2,271 research outputs found
Self-Modeling Based Diagnosis of Software-Defined Networks
Networks built using SDN (Software-Defined Networks) and NFV (Network
Functions Virtualization) approaches are expected to face several challenges
such as scalability, robustness and resiliency. In this paper, we propose a
self-modeling based diagnosis to enable resilient networks in the context of
SDN and NFV. We focus on solving two major problems: On the one hand, we lack
today of a model or template that describes the managed elements in the context
of SDN and NFV. On the other hand, the highly dynamic networks enabled by the
softwarisation require the generation at runtime of a diagnosis model from
which the root causes can be identified. In this paper, we propose finer
granular templates that do not only model network nodes but also their
sub-components for a more detailed diagnosis suitable in the SDN and NFV
context. In addition, we specify and validate a self-modeling based diagnosis
using Bayesian Networks. This approach differs from the state of the art in the
discovery of network and service dependencies at run-time and the building of
the diagnosis model of any SDN infrastructure using our templates
Parallel Architectures for Planetary Exploration Requirements (PAPER)
The Parallel Architectures for Planetary Exploration Requirements (PAPER) project is essentially research oriented towards technology insertion issues for NASA's unmanned planetary probes. It was initiated to complement and augment the long-term efforts for space exploration with particular reference to NASA/LaRC's (NASA Langley Research Center) research needs for planetary exploration missions of the mid and late 1990s. The requirements for space missions as given in the somewhat dated Advanced Information Processing Systems (AIPS) requirements document are contrasted with the new requirements from JPL/Caltech involving sensor data capture and scene analysis. It is shown that more stringent requirements have arisen as a result of technological advancements. Two possible architectures, the AIPS Proof of Concept (POC) configuration and the MAX Fault-tolerant dataflow multiprocessor, were evaluated. The main observation was that the AIPS design is biased towards fault tolerance and may not be an ideal architecture for planetary and deep space probes due to high cost and complexity. The MAX concepts appears to be a promising candidate, except that more detailed information is required. The feasibility for adding neural computation capability to this architecture needs to be studied. Key impact issues for architectural design of computing systems meant for planetary missions were also identified
Exploring Graphs with Time Constraints by Unreliable Collections of Mobile Robots
A graph environment must be explored by a collection of mobile robots. Some
of the robots, a priori unknown, may turn out to be unreliable. The graph is
weighted and each node is assigned a deadline. The exploration is successful if
each node of the graph is visited before its deadline by a reliable robot. The
edge weight corresponds to the time needed by a robot to traverse the edge.
Given the number of robots which may crash, is it possible to design an
algorithm, which will always guarantee the exploration, independently of the
choice of the subset of unreliable robots by the adversary? We find the optimal
time, during which the graph may be explored. Our approach permits to find the
maximal number of robots, which may turn out to be unreliable, and the graph is
still guaranteed to be explored.
We concentrate on line graphs and rings, for which we give positive results.
We start with the case of the collections involving only reliable robots. We
give algorithms finding optimal times needed for exploration when the robots
are assigned to fixed initial positions as well as when such starting positions
may be determined by the algorithm. We extend our consideration to the case
when some number of robots may be unreliable. Our most surprising result is
that solving the line exploration problem with robots at given positions, which
may involve crash-faulty ones, is NP-hard. The same problem has polynomial
solutions for a ring and for the case when the initial robots' positions on the
line are arbitrary.
The exploration problem is shown to be NP-hard for star graphs, even when the
team consists of only two reliable robots
A Dual Digraph Approach for Leaderless Atomic Broadcast (Extended Version)
Many distributed systems work on a common shared state; in such systems,
distributed agreement is necessary for consistency. With an increasing number
of servers, these systems become more susceptible to single-server failures,
increasing the relevance of fault-tolerance. Atomic broadcast enables
fault-tolerant distributed agreement, yet it is costly to solve. Most practical
algorithms entail linear work per broadcast message. AllConcur -- a leaderless
approach -- reduces the work, by connecting the servers via a sparse resilient
overlay network; yet, this resiliency entails redundancy, limiting the
reduction of work. In this paper, we propose AllConcur+, an atomic broadcast
algorithm that lifts this limitation: During intervals with no failures, it
achieves minimal work by using a redundancy-free overlay network. When failures
do occur, it automatically recovers by switching to a resilient overlay
network. In our performance evaluation of non-failure scenarios, AllConcur+
achieves comparable throughput to AllGather -- a non-fault-tolerant distributed
agreement algorithm -- and outperforms AllConcur, LCR and Libpaxos both in
terms of throughput and latency. Furthermore, our evaluation of failure
scenarios shows that AllConcur+'s expected performance is robust with regard to
occasional failures. Thus, for realistic use cases, leveraging redundancy-free
distributed agreement during intervals with no failures improves performance
significantly.Comment: Overview: 24 pages, 6 sections, 3 appendices, 8 figures, 3 tables.
Modifications from previous version: extended the evaluation of AllConcur+
with a simulation of a multiple datacenters deploymen
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