are critical for the future growth of space systems, with multiple commercial space operators competing for downloading their commercial data in a timely fashion, relying on the services of a scarce set of ground stations that is subject to numerous strong constraints, so it cannot simply be expanded. We present a distributed auction-based scheduling approach for maximizing the value of the downloaded data. Our method allows competing satellite operators to bid for contact times and has a fair and transparent price estimation based on the competition. On its own, it can also be used with a simple bidding strategy to obtain good schedules; this is demonstrated on benchmark simulation with up to 1080 satellites. As a consequence, we are able to achieve values rates of 74% of available data, compared to 28% for standard greedy strategies.

We consider practical methods for the problem of finding a minimum-weight triangulation (MWT) of a planar point set, a classic problem of computational geometry with many applications. While Mulzer and Rote proved in 2006 that computing an MWT is NP-hard, Beirouti and Snoeyink showed in 1998 that computing provably optimal solutions for MWT instances of up to 80,000 uniformly distributed points is possible, making use of clever heuristics that are based on geometric insights. We show that these techniques can be refined and extended to instances of much bigger size and different type, based on an array of modifications and parallelizations in combination with more efficient geometric encodings and data structures. As a result, we are able to solve MWT instances with up to 30,000,000 uniformly distributed points in less than 4 minutes to provable optimality. Moreover, we can compute optimal solutions for a vast array of other benchmark instances that are not uniformly distributed, including normally distributed instances (up to 30,000,000 points), all point sets in the TSPLIB (up to 85,900 points), and VLSI instances with up to 744,710 points. This demonstrates that from a practical point of view, MWT instances can be handled quite well, despite their theoretical difficulty.

We consider the Minimum Perimeter Polygon Problem (MP3): for a given set V of points in the plane, find a polygon P with holes that has vertex set V , such that the total boundary length is smallest possible. The MP3 can be considered a natural geometric generalization of the Traveling Salesman Problem (TSP), which asks for a simple polygon with minimum perimeter. Just like the TSP, the MP3 occurs naturally in the context of curve reconstruction. Even though the closely related problem of finding a minimum cycle cover is polynomially solvable by matching techniques, we prove how the topological structure of a polygon leads to NP-hardness of the MP3. On the positive side, we provide constant-factor approximation algorithms. In addition to algorithms with theoretical worst-case guarantess, we provide practical methods for computing provably optimal solutions for relatively large instances, based on integer programming. An additional difficulty compared to the TSP is the fact that only a subset of subtour constraints is valid, depending not on combinatorics, but on geometry. We overcome this difficulty by establishing and exploiting geometric properties. This allows us to reliably solve a wide range of benchmark instances with up to 600 vertices within reasonable time on a standard machine. We also show that restricting the set of connections between points to edges of the Delaunay triangulation yields results that are on average within 0.5% of the optimum for large classes of benchmark instances.

Casted whey protein films exposed to ultraviolet irradiation were analyzed for their cross-linking properties and mechanical and barrier performance. Expected mechanical and barrier improvements are discussed with regard to quantification of the cross-linking in the UV-treated whey protein films. Swelling tests were used to determine the degree of swelling, degree of cross-linking, and cross-linking density. When the UV radiation dosage was raised, a significant increase of the tensile strength as well as an increase in Young’s modulus was observed. No significant changes in water vapor and oxygen barrier properties between the UV-treated films and an untreated reference sample could be observed. The cross-linking density and the degree of cross-linking significantly increased due to UV radiation. Combined results indicate a disordered protein network in cast films showing locally free volume and therefore only minor mechanical and barrier improvements.

The maturation of the Web platform has given rise to sophisticated and demanding Web applications such as interactive 3D visualization, audio and video software, and games. With that, efficiency and security of code on the Web has become more important than ever. Yet JavaScript as the only built-in language of the Web is not well-equipped to meet these requirements, especially as a compilation target. Engineers from the four major browser vendors have risen to the challenge and collaboratively designed a portable low-level bytecode called WebAssembly. It offers compact representation, efficient validation and compilation, and safe low to no-overhead execution. Rather than committing to a specific programming model, WebAssembly is an abstraction over modern hardware, making it language-, hardware-, and platform-independent, with use cases beyond just the Web. WebAssembly has been designed with a formal semantics from the start. We describe the motivation, design and formal semantics of WebAssembly and provide some preliminary experience with implementations.

