2,458 research outputs found
Optimal byzantine resilient convergence in oblivious robot networks
Given a set of robots with arbitrary initial location and no agreement on a
global coordinate system, convergence requires that all robots asymptotically
approach the exact same, but unknown beforehand, location. Robots are
oblivious-- they do not recall the past computations -- and are allowed to move
in a one-dimensional space. Additionally, robots cannot communicate directly,
instead they obtain system related information only via visual sensors. We draw
a connection between the convergence problem in robot networks, and the
distributed \emph{approximate agreement} problem (that requires correct
processes to decide, for some constant , values distance
apart and within the range of initial proposed values). Surprisingly, even
though specifications are similar, the convergence implementation in robot
networks requires specific assumptions about synchrony and Byzantine
resilience. In more details, we prove necessary and sufficient conditions for
the convergence of mobile robots despite a subset of them being Byzantine (i.e.
they can exhibit arbitrary behavior). Additionally, we propose a deterministic
convergence algorithm for robot networks and analyze its correctness and
complexity in various synchrony settings. The proposed algorithm tolerates f
Byzantine robots for (2f+1)-sized robot networks in fully synchronous networks,
(3f+1)-sized in semi-synchronous networks. These bounds are optimal for the
class of cautious algorithms, which guarantee that correct robots always move
inside the range of positions of the correct robots
Optimal Byzantine Resilient Convergence in Asynchronous Robot Networks
We propose the first deterministic algorithm that tolerates up to
byzantine faults in -sized networks and performs in the asynchronous
CORDA model. Our solution matches the previously established lower bound for
the semi-synchronous ATOM model on the number of tolerated Byzantine robots.
Our algorithm works under bounded scheduling assumptions for oblivious robots
moving in a uni-dimensional space
Fault-Tolerant Dispersion of Mobile Robots
We consider the mobile robot dispersion problem in the presence of faulty
robots (crash-fault). Mobile robot dispersion consists of robots in
an -node anonymous graph. The goal is to ensure that regardless of the
initial placement of the robots over the nodes, the final configuration
consists of having at most one robot at each node. In a crash-fault setting, up
to robots may fail by crashing arbitrarily and subsequently lose all
the information stored at the robots, rendering them unable to communicate. In
this paper, we solve the dispersion problem in a crash-fault setting by
considering two different initial configurations: i) the rooted configuration,
and ii) the arbitrary configuration. In the rooted case, all robots are placed
together at a single node at the start. The arbitrary configuration is a
general configuration (a.k.a. arbitrary configuration in the literature) where
the robots are placed in some clusters arbitrarily across the graph. For
the first case, we develop an algorithm solving dispersion in the presence of
faulty robots in rounds, which improves over the previous
-round result by \cite{PS021}. For the
arbitrary configuration, we present an algorithm solving dispersion in
rounds, when the number of edges
and the maximum degree of the graph is known to the robots
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