2,499 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
Hybrid Tractable Classes of Binary Quantified Constraint Satisfaction Problems
In this paper, we investigate the hybrid tractability of binary Quantified
Constraint Satisfaction Problems (QCSPs). First, a basic tractable class of
binary QCSPs is identified by using the broken-triangle property. In this
class, the variable ordering for the broken-triangle property must be same as
that in the prefix of the QCSP. Second, we break this restriction to allow that
existentially quantified variables can be shifted within or out of their
blocks, and thus identify some novel tractable classes by introducing the
broken-angle property. Finally, we identify a more generalized tractable class,
i.e., the min-of-max extendable class for QCSPs
- …