We consider the Minimum Perimeter Polygon Problem (MP3): for a given set V of points in the plane, find a polygon P with holes that has vertex set V , such that the total boundary length is smallest possible. The MP3 can be considered a natural geometric generalization of the Traveling Salesman Problem (TSP), which asks for a simple polygon with minimum perimeter. Just like the TSP, the MP3 occurs naturally in the context of curve reconstruction. Even though the closely related problem of finding a minimum cycle cover is polynomially solvable by matching techniques, we prove how the topological structure of a polygon leads to NP-hardness of the MP3. On the positive side, we provide constant-factor approximation algorithms. In addition to algorithms with theoretical worst-case guarantess, we provide practical methods for computing provably optimal solutions for relatively large instances, based on integer programming. An additional difficulty compared to the TSP is the fact that only a subset of subtour constraints is valid, depending not on combinatorics, but on geometry. We overcome this difficulty by establishing and exploiting geometric properties. This allows us to reliably solve a wide range of benchmark instances with up to 600 vertices within reasonable time on a standard machine. We also show that restricting the set of connections between points to edges of the Delaunay triangulation yields results that are on average within 0.5% of the optimum for large classes of benchmark instances.

This study investigated the chemical grafting of a single-layer poly(vinyl alcohol) (PVOH) film. The effect of the grafting parameters (grafting time, grafting temperature, and concentration of fatty acid chloride) on the hydrophobicity of the film surface and the film solubility were evaluated. The PVOH substrate film (cold-water soluble at 20°C) was manufactured by flat extrusion and had a thickness of 50 μm (±5 μm). The chemical grafting was performed using the transfer method with palmitoyl chloride (C16). The solubility, surface energy, and water vapor transmission rate of the grafted films were measured. The process parameters which produced the most hydrophobic PVOH film were found to be a fatty acid concentration of 3%, a grafting time of 14 min, and a grafting temperature of 130°C. These studies involved systematic adjustment of the hydrophobicity of one side of PVOH films. The results open up opportunities for packing fluids in water soluble packaging.

We provide exact and approximation methods for solving a geometric relaxation of the Traveling Salesman Problem (TSP) that occurs in curve reconstruction: for a given set of vertices in the plane, the problem Minimum Perimeter Polygon (MPP) asks for a (not necessarily simply connected) polygon with shortest possible boundary length. Even though the closely related problem of finding a minimum cycle cover is polynomially solvable by matching techniques, we prove how the topological structure of a polygon leads to NP-hardness of the MPP. On the positive side, we show how to achieve a constant-factor approximation.When trying to solve MPP instances to provable optimality by means of integer programming, an additional difficulty compared to the TSP is the fact that only a subset of subtour constraints is valid, depending not on combinatorics, but on geometry. We overcome this difficulty by establishing and exploiting additional geometric properties. This allows us to reliably solve a wide range of benchmark instances with up to 600 vertices within reasonable time on a standard machine. We also show that using a natural geometry-based sparsification yields results that are on average within 0.5% of the optimum.

The semantics of concurrent data structures is usually given by a sequential specification and a consistency condition. Linearizability is the most popular consistency condition due to its simplicity and general applicability. Nevertheless, for applications that do not require all guarantees offered by linearizability, recent research has focused on improving performance and scalability of concurrent data structures by relaxing their semantics. In this paper, we present local linearizability, a relaxed consistency condition that is applicable to container-type concurrent data structures like pools, queues, and stacks. While linearizability requires that the effect of each operation is observed by all threads at the same time, local linearizability only requires that for each thread T, the effects of its local insertion operations and the effects of those removal operations that remove values inserted by T are observed by all threads at the same time. We investigate theoretical and practical properties of local linearizability and its relationship to many existing consistency conditions. We present a generic implementation method for locally linearizable data structures that uses existing linearizable data structures as building blocks. Our implementations show performance and scalability improvements over the original building blocks and outperform the fastest existing container-type implementations.

Concurrent data structures such as concurrent queues, stacks, and pools are widely used for concurrent programming of shared-memory multiprocessor and multicore machines. The key challenge is to develop data structures that are not only fast on a given machine but whose performance scales, ideally linearly, with the number of threads, cores, and processors on even bigger machines. Part of that challenge is to provide a common ground for systematically evaluating the performance and scalability of new concurrent data structures and comparing the results with the performance and scalability of existing solutions. For this purpose, we have developed Scal which is an open-source benchmarking framework that provides (1) software infrastructure for executing concurrent data structure algorithms, (2) workloads for benchmarking their performance and scalability, and (3) implementations of a large set of concurrent data structures. We discuss the Scal infrastructure, workloads, and implementations, and encourage further use and development of Scal in the design and implementation of ever faster concurrent data structures.

