Agentic Distributed Computing

2025-07-06

AI Summary

This paper investigates graph-level tasks—specifically leader election and minimum spanning tree (MST) construction—in the *agentic distributed model*, where mobile agents serve as computational units and communication occurs only when agents co-locate at the same node, contrasting with classical message-passing models. We conduct the first systematic study under the general setting where the number of agents $k$ satisfies $k leq n$, lifting the prior restriction $k = n$ (with $n$ denoting the number of graph nodes). We present deterministic distributed algorithms achieving leader election in $O(D + k)$ time and $O(log n)$ memory per agent, and MST construction in $O(n + k)$ time and $O(log n)$ memory, both time-optimal. Our results extend the theoretical foundations of mobile agent computing and provide tight complexity bounds alongside implementable algorithmic frameworks for resource-constrained distributed systems.

Technology Category

• Multiagent Systems: Distributed Problem Solving
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

The most celebrated and extensively studied model of distributed computing is the {em message-passing model,} in which each vertex/node of the (distributed network) graph corresponds to a static computational device that communicates with other devices through passing messages. In this paper, we consider the {em agentic model} of distributed computing which extends the message-passing model in a new direction. In the agentic model, computational devices are modeled as relocatable or mobile computational devices (called agents in this paper), i.e., each vertex/node of the graph serves as a container for the devices, and hence communicating with another device requires relocating to the same node. We study two fundamental graph level tasks, leader election, and minimum spanning tree, in the agentic model, which will enhance our understanding of distributed computation across paradigms. The objective is to minimize both time and memory complexities. Following the literature, we consider the synchronous setting in which each agent performs its operations synchronously with others, and hence the time complexity can be measured in rounds. In this paper, we present two deterministic algorithms for leader election: one for the case of $k<n$ and another for the case of $k=n$, minimizing both time and memory complexities, where $k$ and $n$, respectively, are the number of agents and number of nodes of the graph. Using these leader election results, we develop deterministic algorithms for agents to construct a minimum spanning tree of the graph, minimizing both time and memory complexities. To the best of our knowledge, this is the first study of distributed graph level tasks in the agentic model with $kleq n$. Previous studies only considered the case of $k=n$.

Problem

• Extends message-passing model to mobile agents
• Solves leader election for k<n and k=n cases
• Develops deterministic MST algorithms for agents

Innovation

• Mobile agents replace static nodes in computing
• Leader election algorithms for agentic model
• Deterministic MST construction with mobile agents