Ameba-inspired Self-organizing Particle Systems

Dolev, Shlomi; Gmyr, Robert; Richa, Andrea W.; Scheideler, Christian

doi:10.48550/arxiv.1307.4259

Cited by 3 publications

(3 citation statements)

References 27 publications

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“…That is, the goal of a protocol is to result in a desired interaction pattern while in our model the goal of a protocol is to construct a network while operating under a totally unpredictable interaction pattern. Very recently, a model inspired by the behavior of ameba that allows algorithmic research on self-organizing particle systems was proposed [DGRS13]. The goal is for the particles to self-organize in order to adapt to a desired shape without any central control, which is quite similar to our objective, however the two models seem two have little in common.…”

Section: Further Related Workmentioning

confidence: 99%

Simple and efficient local codes for distributed stable network construction

Michail

Spirakis

2015

Distrib. Comput.

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Abstract. In this work, we study protocols (i.e. distributed algorithms) so that populations of distributed processes can construct networks. In order to highlight the basic principles of distributed network construction we keep the model minimal in all respects. In particular, we assume finite-state processes that all begin from the same initial state and all execute the same protocol (i.e. the system is homogeneous). Moreover, we assume pairwise interactions between the processes that are scheduled by an adversary. The only constraint on the adversary scheduler is that it must be fair, intuitively meaning that it must assign to every reachable configuration of the system a non-zero probability to occur. In order to allow processes to construct networks, we let them activate and deactivate their pairwise connections. When two processes interact, the protocol takes as input the states of the processes and the state of their connection and updates all of them. In particular, in every interaction, the protocol may activate an inactive connection, deactivate an active one, or leave the state of a connection unchanged. Initially all connections are inactive and the goal is for the processes, after interacting and activating/deactivating connections for a while, to end up with a desired stable network (i.e. one that does not change any more). We give protocols (optimal in some cases) and lower bounds for several basic network construction problems such as spanning line, spanning ring, spanning star, and regular network. We provide proofs of correctness for all of our protocols and analyze the expected time to convergence of most of them under a uniform random scheduler that selects the next pair of interacting processes uniformly at random from all such pairs. Finally, we prove several universality results by presenting generic protocols that are capable of simulating a Turing Machine (TM) and exploiting it in order to construct a large class of networks. Our universality protocols use a subset of the population (waste) in order to distributedly construct there a TM able to decide a graph class in some given space. Then, the protocols repeatedly construct in the rest of the population (useful space) a graph equiprobably drawn from all possible graphs. The TM works on this and accepts if the presented graph is in the class. We additionally show how to partition the population into k supernodes, each being a line of log k nodes, for the largest such k. This amount of local memory is sufficient for the supernodes to obtain unique names and exploit their names and their memory to realize nontrivial constructions. Delicate composition and reinitialization issues have to be solved for these general constructions to work.

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Section: Further Related Workmentioning

confidence: 99%

Simple and efficient local codes for distributed stable network construction

Michail

Spirakis

2015

Distrib. Comput.

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“…Another important difference is that network constructors allow the edges to choose between only two possible states which is not the case in [8], thus simulating an active or inactive communication link in the final configuration. Fields where population protocols and network constructors can be applied include Algorithmic Self-Assembly, Cellular Automata [2], Social Networks, and Network Formation in Nature [3].…”

Section: Network Constructors Modelmentioning

confidence: 99%

NETCS: A New Simulator of Population Protocols and Network Constructors

Amaxilatis,

Logaras,

Michail

et al. 2015

Preprint

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Network Constructors are an extension of the standard population protocol model in which finite-state agents interact in pairs under the control of an adversary scheduler. In this work we present NETCS, a simulator designed to evaluate the performance of various network constructors and population protocols under different schedulers and network configurations. Our simulator provides researchers with an intuitive user interface and a quick experimentation environment to evaluate their work. It also harnesses the power of the cloud, as experiments are executed remotely and scheduled through the web interface provided. To prove the validity and quality of our simulator we provide an extensive evaluation of multiple protocols with more than 100000 experiments for different network sizes and configurations that validate the correctness of the theoretical analysis of existing protocols and estimate the real values of the hidden asymptotic coefficients. We also show experimentally (with more than 40000 experiments) that a probabilistic algorithm is capable of counting the actual size of the network in bounded time given a unique leader.

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“…AMOEBOT model was proposed as a computational model for Programmable Matter to enable a strict algorithmic analysis of cooperative systems at the nano size [33]. The model was originally proposed by Dolev et al [52] as "amoeba-inspired self-organizing particle systems". Next, it was refined and formally announced as the Amoebot model by Derakhshandeh et al [41].…”

Section: Amoebotmentioning

confidence: 99%

Connected Line Recovery and Maintenance by Programmable Matter

Nokhanji¹

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Several different distributed computational universes have been considered and studied within the interdisciplinary field called Programmable Matter. In this field, the matter is envisioned as a very large number of micro and nano-sized computational entities with limited capabilities programmed to collectively perform a task without the need for any central or external intervention. Within distributed computing, several theoretical active and hybrid models for programmable matter have been proposed. Within these models, a central concern has been the formation of geometric shapes; among them, the line is especially important. An important requirement, common to most research, is the connectivity of the operating elements at all times.

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Ameba-inspired Self-organizing Particle Systems

Cited by 3 publications

References 27 publications

Simple and efficient local codes for distributed stable network construction

Simple and efficient local codes for distributed stable network construction

NETCS: A New Simulator of Population Protocols and Network Constructors

Connected Line Recovery and Maintenance by Programmable Matter

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