ABSTRACTS
Adaptive Multi-Agent Real-Time Operating System
K. S Amelin, M. V. Baklanovskiy, O. N. Granichin, Y. V. Ivanskiy, A. D.
Kornivets, N. V. Mal’kovskiy, D. G. Naidanov, R. Y. Shein
(konstantinamelin,
oleg_granichin)@mail.ru
Key words: adaptive systems, multi-agent systems, real-time operating system.
The development of
computer technology is moving from rising the clock frequency and the
performance of a single processor towards multi-core parallelism and
integration of the individual processors into a complex. However the approach
based on combining the computing nodes into a single system has its own
drawbacks. Such systems have a rigid hierarchy which limits the scope of their
efficient use, since the particular configuration of the computer system is
targeted at solving a specific range of tasks. Next, failure of a small number
of nodes at the upper levels of the hierarchy can affect the functioning of the
entire system. In addition, when planning the load of computing nodes, serious
difficulties arise due to the large number of nodes and complex switching
rules. To overcome such difficulties in the construction of large-scale
systems, the ideology of multi-agent systems becomes popular. Such systems do
not assume the existence of a priori structured links between the elements
(agents), and each element has certain autonomy and is capable of forming new
links with other agents in the process of solving a problem.
The paper describes the main
features of the new project by the authors which is aimed at the development of
the prototype of a new real-time operating system (OS) targeted at properly
scheduling the work of complexes consisting of a large number of computing
nodes which are built on the principles of the multi-agent technology. Such
decentralized OS should ensure the efficient load of computing devices and have
the ability to change the topology of the network caused both by on-line
network re-structuring and possible losses and/or acquisition of nodes.
Bibliogr.: 8 refs.
Scheduling in Stochastic Wireless Multihop Networks
N. O. Amelina, K. S. Amelin
D. J. Vergados
Norwegian
(natalia_amelina,
konstantinamelin)@mail.ru, djvergad@gmail.com
Key words: consensus problem, wireless multihop networks, scheduling, load
balancing.
One of the challenges in
wireless multihop networks is the problem of scheduling transmissions in an
efficient and fair manner. The performance of a scheduling algorithm is closely
related to its ability to adapt to the changing traffic conditions. Although
theoretical results have been obtained regarding the capacity of wireless
multihop networks, analytic results on the interaction of load balancing and
scheduling algorithms have yet to be derived. In this paper we consider a
stochastic wireless multihop network of nonlinear nodes with switching
topology, noisy and delayed measurements. The problem of wireless scheduling
was modeled as a load balancing problem and the consensus protocol was
suggested to solve it. Conditions for an approximate consensus that gives an
almost optimal behavior of the system were provided. Through analysis and
simulation, we evaluate the performance of various scheduling algorithms. We
show that load balancing improves the delay and fairness of the system.
Bibliogr.: 23 refs.
3D-Image Recovery from Compressed Ultrasonography Data
Y. V. Ivanskiy,
Key words: compressive sensing, compressive sampling, randomized measurements, ℓ1-optimization,
ultrasonography.
The paper considers the
applicability of compressed sensing to the reduction of the amount of channels
connecting ultrasound transducers and the processing unit. The conceptual simulation
model of ultrasound scanner was designed and implemented. The model provides
compression, transmission, and recovery of signals generated from the
ultrasonography data. A number of experiments with different parameters were
performed. The results show the capabilities of the compressed sensing approach
in the problem under consideration and the quality of ultrasonography data
reconstruction at the processing unit.
Bibliogr.: 20 refs.
Determination of the Coordinates of Flying Vehicles
from the Range-Difference Measurements Subject to Individual Systematic Errors
Y. K. Kisin,
Key words: measurements, range difference, systematic errors, algorithm,
trajectory.
The paper addresses the
problem of determining the coordinates of an flying vehicles from the
range-difference measurements corrupted by systematic errors in every range
difference. The results are illustrated via simulation examples.
Bibliogr.: 9 refs.
On Exact Confidence Regions under External Arbitrary
Noise Within the Context of Linear Recommender System
A. A. Senov,
Key words: linear regression, confidence intervals, sign-perturbed sums,
randomization.
