97 research outputs found
Playing With Population Protocols
Population protocols have been introduced as a model of sensor networks
consisting of very limited mobile agents with no control over their own
movement: A collection of anonymous agents, modeled by finite automata,
interact in pairs according to some rules.
Predicates on the initial configurations that can be computed by such
protocols have been characterized under several hypotheses.
We discuss here whether and when the rules of interactions between agents can
be seen as a game from game theory. We do so by discussing several basic
protocols
On the Convergence of Population Protocols When Population Goes to Infinity
Population protocols have been introduced as a model of sensor networks
consisting of very limited mobile agents with no control over their own
movement. A population protocol corresponds to a collection of anonymous
agents, modeled by finite automata, that interact with one another to carry out
computations, by updating their states, using some rules. Their computational
power has been investigated under several hypotheses but always when restricted
to finite size populations. In particular, predicates stably computable in the
original model have been characterized as those definable in Presburger
arithmetic. We study mathematically the convergence of population protocols
when the size of the population goes to infinity. We do so by giving general
results, that we illustrate through the example of a particular population
protocol for which we even obtain an asymptotic development. This example shows
in particular that these protocols seem to have a rather different
computational power when a huge population hypothesis is considered.Comment: Submitted to Applied Mathematics and Computation. 200
Ants: Mobile Finite State Machines
Consider the Ants Nearby Treasure Search (ANTS) problem introduced by
Feinerman, Korman, Lotker, and Sereni (PODC 2012), where mobile agents,
initially placed at the origin of an infinite grid, collaboratively search for
an adversarially hidden treasure. In this paper, the model of Feinerman et al.
is adapted such that the agents are controlled by a (randomized) finite state
machine: they possess a constant-size memory and are able to communicate with
each other through constant-size messages. Despite the restriction to
constant-size memory, we show that their collaborative performance remains the
same by presenting a distributed algorithm that matches a lower bound
established by Feinerman et al. on the run-time of any ANTS algorithm
Generalized Communicating P Systems Working in Fair Sequential Model
In this article we consider a new derivation mode for generalized
communicating P systems (GCPS) corresponding to the functioning of population
protocols (PP) and based on the sequential derivation mode and a fairness
condition. We show that PP can be seen as a particular variant of GCPS. We also
consider a particular stochastic evolution satisfying the fairness condition
and obtain that it corresponds to the run of a Gillespie's SSA. This permits to
further describe the dynamics of GCPS by a system of ODEs when the population
size goes to the infinity.Comment: Presented at MeCBIC 201
Distributed anonymous function computation in information fusion and multiagent systems
We propose a model for deterministic distributed function computation by a
network of identical and anonymous nodes, with bounded computation and storage
capabilities that do not scale with the network size. Our goal is to
characterize the class of functions that can be computed within this model. In
our main result, we exhibit a class of non-computable functions, and prove that
every function outside this class can at least be approximated. The problem of
computing averages in a distributed manner plays a central role in our
development
How to Work with Honest but Curious Judges? (Preliminary Report)
The three-judges protocol, recently advocated by Mclver and Morgan as an
example of stepwise refinement of security protocols, studies how to securely
compute the majority function to reach a final verdict without revealing each
individual judge's decision. We extend their protocol in two different ways for
an arbitrary number of 2n+1 judges. The first generalisation is inherently
centralised, in the sense that it requires a judge as a leader who collects
information from others, computes the majority function, and announces the
final result. A different approach can be obtained by slightly modifying the
well-known dining cryptographers protocol, however it reveals the number of
votes rather than the final verdict. We define a notion of conditional
anonymity in order to analyse these two solutions. Both of them have been
checked in the model checker MCMAS
Uniform Partition in Population Protocol Model Under Weak Fairness
We focus on a uniform partition problem in a population protocol model. The uniform partition problem aims to divide a population into k groups of the same size, where k is a given positive integer. In the case of k=2 (called uniform bipartition), a previous work clarified space complexity under various assumptions: 1) an initialized base station (BS) or no BS, 2) weak or global fairness, 3) designated or arbitrary initial states of agents, and 4) symmetric or asymmetric protocols, except for the setting that agents execute a protocol from arbitrary initial states under weak fairness in the model with an initialized base station. In this paper, we clarify the space complexity for this remaining setting. In this setting, we prove that P states are necessary and sufficient to realize asymmetric protocols, and that P+1 states are necessary and sufficient to realize symmetric protocols, where P is the known upper bound of the number of agents. From these results and the previous work, we have clarified the solvability of the uniform bipartition for each combination of assumptions. Additionally, we newly consider an assumption on a model of a non-initialized BS and clarify solvability and space complexity in the assumption. Moreover, the results in this paper can be applied to the case that k is an arbitrary integer (called uniform k-partition)
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