1,698 research outputs found
Byzantine Gathering in Polynomial Time
Gathering a group of mobile agents is a fundamental task in the field of distributed and mobile systems. This can be made drastically more difficult to achieve when some agents are subject to faults, especially the Byzantine ones that are known as being the worst faults to handle. In this paper we study, from a deterministic point of view, the task of Byzantine gathering in a network modeled as a graph. In other words, despite the presence of Byzantine agents, all the other (good) agents, starting from {possibly} different nodes and applying the same deterministic algorithm, have to meet at the same node in finite time and stop moving. An adversary chooses the initial nodes of the agents (the number of agents may be larger than the number of nodes) and assigns a different positive integer (called label) to each of them. Initially, each agent knows its label. The agents move in synchronous rounds and can communicate with each other only when located at the same node. Within the team, f of the agents are Byzantine. A Byzantine agent acts in an unpredictable and arbitrary way. For example, it can choose an arbitrary port when it moves, can convey arbitrary information to other agents and can change its label in every round, in particular by forging the label of another agent or by creating a completely new one.
Besides its label, which corresponds to a local knowledge, an agent is assigned some global knowledge denoted by GK that is common to all agents. In literature, the Byzantine gathering problem has been analyzed in arbitrary n-node graphs by considering the scenario when GK=(n,f) and the scenario when GK=f. In the first (resp. second) scenario, it has been shown that the minimum number of good agents guaranteeing deterministic gathering of all of them is f+1 (resp. f+2). However, for both these scenarios, all the existing deterministic algorithms, whether or not they are optimal in terms of required number of good agents, have the major disadvantage of having a time complexity that is exponential in n and L, where L is the value of the largest label belonging to a good agent. In this paper, we seek to design a deterministic solution for Byzantine gathering that makes a concession on the proportion of Byzantine agents within the team, but that offers a significantly lower complexity. We also seek to use a global knowledge whose the length of the binary representation (that we also call size) is small. In this respect, assuming that the agents are in a strong team i.e., a team in which the number of good agents is at least some prescribed value that is quadratic in f, we give positive and negative results. On the positive side, we show an algorithm that solves Byzantine gathering with all strong teams in all graphs of size at most n, for any integers n and f, in a time polynomial in n and the length |l_{min}| of the binary representation of the smallest label of a good agent. The algorithm works using a global knowledge of size O(log log log n), which is of optimal order of magnitude in our context to reach a time complexity that is polynomial in n and |l_{min}|. Indeed, on the negative side, we show that there is no deterministic algorithm solving Byzantine gathering with all strong teams, in all graphs of size at most n, in a time polynomial in n and |l_{min}| and using a global knowledge of size o(log log log n)
Byzantine Gathering in Polynomial Time
We study the task of Byzantine gathering in a network modeled as a graph.
Despite the presence of Byzantine agents, all the other (good) agents, starting
from possibly different nodes and applying the same deterministic algorithm,
have to meet at the same node in finite time and stop moving. An adversary
chooses the initial nodes of the agents and assigns a different label to each
of them. The agents move in synchronous rounds and communicate with each other
only when located at the same node. Within the team, f of the agents are
Byzantine. A Byzantine agent acts in an unpredictable way: in particular it may
forge the label of another agent or create a completely new one. Besides its
label, which corresponds to a local knowledge, an agent is assigned some global
knowledge GK that is common to all agents. In literature, the Byzantine
gathering problem has been analyzed in arbitrary n-node graphs by considering
the scenario when GK=(n,f) and the scenario when GK=f. In the first (resp.
second) scenario, it has been shown that the minimum number of good agents
guaranteeing deterministic gathering of all of them is f+1 (resp. f+2). For
both these scenarios, all the existing deterministic algorithms, whether or not
they are optimal in terms of required number of good agents, have a time
complexity that is exponential in n and L, where L is the largest label
belonging to a good agent.
In this paper, we seek to design a deterministic solution for Byzantine
gathering that makes a concession on the proportion of Byzantine agents within
the team, but that offers a significantly lower complexity. We also seek to use
a global knowledge whose the length of the binary representation is small.