Concurrent data-structures, such as stacks, queues, and deques, often implicitly enforce a total order over elements in their underlying memory layout. However, much of this order is unnecessary: linearizability only requires that elements are ordered if the insert methods ran in sequence. We propose a new approach which uses timestamping to avoid unnecessary ordering. Pairs of elements can be left unordered if their associated insert operations ran concurrently, and order imposed as necessary at the eventual removal. We realise our approach in a new non-blocking data-structure, the TS (timestamped) stack. Using the same approach, we can define corresponding queue and deque data-structures. In experiments on x86, the TS stack outperforms and outscales all its competitors -- for example, it outperforms the elimination-backoff stack by factor of two. In our approach, more concurrency translates into less ordering, giving less-contended removal and thus higher performance and scalability. Despite this, the TS stack is linearizable with respect to stack semantics. The weak internal ordering in the TS stack presents a challenge when establishing linearizability: standard techniques such as linearization points work well when there exists a total internal order. We present a new stack theorem, mechanised in Isabelle, which characterises the orderings sufficient to establish stack semantics. By applying our stack theorem, we show that the TS stack is indeed linearizable. Our theorem constitutes a new, generic proof technique for concurrent stacks, and it paves the way for future weakly ordered data-structure designs.

The semantics of concurrent data structures is usually given by a sequential specification and a consistency condition. Linearizability is the most popular consistency condition due to its simplicity and general applicability. Nevertheless, for applications that do not require all guarantees offered by linearizability, recent research has focused on improving performance and scalability of concurrent data structures by relaxing their semantics. In this paper, we present local linearizability, a relaxed consistency condition that is applicable to container-type concurrent data structures like pools, queues, and stacks. While linearizability requires that the effect of each operation is observed by all threads at the same time, local linearizability only requires that for each thread T, the effects of its local insertion operations and the effects of those removal operations that remove values inserted by T are observed by all threads at the same time. We investigate theoretical and practical properties of local linearizability and its relationship to many existing consistency conditions. We present a generic implementation method for locally linearizable data structures that uses existing linearizable data structures as building blocks. Our implementations show performance and scalability improvements over the original building blocks and outperform the fastest existing container-type implementations.

Concurrent data-structures, such as stacks, queues and deques, often implicitly enforce a total order over elements with their underlying memory layout. However, linearizability only requires that elements are ordered if the inserting methods ran sequentially. We propose a new data-structure design which uses explicit timestamping to avoid unwanted ordering. Elements can be left unordered by associating them with unordered timestamps if their insert operations ran concurrently. In our approach, more concurrency translates into less ordering, and thus less-contended removal and ultimately higher performance and scalability. As a proof of concept, we realise our approach in a non-blocking doubleended queue. In experiments our deque outperforms and outscales the Michael-Scott queue by a factor of 4.2 and the Treiber stack by a factor of 2.8. It even outscales the elimination-backoff stack, the fastest concurrent stack of which we are aware, and the flat-combining queue, a fast queue more scalable than Michael-Scott.

A prominent remedy to multicore scalability issues in concurrent data structure implementations is to relax the sequential specification of the data structure. We present distributed queues (DQ), a new family of relaxed concurrent queue implementations. DQs implement relaxed queues with linearizable emptiness check and either configurable or bounded out-of-order behavior or pool behavior. Our experiments show that DQs outperform and outscale in micro- and macrobenchmarks all strict and relaxed queue as well as pool implementations that we considered.

Designing and implementing high-performance concurrent data structures whose access performance scales on multicore hardware is difficult. Concurrent implementations of FIFO queues, for example, seem to require algorithms that efficiently increase the potential for parallel access by implementing semantically relaxed rather than strict FIFO queues where elements may be returned in some out-of-order fashion. However, we show experimentally that the on average shorter execution time of enqueue and dequeue operations of fast but relaxed implementations may offset the effect of semantical relaxations making them appear as behaving more FIFO than strict but slow implementations. Our key assumption is that ideal concurrent data structure operations should execute in zero time. We define two metrics, element-fairness and operation-fairness, to measure the degree of element and operation reordering, respectively, assuming operations take zero time. Element-fairness quantifies the deviation from FIFO queue semantics had all operations executed in zero time. With this metric even strict implementations of FIFO queues are not FIFO. Operation-fairness helps explaining element-fairness by quantifying operation reordering when considering the actual time operations took effect relative to their invocation time. In our experiments, the effect of poor operation-fairness of strict but slow implementations on element-fairness may outweigh the effect of semantical relaxation of fast but relaxed implementations.