7,964 research outputs found
Stable Leader Election in Population Protocols Requires Linear Time
A population protocol *stably elects a leader* if, for all , starting from
an initial configuration with agents each in an identical state, with
probability 1 it reaches a configuration that is correct (exactly
one agent is in a special leader state ) and stable (every configuration
reachable from also has a single agent in state ). We show
that any population protocol that stably elects a leader requires
expected "parallel time" --- expected total pairwise interactions
--- to reach such a stable configuration. Our result also informs the
understanding of the time complexity of chemical self-organization by showing
an essential difficulty in generating exact quantities of molecular species
quickly.Comment: accepted to Distributed Computing special issue of invited papers
from DISC 2015; significantly revised proof structure and intuitive
explanation
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.)
Communication Efficient Self-Stabilizing Leader Election
This paper presents a randomized self-stabilizing algorithm that elects a leader r in a general n-node undirected graph and constructs a spanning tree T rooted at r. The algorithm works under the synchronous message passing network model, assuming that the nodes know a linear upper bound on n and that each edge has a unique ID known to both its endpoints (or, alternatively, assuming the KT? model). The highlight of this algorithm is its superior communication efficiency: It is guaranteed to send a total of O? (n) messages, each of constant size, till stabilization, while stabilizing in O? (n) rounds, in expectation and with high probability. After stabilization, the algorithm sends at most one constant size message per round while communicating only over the (n - 1) edges of T. In all these aspects, the communication overhead of the new algorithm is far smaller than that of the existing (mostly deterministic) self-stabilizing leader election algorithms.
The algorithm is relatively simple and relies mostly on known modules that are common in the fault free leader election literature; these modules are enhanced in various subtle ways in order to assemble them into a communication efficient self-stabilizing algorithm
Polynomial-Time Space-Optimal Silent Self-Stabilizing Minimum-Degree Spanning Tree Construction
Motivated by applications to sensor networks, as well as to many other areas,
this paper studies the construction of minimum-degree spanning trees. We
consider the classical node-register state model, with a weakly fair scheduler,
and we present a space-optimal \emph{silent} self-stabilizing construction of
minimum-degree spanning trees in this model. Computing a spanning tree with
minimum degree is NP-hard. Therefore, we actually focus on constructing a
spanning tree whose degree is within one from the optimal. Our algorithm uses
registers on bits, converges in a polynomial number of rounds, and
performs polynomial-time computation at each node. Specifically, the algorithm
constructs and stabilizes on a special class of spanning trees, with degree at
most . Indeed, we prove that, unless NP coNP, there are no
proof-labeling schemes involving polynomial-time computation at each node for
the whole family of spanning trees with degree at most . Up to our
knowledge, this is the first example of the design of a compact silent
self-stabilizing algorithm constructing, and stabilizing on a subset of optimal
solutions to a natural problem for which there are no time-efficient
proof-labeling schemes. On our way to design our algorithm, we establish a set
of independent results that may have interest on their own. In particular, we
describe a new space-optimal silent self-stabilizing spanning tree
construction, stabilizing on \emph{any} spanning tree, in rounds, and
using just \emph{one} additional bit compared to the size of the labels used to
certify trees. We also design a silent loop-free self-stabilizing algorithm for
transforming a tree into another tree. Last but not least, we provide a silent
self-stabilizing algorithm for computing and certifying the labels of a
NCA-labeling scheme
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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