176 research outputs found
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
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
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