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Dispersion

Spread \(k \le n\) agents over the nodes of an \(n\)-node anonymous graph so that no node hosts more than one agent, as fast as possible and with as little memory per agent as possible.

Problem statement and measuresexpand

Given a connected graph \(G\) with \(n\) nodes and \(m\) edges, and \(k \le n\) agents placed on the nodes of \(G\) in any initial configuration (the node of each agent; several agents may share a node), the agents must reach a configuration in which every node hosts at most one agent, and stay there.

Time is the number of rounds (synchronous) or epochs (asynchronous; an epoch is an interval in which every agent completes at least one full Communicate–Compute–Move step, not necessarily the shortest one) until the dispersed configuration is reached; where a result also makes every agent terminate explicitly, the notes say so. Memory is the number of bits of persistent memory each agent needs, counting its \(O(\log k)\)-bit identifier. Unless a variant or a result says otherwise, agents know nothing about \(n\), \(m\), \(k\), \(\Delta\) or \(D\).

Dispersion is the natural "one agent per node" problem: it is equivalent to leaving one agent at every node of a depth-first search (DFS) tree of \(k\) nodes, which is why depth-first search bounds such as \(\min(m, k\Delta)\) appear throughout, and it is a building block for exploration, leader election and self-deployment of agents.

Measures: Time, rounds in the synchronous model, epochs in the asynchronous model, until dispersion is reached; Memory, bits of persistent memory per agent, including its identifier.

Crash faults on unoriented grids

verified
Time: polynomial gapMemory: polynomial gap

Without a consistent compass the only crash-tolerant grid algorithm takes \(O(\sqrt n\log n)\) rounds and \(O(\sqrt n\log n)\) bits, against \(O(\sqrt n)\) rounds and \(O(\log n)\) bits on oriented grids.

Assumed (added on the last edge are outlined)

+Graph dynamicsstatic graph+Edge directionundirected+Number of agents\(k \le n\)+Identifiersdistinct identifiers (eponymous): agents have pairwise distinct identifiers+Topologygrid+Faultsup to \(f\) agents may crash (stop forever)+Communicationlocal (co-located agents communicate)+Timingsynchronous rounds

Not assumed

RandomnessdeterministicGrid orientationunoriented (no consistent compass)Node memoryno whiteboardsNode identifiersanonymous nodesInitial configurationarbitrary (agents on any \(\ell \le k\) nodes)
Formal definitions of this setting
Graph dynamics: static graph
\(G_t=G\) for all \(t\): the edge set never changes.
Edge direction: undirected
\(G=(V,E)\) with \(E\subseteq\binom V2\); every edge can be traversed in both directions.
Number of agents: \(k \le n\)
The number of agents satisfies \(1\le k\le n\).
Identifiers: distinct IDs (eponymous)
Distinct identifiers (eponymous agents): the label function \(\mathrm{id}:\{1,\dots,k\}\to\{1,\dots,L\}\) is injective; usually \(L=k^{O(1)}\), so a label takes \(O(\log k)\) bits.
Randomness: deterministic
The next state and move of an agent are a function of its current state and what it observes.
Topology: grid
\(G\) is a \(\sqrt n\times\sqrt n\) grid graph; whether ports are globally consistent (oriented) is stated per result.
Grid orientation: unoriented
Port labels carry no global meaning: at every node \(v\) the \(\delta_v\) incident edges get the labels \(1,\dots,\delta_v\) in an arbitrary order, chosen independently at each node, so an agent that enters \(v\) cannot tell from the labels which port continues in the same row or column. This is the default on every graph; on a grid it is called an unoriented grid.
Faults: at most crash faults
Up to \(f\) agents may stop forever at an adversarially chosen time; a crashed agent stays at its node (or vanishes, as stated per result) and never acts again.
Communication: local communication
Agents at the same node at the same time can read each other's entire memory (face-to-face communication). Agents crossing on an edge do not meet.
Timing: synchronous
Time proceeds in rounds \(t=1,2,\dots\); in every round every agent communicates, computes and moves (at most one edge) simultaneously.
Node memory: no whiteboards
Nodes have no storage: no information can be left at a node except by an agent staying there.
Node identifiers: anonymous nodes
Nodes have no identifiers; an agent at \(v\) sees only \(\deg(v)\) and the port numbers \(1,\dots,\deg(v)\), which are assigned locally and independently at each endpoint of an edge.
Initial configuration: any start
Agents start at arbitrary nodes; \(\ell\le k\) nodes are initially occupied, possibly with several agents each.

What is known

Time · rounds in the synchronous model, epochs in the asynchronous model, until dispersion is reached
polynomial gap
\(O(\sqrt n\log n)\) versus \(\Omega(\sqrt k)\): a \(\log n\) factor for \(k = \Omega(n)\), a factor \(\sqrt{n/k}\,\log n\) for smaller \(k\).
lower bound
\(\Omega(\sqrt k)\) Kshemkalyani et al. 2020c
bottleneckdistance
holds when
  • \(k\) agents on one node: a grid ball of radius \(r\) holds \(O(r^2)\) nodes
  • any algorithm
\(\Omega(\sqrt n)\) when \(k = \Omega(n)\).
introductory—
current best
\(O(\sqrt n\log n)\)
knows \(n\)
Memory · bits of persistent memory per agent, including its identifier
polynomial gap
\(O(\sqrt n\log n)\) versus \(\Omega(\log k)\), a factor \(\sqrt n\).
lower bound
\(\Omega(\log k)\) Kshemkalyani et al. 2020c
bottlenecksymmetry breaking
holds when
  • deterministic
  • all agents have the same memory bound
  • an initial configuration with co-located agents (rooted suffices)
  • memory counts the identifier
introductory—
current best
\(O(\sqrt n\log n)\)
knows \(n\)

Results, in order of publication

Time \(O(\sqrt n\log n)\)Memory \(O(\sqrt n\log n)\)
knows \(n\)

Introductory and current best (its Theorem 12, Section 6): any number of crashed agents.

Open questions

  1. Unoriented grids with crashes: close the gap between \(O(\sqrt n\log n)\) rounds with \(O(\sqrt n\log n)\) bits and the fault-free \(O(\sqrt n)\) rounds with \(O(\log n)\) bits Banerjee et al. 2024.

What carries over from neighbouring settings

Read off the order of assumptions, not checked case by case: results may carry extra assumptions (shown on their pages), and asynchronous time is measured in epochs.

Algorithms from weaker settings work here

Crash faults
Time \(O(\min(m, k\Delta))\)Memory \(O(k\log(k+\Delta))\)

Lower bounds from stronger settings hold here

Unoriented grids
Time \(\Omega(\sqrt k)\)Memory \(\Omega(\log k)\)
Crash faults on oriented grids
Time \(\Omega(\sqrt k)\)Memory \(\Omega(\log k)\)

Know a better result for this setting, or found a mistake? Suggest a result · Report an error. Accepted contributions are acknowledged.