25,496 research outputs found
Self-Healing Computation
In the problem of reliable multiparty computation (RC), there are
parties, each with an individual input, and the parties want to jointly compute
a function over inputs. The problem is complicated by the fact that an
omniscient adversary controls a hidden fraction of the parties.
We describe a self-healing algorithm for this problem. In particular, for a
fixed function , with parties and gates, we describe how to perform
RC repeatedly as the inputs to change. Our algorithm maintains the
following properties, even when an adversary controls up to parties, for any constant . First, our
algorithm performs each reliable computation with the following amortized
resource costs: messages, computational
operations, and latency, where is the depth of the circuit
that computes . Second, the expected total number of corruptions is , after which the adversarially controlled parties are
effectively quarantined so that they cause no more corruptions.Comment: 17 pages and 1 figure. It is submitted to SSS'1
An efficient self-healing key distribution scheme
Self-healing key distribution schemes enable a group user to recover session keys from two broadcast messages he received before and after those sessions, even if the broadcast messages for the middle sessions are lost due to network failure. These schemes are quite suitable in supporting secure communication over unreliable networks such as sensor networks and ad hoc networks. An efficient self-healing key distribution scheme is proposed in this paper. The scheme bases on the concept of access polynomial and self-healing key distribution model constructed by Hong et al. The new scheme reduces communication and computation overheads greatly yet still keeps the constant storageoverhead
Emergent velocity agreement in robot networks
In this paper we propose and prove correct a new self-stabilizing velocity
agreement (flocking) algorithm for oblivious and asynchronous robot networks.
Our algorithm allows a flock of uniform robots to follow a flock head emergent
during the computation whatever its direction in plane. Robots are
asynchronous, oblivious and do not share a common coordinate system. Our
solution includes three modules architectured as follows: creation of a common
coordinate system that also allows the emergence of a flock-head, setting up
the flock pattern and moving the flock. The novelty of our approach steams in
identifying the necessary conditions on the flock pattern placement and the
velocity of the flock-head (rotation, translation or speed) that allow the
flock to both follow the exact same head and to preserve the flock pattern.
Additionally, our system is self-healing and self-stabilizing. In the event of
the head leave (the leading robot disappears or is damaged and cannot be
recognized by the other robots) the flock agrees on another head and follows
the trajectory of the new head. Also, robots are oblivious (they do not recall
the result of their previous computations) and we make no assumption on their
initial position. The step complexity of our solution is O(n)
Efficient Utility-Driven Self-Healing Employing Adaptation Rules for Large Dynamic Architectures
Self-adaptation can be realized in various ways. Rule-based approaches
prescribe the adaptation to be executed if the system or environment satisfy
certain conditions and result in scalable solutions, however, with often only
satisfying adaptation decisions. In contrast, utility-driven approaches
determine optimal adaptation decisions by using an often costly optimization
step, which typically does not scale well for larger problems. We propose a
rule-based and utility-driven approach that achieves the beneficial properties
of each of these directions such that the adaptation decisions are optimal
while the computation remains scalable since an expensive optimization step can
be avoided. The approach can be used for the architecture-based self-healing of
large software systems. We define the utility for large dynamic architectures
of such systems based on patterns capturing issues the self-healing must
address and we use patternbased adaptation rules to resolve the issues.
Defining the utility as well as the adaptation rules pattern-based allows us to
compute the impact of each rule application on the overall utility and to
realize an incremental and efficient utility-driven self-healing. We
demonstrate the efficiency and optimality of our scheme in comparative
experiments with a static rule-based scheme as a baseline and a utility-driven
approach using a constraint solver
Self-Healing Tile Sets
Biology provides the synthetic chemist with a tantalizing and frustrating challenge:
to create complex objects, defined from the molecular scale up to meters,
that construct themselves from elementary components, and perhaps
even reproduce themselves. This is the challenge of bottom-up fabrication.
The most compelling answer to this challenge was formulated in the early
1980s by Ned Seeman, who realized that the information carried by DNA
strands provides a means to program molecular self-assembly, with potential
applications including DNA scaffolds for crystallography [19] or for molecular
electronic circuits [15]. This insight opened the doors to engineering with the
rich set of phenomena available in nucleic acid chemistry [20]
Memcomputing: a computing paradigm to store and process information on the same physical platform
In present day technology, storing and processing of information occur on
physically distinct regions of space. Not only does this result in space
limitations; it also translates into unwanted delays in retrieving and
processing of relevant information. There is, however, a class of two-terminal
passive circuit elements with memory, memristive, memcapacitive and
meminductive systems -- collectively called memelements -- that perform both
information processing and storing of the initial, intermediate and final
computational data on the same physical platform. Importantly, the states of
these memelements adjust to input signals and provide analog capabilities
unavailable in standard circuit elements, resulting in adaptive circuitry, and
providing analog massively-parallel computation. All these features are
tantalizingly similar to those encountered in the biological realm, thus
offering new opportunities for biologically-inspired computation. Of particular
importance is the fact that these memelements emerge naturally in nanoscale
systems, and are therefore a consequence and a natural by-product of the
continued miniaturization of electronic devices. We will discuss the various
possibilities offered by memcomputing, discuss the criteria that need to be
satisfied to realize this paradigm, and provide an example showing the solution
of the shortest-path problem and demonstrate the healing property of the
solution path.Comment: The first part of this paper has been published in Nature Physics 9,
200-202 (2013). The second part has been expanded and is now included in
arXiv:1304.167
Generalized Self-Healing Key Distribution using Vector Space Access Structure
Abstract. We propose and analyze a generalized self-healing key distribution using vector space access structure in order to reach more flexible performance of the scheme. Our self-healing technique enables better performance gain over previous approaches in terms of storage, communication and computation complexity. We provide rigorous treatment of security of our scheme in an appropriate security framework and show it is computationally secure and achieves forward and backward secrecy
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