In this paper, we consider the distributed setting of computational mobile entities, called robots, that have to perform tasks without global coordination. Depending on the environment as well as on the robots' capabilities, tasks might be accomplished or not. In particular, we focus on the well-known scenario where the robots reside on the nodes of a graph and operate in Look-Compute-Move cycles. In one cycle, a robot perceives the current configuration in terms of robots positions (Look), decides whether to move toward some edge of the graph (Compute), and in the positive case it performs an instantaneous move along the computed edge (Move). We then compare two basic models: in the first model robots are fully synchronous, while in the second one robots are asynchronous and lights-enhanced, that is, each robot is equipped with a constant number of lights visible to all other robots. The question whether one model is more powerful than the other in terms of computable tasks has been considered in [Das et al., Int.'l Conf. on Distributed Computing Systems, 2012] but for robots moving on the Euclidean plane rather than on a graph. We provide two different tasks, and show that on graphs one task can be solved in the fully synchronous model but not in the asynchronous lights-enhanced model, while for the other task the converse holds. Hence we can assert that the fully synchronous model and the asynchronous lights-enhanced model are incomparable on graphs. This opens challenging directions in order to understand which peculiarities make the models so different.

Synchronous Robots vs Asynchronous Lights-Enhanced Robots on Graphs

D'EMIDIO, MATTIA;FRIGIONI, DANIELE;
2016-01-01

Abstract

In this paper, we consider the distributed setting of computational mobile entities, called robots, that have to perform tasks without global coordination. Depending on the environment as well as on the robots' capabilities, tasks might be accomplished or not. In particular, we focus on the well-known scenario where the robots reside on the nodes of a graph and operate in Look-Compute-Move cycles. In one cycle, a robot perceives the current configuration in terms of robots positions (Look), decides whether to move toward some edge of the graph (Compute), and in the positive case it performs an instantaneous move along the computed edge (Move). We then compare two basic models: in the first model robots are fully synchronous, while in the second one robots are asynchronous and lights-enhanced, that is, each robot is equipped with a constant number of lights visible to all other robots. The question whether one model is more powerful than the other in terms of computable tasks has been considered in [Das et al., Int.'l Conf. on Distributed Computing Systems, 2012] but for robots moving on the Euclidean plane rather than on a graph. We provide two different tasks, and show that on graphs one task can be solved in the fully synchronous model but not in the asynchronous lights-enhanced model, while for the other task the converse holds. Hence we can assert that the fully synchronous model and the asynchronous lights-enhanced model are incomparable on graphs. This opens challenging directions in order to understand which peculiarities make the models so different.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/103375
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