20,592 research outputs found
Minimizing Message Size in Stochastic Communication Patterns: Fast Self-Stabilizing Protocols with 3 bits
This paper considers the basic model of communication, in
which in each round, each agent extracts information from few randomly chosen
agents. We seek to identify the smallest amount of information revealed in each
interaction (message size) that nevertheless allows for efficient and robust
computations of fundamental information dissemination tasks. We focus on the
Majority Bit Dissemination problem that considers a population of agents,
with a designated subset of source agents. Each source agent holds an input bit
and each agent holds an output bit. The goal is to let all agents converge
their output bits on the most frequent input bit of the sources (the majority
bit). Note that the particular case of a single source agent corresponds to the
classical problem of Broadcast. We concentrate on the severe fault-tolerant
context of self-stabilization, in which a correct configuration must be reached
eventually, despite all agents starting the execution with arbitrary initial
states.
We first design a general compiler which can essentially transform any
self-stabilizing algorithm with a certain property that uses -bits
messages to one that uses only -bits messages, while paying only a
small penalty in the running time. By applying this compiler recursively we
then obtain a self-stabilizing Clock Synchronization protocol, in which agents
synchronize their clocks modulo some given integer , within rounds w.h.p., and using messages that contain bits only.
We then employ the new Clock Synchronization tool to obtain a
self-stabilizing Majority Bit Dissemination protocol which converges in time, w.h.p., on every initial configuration, provided that the
ratio of sources supporting the minority opinion is bounded away from half.
Moreover, this protocol also uses only 3 bits per interaction.Comment: 28 pages, 4 figure
Self-stabilizing cluster routing in Manet using link-cluster architecture
We design a self-stabilizing cluster routing algorithm based on the link-cluster architecture of wireless ad hoc networks. The network is divided into clusters. Each cluster has a single special node, called a clusterhead that contains the routing information about inter and intra-cluster communication. A cluster is comprised of all nodes that choose the corresponding clusterhead as their leader. The algorithm consists of two main tasks. First, the set of special nodes (clusterheads) is elected such that it models the link-cluster architecture: any node belongs to a single cluster, it is within two hops of the clusterhead, it knows the direct neighbor on the shortest path towards the clusterhead, and there exist no two adjacent clusterheads. Second, the routing tables are maintained by the clusterheads to store information about nodes both within and outside the cluster. There are two advantages of maintaining routing tables only in the clusterheads. First, as no two neighboring nodes are clusterheads (as per the link-cluster architecture), there is no need to check the consistency of the routing tables. Second, since all other nodes have significantly less work (they only forward messages), they use much less power than the clusterheads. Therefore, if a clusterhead runs out of power, a neighboring node (that is not a clusterhead) can accept the role of a clusterhead. (Abstract shortened by UMI.)
Global Versus Local Computations: Fast Computing with Identifiers
This paper studies what can be computed by using probabilistic local
interactions with agents with a very restricted power in polylogarithmic
parallel time. It is known that if agents are only finite state (corresponding
to the Population Protocol model by Angluin et al.), then only semilinear
predicates over the global input can be computed. In fact, if the population
starts with a unique leader, these predicates can even be computed in a
polylogarithmic parallel time. If identifiers are added (corresponding to the
Community Protocol model by Guerraoui and Ruppert), then more global predicates
over the input multiset can be computed. Local predicates over the input sorted
according to the identifiers can also be computed, as long as the identifiers
are ordered. The time of some of those predicates might require exponential
parallel time. In this paper, we consider what can be computed with Community
Protocol in a polylogarithmic number of parallel interactions. We introduce the
class CPPL corresponding to protocols that use , for some k,
expected interactions to compute their predicates, or equivalently a
polylogarithmic number of parallel expected interactions. We provide some
computable protocols, some boundaries of the class, using the fact that the
population can compute its size. We also prove two impossibility results
providing some arguments showing that local computations are no longer easy:
the population does not have the time to compare a linear number of consecutive
identifiers. The Linearly Local languages, such that the rational language
, are not computable.Comment: Long version of SSS 2016 publication, appendixed version of SIROCCO
201
Universal Protocols for Information Dissemination Using Emergent Signals
We consider a population of agents which communicate with each other in a
decentralized manner, through random pairwise interactions. One or more agents
in the population may act as authoritative sources of information, and the
objective of the remaining agents is to obtain information from or about these
source agents. We study two basic tasks: broadcasting, in which the agents are
to learn the bit-state of an authoritative source which is present in the
population, and source detection, in which the agents are required to decide if
at least one source agent is present in the population or not.We focus on
designing protocols which meet two natural conditions: (1) universality, i.e.,
independence of population size, and (2) rapid convergence to a correct global
state after a reconfiguration, such as a change in the state of a source agent.
Our main positive result is to show that both of these constraints can be met.
For both the broadcasting problem and the source detection problem, we obtain
solutions with a convergence time of rounds, w.h.p., from any
starting configuration. The solution to broadcasting is exact, which means that
all agents reach the state broadcast by the source, while the solution to
source detection admits one-sided error on a -fraction of the
population (which is unavoidable for this problem). Both protocols are easy to
implement in practice and have a compact formulation.Our protocols exploit the
properties of self-organizing oscillatory dynamics. On the hardness side, our
main structural insight is to prove that any protocol which meets the
constraints of universality and of rapid convergence after reconfiguration must
display a form of non-stationary behavior (of which oscillatory dynamics are an
example). We also observe that the periodicity of the oscillatory behavior of
the protocol, when present, must necessarily depend on the number ^\\# X of
source agents present in the population. For instance, our protocols inherently
rely on the emergence of a signal passing through the population, whose period
is \Theta(\log \frac{n}{^\\# X}) rounds for most starting configurations. The
design of clocks with tunable frequency may be of independent interest, notably
in modeling biological networks
Population stability: regulating size in the presence of an adversary
We introduce a new coordination problem in distributed computing that we call
the population stability problem. A system of agents each with limited memory
and communication, as well as the ability to replicate and self-destruct, is
subjected to attacks by a worst-case adversary that can at a bounded rate (1)
delete agents chosen arbitrarily and (2) insert additional agents with
arbitrary initial state into the system. The goal is perpetually to maintain a
population whose size is within a constant factor of the target size . The
problem is inspired by the ability of complex biological systems composed of a
multitude of memory-limited individual cells to maintain a stable population
size in an adverse environment. Such biological mechanisms allow organisms to
heal after trauma or to recover from excessive cell proliferation caused by
inflammation, disease, or normal development.
We present a population stability protocol in a communication model that is a
synchronous variant of the population model of Angluin et al. In each round,
pairs of agents selected at random meet and exchange messages, where at least a
constant fraction of agents is matched in each round. Our protocol uses
three-bit messages and states per agent. We emphasize that
our protocol can handle an adversary that can both insert and delete agents, a
setting in which existing approximate counting techniques do not seem to apply.
The protocol relies on a novel coloring strategy in which the population size
is encoded in the variance of the distribution of colors. Individual agents can
locally obtain a weak estimate of the population size by sampling from the
distribution, and make individual decisions that robustly maintain a stable
global population size
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