3,680 research outputs found
Secure and Privacy-Preserving Average Consensus
Average consensus is fundamental for distributed systems since it underpins
key functionalities of such systems ranging from distributed information
fusion, decision-making, to decentralized control. In order to reach an
agreement, existing average consensus algorithms require each agent to exchange
explicit state information with its neighbors. This leads to the disclosure of
private state information, which is undesirable in cases where privacy is of
concern. In this paper, we propose a novel approach that enables secure and
privacy-preserving average consensus in a decentralized architecture in the
absence of any trusted third-parties. By leveraging homomorphic cryptography,
our approach can guarantee consensus to the exact value in a deterministic
manner. The proposed approach is light-weight in computation and communication,
and applicable to time-varying interaction topology cases. A hardware
implementation is presented to demonstrate the capability of our approach.Comment: 7 pages, 4 figures, paper is accepted to CPS-SPC'1
Optimal strategies in the average consensus problem
We prove that for a set of communicating agents to compute the average of
their initial positions (average consensus problem), the optimal topology of
communication is given by a de Bruijn's graph. Consensus is then reached in a
finitely many steps. A more general family of strategies, constructed by block
Kronecker products, is investigated and compared to Cayley strategies.Comment: 9 pages; extended preprint with proofs of a CDC 2007 (Conference on
decision and Control) pape
Discontinuities and hysteresis in quantized average consensus
We consider continuous-time average consensus dynamics in which the agents'
states are communicated through uniform quantizers. Solutions to the resulting
system are defined in the Krasowskii sense and are proven to converge to
conditions of "practical consensus". To cope with undesired chattering
phenomena we introduce a hysteretic quantizer, and we study the convergence
properties of the resulting dynamics by a hybrid system approach.Comment: 26 pages, 7 figures. Accepted for publication in Automatica. v4 is
minor revision of v
Distributed Change Detection via Average Consensus over Networks
Distributed change-point detection has been a fundamental problem when
performing real-time monitoring using sensor-networks. We propose a distributed
detection algorithm, where each sensor only exchanges CUSUM statistic with
their neighbors based on the average consensus scheme, and an alarm is raised
when local consensus statistic exceeds a pre-specified global threshold. We
provide theoretical performance bounds showing that the performance of the
fully distributed scheme can match the centralized algorithms under some mild
conditions. Numerical experiments demonstrate the good performance of the
algorithm especially in detecting asynchronous changes.Comment: 15 pages, 8 figure
Real-valued average consensus over noisy quantized channels
This paper concerns the average consensus problem
with the constraint of quantized communication between
nodes. A broad class of algorithms is analyzed, in which the
transmission strategy, which decides what value to communicate
to the neighbours, can include various kinds of rounding, probabilistic
quantization, and bounded noise. The arbitrariness
of the transmission strategy is compensated by a feedback
mechanism which can be interpreted as a self-inhibitory action.
The result is that the average of the nodes state is not conserved
across iterations, and the nodes do not converge to a consensus;
however, we show that both errors can be made as small
as desired. Bounds on these quantities involve the spectral
properties of the graph and can be proved by employing
elementary techniques of LTI systems analysis
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