Assuming that the agents are in a strong team i.e., a team in which the number
of good agents is at least some prescribed value that is quadratic in f, we
give positive and negative results
Byzantine Gathering in Networks
This paper investigates an open problem introduced in [14]. Two or more
mobile agents start from different nodes of a network and have to accomplish
the task of gathering which consists in getting all together at the same node
at the same time. An adversary chooses the initial nodes of the agents and
assigns a different positive integer (called label) to each of them. Initially,
each agent knows its label but does not know the labels of the other agents or
their positions relative to its own. Agents move in synchronous rounds and can
communicate with each other only when located at the same node. Up to f of the
agents are Byzantine. A Byzantine agent can choose an arbitrary port when it
moves, can convey arbitrary information to other agents and can change its
label in every round, in particular by forging the label of another agent or by
creating a completely new one.
What is the minimum number M of good agents that guarantees deterministic
gathering of all of them, with termination?
We provide exact answers to this open problem by considering the case when
the agents initially know the size of the network and the case when they do
not. In the former case, we prove M=f+1 while in the latter, we prove M=f+2.
More precisely, for networks of known size, we design a deterministic algorithm
gathering all good agents in any network provided that the number of good
agents is at least f+1. For networks of unknown size, we also design a
deterministic algorithm ensuring the gathering of all good agents in any
network but provided that the number of good agents is at least f+2. Both of
our algorithms are optimal in terms of required number of good agents, as each
of them perfectly matches the respective lower bound on M shown in [14], which
is of f+1 when the size of the network is known and of f+2 when it is unknown
Rendezvous in Networks in Spite of Delay Faults
Two mobile agents, starting from different nodes of an unknown network, have
to meet at the same node. Agents move in synchronous rounds using a
deterministic algorithm. Each agent has a different label, which it can use in
the execution of the algorithm, but it does not know the label of the other
agent. Agents do not know any bound on the size of the network. In each round
an agent decides if it remains idle or if it wants to move to one of the
adjacent nodes. Agents are subject to delay faults: if an agent incurs a fault
in a given round, it remains in the current node, regardless of its decision.
If it planned to move and the fault happened, the agent is aware of it. We
consider three scenarios of fault distribution: random (independently in each
round and for each agent with constant probability 0 < p < 1), unbounded adver-
sarial (the adversary can delay an agent for an arbitrary finite number of
consecutive rounds) and bounded adversarial (the adversary can delay an agent
for at most c consecutive rounds, where c is unknown to the agents). The
quality measure of a rendezvous algorithm is its cost, which is the total
number of edge traversals. For random faults, we show an algorithm with cost
polynomial in the size n of the network and polylogarithmic in the larger label
L, which achieves rendezvous with very high probability in arbitrary networks.
By contrast, for unbounded adversarial faults we show that rendezvous is not
feasible, even in the class of rings. Under this scenario we give a rendezvous
algorithm with cost O(nl), where l is the smaller label, working in arbitrary
trees, and we show that \Omega(l) is the lower bound on rendezvous cost, even
for the two-node tree. For bounded adversarial faults, we give a rendezvous
algorithm working for arbitrary networks, with cost polynomial in n, and
logarithmic in the bound c and in the larger label L
Byzantine Agreement with Optimal Early Stopping, Optimal Resilience and Polynomial Complexity
We provide the first protocol that solves Byzantine agreement with optimal
early stopping ( rounds) and optimal resilience () using
polynomial message size and computation.
All previous approaches obtained sub-optimal results and used resolve rules
that looked only at the immediate children in the EIG (\emph{Exponential
Information Gathering}) tree. At the heart of our solution are new resolve
rules that look at multiple layers of the EIG tree.Comment: full version of STOC 2015 abstrac
Certified Universal Gathering in for Oblivious Mobile Robots
We present a unified formal framework for expressing mobile robots models,
protocols, and proofs, and devise a protocol design/proof methodology dedicated
to mobile robots that takes advantage of this formal framework. As a case
study, we present the first formally certified protocol for oblivious mobile
robots evolving in a two-dimensional Euclidean space. In more details, we
provide a new algorithm for the problem of universal gathering mobile oblivious
robots (that is, starting from any initial configuration that is not bivalent,
using any number of robots, the robots reach in a finite number of steps the
same position, not known beforehand) without relying on a common orientation
nor chirality. We give very strong guaranties on the correctness of our
algorithm by proving formally that it is correct, using the COQ proof
assistant. This result demonstrates both the effectiveness of the approach to
obtain new algorithms that use as few assumptions as necessary, and its
manageability since the amount of developed code remains human readable.Comment: arXiv admin note: substantial text overlap with arXiv:1506.0160
- …