539 research outputs found
Fast Consensus under Eventually Stabilizing Message Adversaries
This paper is devoted to deterministic consensus in synchronous dynamic
networks with unidirectional links, which are under the control of an
omniscient message adversary. Motivated by unpredictable node/system
initialization times and long-lasting periods of massive transient faults, we
consider message adversaries that guarantee periods of less erratic message
loss only eventually: We present a tight bound of for the termination
time of consensus under a message adversary that eventually guarantees a single
vertex-stable root component with dynamic network diameter , as well as a
simple algorithm that matches this bound. It effectively halves the termination
time achieved by an existing consensus algorithm, which also works under
our message adversary. We also introduce a generalized, considerably stronger
variant of our message adversary, and show that our new algorithm, unlike the
existing one, still works correctly under it.Comment: 13 pages, 5 figures, updated reference
Gracefully Degrading Gathering in Dynamic Rings
Gracefully degrading algorithms [Biely \etal, TCS 2018] are designed to
circumvent impossibility results in dynamic systems by adapting themselves to
the dynamics. Indeed, such an algorithm solves a given problem under some
dynamics and, moreover, guarantees that a weaker (but related) problem is
solved under a higher dynamics under which the original problem is impossible
to solve. The underlying intuition is to solve the problem whenever possible
but to provide some kind of quality of service if the dynamics become
(unpredictably) higher.In this paper, we apply for the first time this approach
to robot networks. We focus on the fundamental problem of gathering a squad of
autonomous robots on an unknown location of a dynamic ring. In this goal, we
introduce a set of weaker variants of this problem. Motivated by a set of
impossibility results related to the dynamics of the ring, we propose a
gracefully degrading gathering algorithm
Building a generalized distributed system model
The key elements in the second year (1991-92) of our project are: (1) implementation of the distributed system prototype; (2) successful passing of the candidacy examination and a PhD proposal acceptance by the funded student; (3) design of storage efficient schemes for replicated distributed systems; and (4) modeling of gracefully degrading reliable computing systems. In the third year of the project (1992-93), we propose to: (1) complete the testing of the prototype; (2) enhance the functionality of the modules by enabling the experimentation with more complex protocols; (3) use the prototype to verify the theoretically predicted performance of locking protocols, etc.; and (4) work on issues related to real-time distributed systems. This should result in efficient protocols for these systems
Gracefully Degrading Gathering in Dynamic Rings
Gracefully degrading algorithms [Biely \etal, TCS 2018] are designed to circumvent impossibility results in dynamic systems by adapting themselves to the dynamics. Indeed, such an algorithm solves a given problem under some dynamics and, moreover, guarantees that a weaker (but related) problem is solved under a higher dynamics under which the original problem is impossible to solve. The underlying intuition is to solve the problem whenever possible but to provide some kind of quality of service if the dynamics become (unpredictably) higher.In this paper, we apply for the first time this approach to robot networks. We focus on the fundamental problem of gathering a squad of autonomous robots on an unknown location of a dynamic ring. In this goal, we introduce a set of weaker variants of this problem. Motivated by a set of impossibility results related to the dynamics of the ring, we propose a gracefully degrading gathering algorithm
Solving k-Set Agreement Using Failure Detectors in Unknown Dynamic Networks
International audienceThe failure detector abstraction has been used to solve agreement problems in asynchronous systems prone to crash failures, but so far it has mostly been used in static and complete networks. This paper aims to adapt existing failure detectors in order to solve agreement problems in unknown, dynamic systems. We are specifically interested in the k-set agreement problem. The problem of k-set agreement is a generalization of consensus where processes can decide up to k different values. Although some solutions to this problem have been proposed in dynamic networks, they rely on communication synchrony or make strong assumptions on the number of process failures. In this paper we consider unknown dynamic systems modeled using the formalism of Time-Varying Graphs, and extend the definition of the existing ΠΣx,y failure detector to obtain the ΠΣ ⊥,x,y failure detector, which is sufficient to solve k-set agreement in our model. We then provide an implementation of this new failure detector using connectivity and message pattern assumptions. Finally, we present an algorithm using ΠΣ ⊥,x,y to solve k-set agreement
Gathering in Dynamic Rings
The gathering problem requires a set of mobile agents, arbitrarily positioned
at different nodes of a network to group within finite time at the same
location, not fixed in advanced.
The extensive existing literature on this problem shares the same fundamental
assumption: the topological structure does not change during the rendezvous or
the gathering; this is true also for those investigations that consider faulty
nodes. In other words, they only consider static graphs. In this paper we start
the investigation of gathering in dynamic graphs, that is networks where the
topology changes continuously and at unpredictable locations.
We study the feasibility of gathering mobile agents, identical and without
explicit communication capabilities, in a dynamic ring of anonymous nodes; the
class of dynamics we consider is the classic 1-interval-connectivity.
We focus on the impact that factors such as chirality (i.e., a common sense
of orientation) and cross detection (i.e., the ability to detect, when
traversing an edge, whether some agent is traversing it in the other
direction), have on the solvability of the problem. We provide a complete
characterization of the classes of initial configurations from which the
gathering problem is solvable in presence and in absence of cross detection and
of chirality. The feasibility results of the characterization are all
constructive: we provide distributed algorithms that allow the agents to
gather. In particular, the protocols for gathering with cross detection are
time optimal. We also show that cross detection is a powerful computational
element.
We prove that, without chirality, knowledge of the ring size is strictly more
powerful than knowledge of the number of agents; on the other hand, with
chirality, knowledge of n can be substituted by knowledge of k, yielding the
same classes of feasible initial configurations
Consensus in Networks Prone to Link Failures
We consider deterministic distributed algorithms solving Consensus in
synchronous networks of arbitrary topologies. Links are prone to failures.
Agreement is understood as holding in each connected component of a network
obtained by removing faulty links. We introduce the concept of stretch, which
is a function of the number of connected components of a network and their
respective diameters. Fast and early-stopping algorithms solving Consensus are
defined by referring to stretch resulting in removing faulty links. We develop
algorithms that rely only on nodes knowing their own names and the ability to
associate communication with local ports. A network has nodes and it starts
with functional links. We give a general algorithm operating in time
that uses messages of bits. If we additionally restrict executions
to be subject to a bound on stretch, then there is a fast algorithm
solving Consensus in time using messages of bits. Let
be an unknown stretch occurring in an execution; we give an algorithm
working in time and using messages of bits. We
show that Consensus can be solved in the optimal time, but at the
cost of increasing message size to . We also demonstrate how to
solve Consensus by an algorithm that uses only non-faulty links and
works in time , while nodes start with their ports mapped to neighbors
and messages carry bits. We prove lower bounds on performance of
Consensus solutions that refer to parameters of evolving network topologies and
the knowledge available to nodes
- …