1,872 research outputs found
Decentralized Observability with Limited Communication between Sensors
In this paper, we study the problem of jointly retrieving the state of a
dynamical system, as well as the state of the sensors deployed to estimate it.
We assume that the sensors possess a simple computational unit that is capable
of performing simple operations, such as retaining the current state and model
of the system in its memory.
We assume the system to be observable (given all the measurements of the
sensors), and we ask whether each sub-collection of sensors can retrieve the
state of the underlying physical system, as well as the state of the remaining
sensors. To this end, we consider communication between neighboring sensors,
whose adjacency is captured by a communication graph. We then propose a linear
update strategy that encodes the sensor measurements as states in an augmented
state space, with which we provide the solution to the problem of retrieving
the system and sensor states.
The present paper contains three main contributions. First, we provide
necessary and sufficient conditions to ensure observability of the system and
sensor states from any sensor. Second, we address the problem of adding
communication between sensors when the necessary and sufficient conditions are
not satisfied, and devise a strategy to this end. Third, we extend the former
case to include different costs of communication between sensors. Finally, the
concepts defined and the method proposed are used to assess the state of an
example of approximate structural brain dynamics through linearized
measurements.Comment: 15 pages, 5 figures, extended version of paper accepted at IEEE
Conference on Decision and Control 201
Bicriteria Network Design Problems
We study a general class of bicriteria network design problems. A generic
problem in this class is as follows: Given an undirected graph and two
minimization objectives (under different cost functions), with a budget
specified on the first, find a <subgraph \from a given subgraph-class that
minimizes the second objective subject to the budget on the first. We consider
three different criteria - the total edge cost, the diameter and the maximum
degree of the network. Here, we present the first polynomial-time approximation
algorithms for a large class of bicriteria network design problems for the
above mentioned criteria. The following general types of results are presented.
First, we develop a framework for bicriteria problems and their
approximations. Second, when the two criteria are the same %(note that the cost
functions continue to be different) we present a ``black box'' parametric
search technique. This black box takes in as input an (approximation) algorithm
for the unicriterion situation and generates an approximation algorithm for the
bicriteria case with only a constant factor loss in the performance guarantee.
Third, when the two criteria are the diameter and the total edge costs we use a
cluster-based approach to devise a approximation algorithms --- the solutions
output violate both the criteria by a logarithmic factor. Finally, for the
class of treewidth-bounded graphs, we provide pseudopolynomial-time algorithms
for a number of bicriteria problems using dynamic programming. We show how
these pseudopolynomial-time algorithms can be converted to fully
polynomial-time approximation schemes using a scaling technique.Comment: 24 pages 1 figur
Blockchain-based secret key extraction for efficient and secure authentication in VANETs
Intelligent transportation systems are an emerging technology that facilitates real-time vehicle-to-everything communication. Hence, securing and authenticating data packets for intra- and inter-vehicle communication are fundamental security services in vehicular ad-hoc networks (VANETs). However, public-key cryptography (PKC) is commonly used in signature-based authentication, which consumes significant computation resources and communication bandwidth for signatures generation and verification, and key distribution. Therefore, physical layer-based secret key extraction has emerged as an effective candidate for key agreement, exploiting the randomness and reciprocity features of wireless channels. However, the imperfect channel reciprocity generates discrepancies in the extracted key, and existing reconciliation algorithms suffer from significant communication costs and security issues. In this paper,
PKC-based authentication is used for initial legitimacy detection and exchanging authenticated probing packets. Accordingly, we propose a blockchain-based reconciliation technique that allows the trusted third party (TTP) to publish the correction sequence of the mismatched bits through a transaction using a smart contract. The smart contract functions enable the TTP to map the transaction address to vehicle-related information and allow vehicles to obtain the transaction contents securely. The obtained shared key is then used for symmetric key cryptography (SKC)-based authentication for subsequent transmissions, saving significant computation and communication costs. The correctness and security robustness of the scheme are proved using Burrows–Abadi–Needham (BAN)-logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) simulator. We also discussed the scheme’s resistance to typical attacks. The scheme’s performance in terms of packet delay and loss ratio is evaluated using the network simulator (OMNeT++). Finally, the computation analysis shows that the scheme saves ~99% of the time required to verify 1000 messages compared to existing PKC-based schemes
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