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Distance-2-Dispersion: Dispersion with Further Constraints

Authors: Tanvir Kaur; Kaushik Mondal 0001;

Distance-2-Dispersion: Dispersion with Further Constraints

Abstract

The aim of the dispersion problem is to place a set of $k(\leq n)$ mobile robots in the nodes of an unknown graph consisting of $n$ nodes such that in the final configuration each node contains at most one robot, starting from any arbitrary initial configuration of the robots on the graph. In this work we propose a variant of the dispersion problem where we start with any number of robots, and put an additional constraint that no two adjacent nodes contain robots in the final configuration. We name this problem as Distance-2-Dispersion (D-2-D). However, even if the number of robots $k$ is less than $n$, it may not possible for each robot to find a distinct node to reside, maintaining our added constraint. Specifically, if a maximal independent set is already formed by the nodes which contain a robot each, then other robots, if any, who are searching for a node to seat, will not find one. Hence we allow multiple robots to seat on some nodes only if there is no place to seat. If $k\geq n$, it is guaranteed that the nodes with robots form a maximal independent set of the underlying network. The graph $G=(V, E)$ has $n$ nodes and $m$ edges, where nodes are anonymous. It is a port labelled graph, i.e., each node $u$ assigns a distinct port number to each of its incident edges from a range $[0,δ-1]$ where $δ$ is the degree of the node $u$. The robots have unique ids in the range $[1, L]$, where $L \ge k$. Co-located robots can communicate among themselves. We provide an algorithm that solves D-2-D starting from a rooted configuration (i.e., initially all the robots are co-located) and terminate after $2Δ(8m-3n+3)$ synchronous rounds using $O(log Δ)$ memory per robot without using any global knowledge of the graph parameters $m$, $n$ and $Δ$, the maximum degree of the graph. We also provide $Ω(mΔ)$ lower bound on the number of rounds for the D-2-D problem.

Keywords

FOS: Computer and information sciences, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), Distributed, Parallel, and Cluster Computing (cs.DC)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Top 10%
Top 10%
Green