The paper presents a new
finite sample method for identifying non-asymptotic confidence sets for
multiple linear regression parameters, referred to as Modified Sign-Perturbed
Sums (MSPS), for almost arbitrary noise. The MSPS method is a modification of
the Sign-Perturbed Sums (SPS) method (proposed earlier by Csaji B.C., Campi
M.C., Weyer E.), with generalization to the case of arbitrary noise, typical to
data in recommendation systems. The SPS and MSPS methods are compared on both
simulated and real data. Statistical properties of confidence intervals are
discussed. An analytical expression of confidence sets is given. The advantages
of the MSPS method are illustrated.
Bibliogr.: 25 refs.
An Effective Construction of Genetic Maps from
Completely Sequenced Genome Sections
S. S. Sysoev,
Key words: genetic linkage, linkage maps, sequenation, algorithm, pheno-type
mapping.
A new approach is proposed to the
construction of genetic maps from completely sequenced portions of data
(markers). An algorithmic implementation of the approach using the Python
environment is provided. Preliminary testing results from the genetic data for
a set of cats with 35 markers are presented.
Bibliogr.: 8 refs.
An LMI-approach to the Design of Stabilizing Bounded
Control for Linear Systems1
M. V. Khlebnikov,
P. S. Shcherbakov
mkhlebnikov2008@yandex.ru, cavour118@mail.ru
Key words: linear control systems, linear matrix inequalities bounded control,
linear quadratic regulator.
Using the linear matrix
inequalities technique, a stabilizing linear static state feedback is designed
for linear systems under the constraint on the magnitude of the control signal.
A quadratic functional is then constructed such that it is minimized with the
designed control.
Bibliogr.: 12 refs.
On Abstract Analysis of Fuzzy Minimax Automata Models
V. A. Khokhulina,
M. K. Chirkov
Key words: fuzzy automata models, fuzzy minimax automata, fuzzy languages,
equivalence, special method of analysis.
In the paper, a special
method of abstract analysis of fuzzy minimax automata is presented, by which
means decisions can be made on general and special analysis tasks of this type of
automata. The method is based on the equivalence of languages represented by
different types of fuzzy automata and on the possibility of their decomposition
on fuzziness degrees. This makes it possible to reduce abstract analysis of
fuzzy minimax automata models to that of maximin automata, for which there
exist solutions procedures. Examples are given.
Bibliogr.: 10 refs.
Optimal Synthesis of Nonstationary Nondeterministic
M. K. Chirkov,
Key words: nondeterministic automata, nonstationary automata, optimal synthesis
of automata, optimal behavior, fuzzy functioning conditions.
The paper deals with the
design of nonstationary nondeterministic finite state automaton that maximizes
the performance index under fuzzy conditions; the additional optimality
criterion is the number of states of the automaton. A general design procedure
is proposed and an example is discussed.
Bibliogr.: 7 refs.
Two-Level
Metrics and a New Concept of Machine Learning
V. N. Shats,
Key words: machine learning; self-organizing system; metric; supervised learning;
learning without a teacher.
We develop a new concept
of machine learning associated with a multi-step mechanism of processing
external information in self-organizing systems. This concept is based on a
two-level conformity metrics between the object and a class of plants. In
accordance with this metrics, for each of the individual attributes and the
overall set of them, we evaluate the probability that an object belongs to a
given class; to determine the class, the maximum likelihood method is used. The
metrics is implemented as a module having simple calculation algorithm.
Essentially, the problems of learning with or without a teacher reduce to the
calling to the module. The efficiency of the concept is shown via applications
to specific problems.
Bibliogr.: 13 refs.
P. T. Stoynov,
Sofia,
Bulgaria
Key words: surplus processes,
reflected surplus processes, budget restriction.
In this paper we
consider a risk model based on reflected surplus processes. This kind of processes
can represent the surplus of companies with steady outflows and sporadic
inflows. We consider the case where the company can adjust its expense rate by
reducing it if no inflow is made by a random time with a specific distribution
following the last inflow.
Bibliogr.: 7 refs.