4,670 research outputs found
Computing in the RAIN: a reliable array of independent nodes
The RAIN project is a research collaboration between Caltech and NASA-JPL on distributed computing and data-storage systems for future spaceborne missions. The goal of the project is to identify and develop key building blocks for reliable distributed systems built with inexpensive off-the-shelf components. The RAIN platform consists of a heterogeneous cluster of computing and/or storage nodes connected via multiple interfaces to networks configured in fault-tolerant topologies. The RAIN software components run in conjunction with operating system services and standard network protocols. Through software-implemented fault tolerance, the system tolerates multiple node, link, and switch failures, with no single point of failure. The RAIN-technology has been transferred to Rainfinity, a start-up company focusing on creating clustered solutions for improving the performance and availability of Internet data centers. In this paper, we describe the following contributions: 1) fault-tolerant interconnect topologies and communication protocols providing consistent error reporting of link failures, 2) fault management techniques based on group membership, and 3) data storage schemes based on computationally efficient error-control codes. We present several proof-of-concept applications: a highly-available video server, a highly-available Web server, and a distributed checkpointing system. Also, we describe a commercial product, Rainwall, built with the RAIN technology
Succinct Representations of Permutations and Functions
We investigate the problem of succinctly representing an arbitrary
permutation, \pi, on {0,...,n-1} so that \pi^k(i) can be computed quickly for
any i and any (positive or negative) integer power k. A representation taking
(1+\epsilon) n lg n + O(1) bits suffices to compute arbitrary powers in
constant time, for any positive constant \epsilon <= 1. A representation taking
the optimal \ceil{\lg n!} + o(n) bits can be used to compute arbitrary powers
in O(lg n / lg lg n) time.
We then consider the more general problem of succinctly representing an
arbitrary function, f: [n] \rightarrow [n] so that f^k(i) can be computed
quickly for any i and any integer power k. We give a representation that takes
(1+\epsilon) n lg n + O(1) bits, for any positive constant \epsilon <= 1, and
computes arbitrary positive powers in constant time. It can also be used to
compute f^k(i), for any negative integer k, in optimal O(1+|f^k(i)|) time.
We place emphasis on the redundancy, or the space beyond the
information-theoretic lower bound that the data structure uses in order to
support operations efficiently. A number of lower bounds have recently been
shown on the redundancy of data structures. These lower bounds confirm the
space-time optimality of some of our solutions. Furthermore, the redundancy of
one of our structures "surpasses" a recent lower bound by Golynski [Golynski,
SODA 2009], thus demonstrating the limitations of this lower bound.Comment: Preliminary versions of these results have appeared in the
Proceedings of ICALP 2003 and 2004. However, all results in this version are
improved over the earlier conference versio
Partial Orders for Efficient BMC of Concurrent Software
This version previously deposited at arXiv:1301.1629v1 [cs.LO]The vast number of interleavings that a concurrent program can have is typically identified as the root cause of the difficulty of automatic analysis of concurrent software. Weak memory is generally believed to make this problem even harder. We address both issues by modelling programs' executions with partial orders rather than the interleaving semantics (SC). We implemented a software analysis tool based on these ideas. It scales to programs of sufficient size to achieve first-time formal verification of non-trivial concurrent systems code over a wide range of models, including SC, Intel x86 and IBM Power
Measurements As First-class Artifacts
The emergence of programmable switches has sparked a significant amount of
work on new techniques to perform more powerful measurement tasks, for
instance, to obtain fine-grained traffic and performance statistics. Previous
work has focused on the efficiency of these measurements alone and has
neglected flexibility, resulting in solutions that are hard to reuse or
repurpose and that often overlap in functionality or goals.
In this paper, we propose the use of a set of reusable primitive building
blocks that can be composed to express measurement tasks in a concise and
simple way. We describe the rationale for the design of our primitives, that we
have named MAFIA (Measurements As FIrst-class Artifacts), and using several
examples we illustrate how they can be combined to realize a comprehensive
range of network measurement tasks. Writing MAFIA code does not require expert
knowledge of low-level switch architecture details. Using a prototype
implementation of MAFIA, we demonstrate the applicability of our approach and
show that the use of our primitives results in compiled code that is comparable
in size and resource usage with manually written specialized P4 code and can be
run in current hardware.Comment: Infocom 2019 extended versio
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