Introduction to the special section on dependable network computing

Dependable network computing is becoming a key part of our daily economic and social life. Every day, millions of users and businesses are utilizing the Internet infrastructure for real-time electronic commerce transactions, scheduling important events, and building relationships. While network traffic and the number of users are rapidly growing, the mean-time between failures (MTTF) is surprisingly short; according to recent studies, in the majority of Internet backbone paths, the MTTF is 28 days. This leads to a strong requirement for highly dependable networks, servers, and software systems. The challenge is to build interconnected systems, based on available technology, that are inexpensive, accessible, scalable, and dependable. This special section provides insights into a number of these exciting challenges

MAGE: Nearly Zero-Cost Virtual Memory for Secure Computation

Secure Computation (SC) is a family of cryptographic primitives for computing on encrypted data in single-party and multi-party settings. SC is being increasingly adopted by industry for a variety of applications. A significant obstacle to using SC for practical applications is the memory overhead of the underlying cryptography. We develop MAGE, an execution engine for SC that efficiently runs SC computations that do not fit in memory. We observe that, due to their intended security guarantees, SC schemes are inherently oblivious -- their memory access patterns are independent of the input data. Using this property, MAGE calculates the memory access pattern ahead of time and uses it to produce a memory management plan. This formulation of memory management, which we call memory programming, is a generalization of paging that allows MAGE to provide a highly efficient virtual memory abstraction for SC. MAGE outperforms the OS virtual memory system by up to an order of magnitude, and in many cases, runs SC computations that do not fit in memory at nearly the same speed as if the underlying machines had unbounded physical memory to fit the entire computation.Comment: 19 pages; Accepted to OSDI 202

Performant TCP for Low-Power Wireless Networks

Low-power and lossy networks (LLNs) enable diverse applications integrating many resource-constrained embedded devices, often requiring interconnectivity with existing TCP/IP networks as part of the Internet of Things. But TCP has received little attention in LLNs due to concerns about its overhead and performance, leading to LLN-specific protocols that require specialized gateways for interoperability. We present a systematic study of a well-designed TCP stack in IEEE 802.15.4-based LLNs, based on the TCP protocol logic in FreeBSD. Through careful implementation and extensive experiments, we show that modern low-power sensor platforms are capable of running full-scale TCP and that TCP, counter to common belief, performs well despite the lossy nature of LLNs. By carefully studying the interaction between the transport and link layers, we identify subtle but important modifications to both, achieving TCP goodput within 25% of an upper bound (5-40x higher than prior results) and low-power operation commensurate to CoAP in a practical LLN application scenario. This suggests that a TCP-based transport layer, seamlessly interoperable with existing TCP/IP networks, is viable and performant in LLNs.Comment: 22 pages; Accepted at NSDI 2020; Updated Table

SnapLink: Fast and Accurate Vision-Based Appliance Control in Large Commercial Buildings

As the number and heterogeneity of appliances in smart buildings increases, identifying and controlling them becomes challenging. Existing methods face various challenges when deployed in large commercial buildings. For example, voice command assistants require users to memorize many control commands. Attaching Bluetooth dongles or QR codes to appliances introduces considerable deployment overhead. In comparison, identifying an appliance by simply pointing a smartphone camera at it and controlling the appliance using a graphical overlay interface is more intuitive. We introduce SnapLink, a responsive and accurate vision-based system for mobile appliance identification and interaction using image localization. Compared to the image retrieval approaches used in previous vision-based appliance control systems, SnapLink exploits 3D models to improve identification accuracy and reduce deployment overhead via quick video captures and a simplified labeling process. We also introduce a feature sub-sampling mechanism to achieve low latency at the scale of a commercial building. To evaluate SnapLink, we collected training videos from 39 rooms to represent the scale of a modern commercial building. It achieves a 94% successful appliance identification rate among 1526 test images of 179 appliances within 120 ms average server processing time. Furthermore, we show that SnapLink is robust to viewing angle and distance differences, illumination changes, as well as daily changes in the environment. We believe the SnapLink use case is not limited to appliance control: it has the potential to enable various new smart building applications

Systemic therapy of Cushing’s syndrome

Cushing’s disease (CD) in a stricter sense derives from pathologic adrenocorticotropic hormone (ACTH) secretion usually triggered by micro- or macroadenoma of the pituitary gland. It is, thus, a form of secondary hypercortisolism. In contrast, Cushing’s syndrome (CS) describes the complexity of clinical consequences triggered by excessive cortisol blood levels over extended periods of time irrespective of their origin. CS is a rare disease according to the European orphan regulation affecting not more than 5/10,000 persons in Europe. CD most commonly affects adults aged 20–50 years with a marked female preponderance (1:5 ratio of male vs. female). Patient presentation and clinical symptoms substantially vary depending on duration and plasma levels of cortisol. In 80% of cases CS is ACTH-dependent and in 20% of cases it is ACTH-independent, respectively. Endogenous CS usually is a result of a pituitary tumor. Clinical manifestation of CS, apart from corticotropin-releasing hormone (CRH-), ACTH-, and cortisol-producing (malign and benign) tumors may also be by exogenous glucocorticoid intake. Diagnosis of hypercortisolism (irrespective of its origin) comprises the following: Complete blood count including serum electrolytes, blood sugar etc., urinary free cortisol (UFC) from 24 h-urine sampling and circadian profile of plasma cortisol, plasma ACTH, dehydroepiandrosterone, testosterone itself, and urine steroid profile, Low-Dose-Dexamethasone-Test, High-Dose-Dexamethasone-Test, after endocrine diagnostic tests: magnetic resonance imaging (MRI), ultra-sound, computer tomography (CT) and other localization diagnostics. First-line therapy is trans-sphenoidal surgery (TSS) of the pituitary adenoma (in case of ACTH-producing tumors). In patients not amenable for surgery radiotherapy remains an option. Pharmacological therapy applies when these two options are not amenable or refused. In cases when pharmacological therapy becomes necessary, Pasireotide should be used in first-line in CD. CS patients are at an overall 4-fold higher mortality rate than age- and gender-matched subjects in the general population. The following article describes the most prominent substances used for clinical management of CS and gives a systematic overview of safety profiles, pharmacokinetic (PK)-parameters, and regulatory framework

Who Eats Whom in a Pool? A Comparative Study of Prey Selectivity by Predatory Aquatic Insects

Predatory aquatic insects are a diverse group comprising top predators in small fishless water bodies. Knowledge of their diet composition is fragmentary, which hinders the understanding of mechanisms maintaining their high local diversity and of their impacts on local food web structure and dynamics. We conducted multiple-choice predation experiments using nine common species of predatory aquatic insects, including adult and larval Coleoptera, adult Heteroptera and larval Odonata, and complemented them with literature survey of similar experiments. All predators in our experiments fed selectively on the seven prey species offered, and vulnerability to predation varied strongly between the prey. The predators most often preferred dipteran larvae; previous studies further reported preferences for cladocerans. Diet overlaps between all predator pairs and predator overlaps between all prey pairs were non-zero. Modularity analysis separated all primarily nectonic predator and prey species from two groups of large and small benthic predators and their prey. These results, together with limited evidence from the literature, suggest a highly interconnected food web with several modules, in which similarly sized predators from the same microhabitat are likely to compete strongly for resources in the field (observed Pianka’s diet overlap indices >0.85). Our experiments further imply that ontogenetic diet shifts are common in predatory aquatic insects, although we observed higher diet overlaps than previously reported. Hence, individuals may or may not shift between food web modules during ontogeny