Optimal Local Algorithms via Topology-Sensitivity

The project aims to develop topology-sensitive algorithms that optimize locality in distributed computation, enhancing efficiency and scalability for solving complex graph problems.

Subsidie
€ 1.499.456
2025

Projectdetails

Introduction

Considering the rapid growth of data sets and network sizes over the past decade, there is little doubt that the future of computation is distributed. One central aspect lying at the heart of distributed algorithms is the question of locality: what can be computed using only local information, and how much information is needed?

Importance of Locality

While answering this question is essential for obtaining highly efficient algorithms for many important distributed problems—such as load balancing in massive networks—locality is a fundamentally important concept also in many other fields of algorithmics, such as:

  • Classical sequential algorithms
  • Massively parallel algorithms
  • Dynamic algorithms
  • Sublinear algorithms
  • Streaming algorithms
  • Online algorithms

Challenges in Distributed Algorithms

In the context of distributed algorithms, a careful analysis of recent research on impossibilities reveals the key challenges in understanding locality—and therefore in designing optimal algorithms—for many graph problems. These challenges include:

  1. Understanding how to solve tree-like structures efficiently.
  2. Understanding how to explicitly exploit any deviations from a tree-like topology algorithmically.

Project Goals

The goal of this proposal is to gain a fundamental understanding of locality via the novel concept of topology-sensitive algorithms. This approach precisely addresses the key challenges by explicitly exploiting local topological features in the input instance.

Expected Outcomes

Such an understanding will result in:

  • Optimal algorithms
  • Tight complexity bounds for many important distributed problems

This will help resolve central questions in distributed algorithms that have been open for decades, laying the foundations for highly efficient and scalable algorithms in massive networks. It will also imply significant improvements over the state-of-the-art in a variety of other algorithmic fields.

Conclusion

In a nutshell, the proposed project aims at a world in which everything that can be done locally will be done locally.

Financiële details & Tijdlijn

Financiële details

Subsidiebedrag€ 1.499.456
Totale projectbegroting€ 1.499.456

Tijdlijn

Startdatum1-1-2025
Einddatum31-12-2029
Subsidiejaar2025

Partners & Locaties

Projectpartners

  • CISPA - HELMHOLTZ-ZENTRUM FUR INFORMATIONSSICHERHEIT GGMBHpenvoerder

Land(en)

Germany

Vergelijkbare projecten binnen European Research Council

ERC STG

MANUNKIND: Determinants and Dynamics of Collaborative Exploitation

This project aims to develop a game theoretic framework to analyze the psychological and strategic dynamics of collaborative exploitation, informing policies to combat modern slavery.

€ 1.497.749
ERC STG

Elucidating the phenotypic convergence of proliferation reduction under growth-induced pressure

The UnderPressure project aims to investigate how mechanical constraints from 3D crowding affect cell proliferation and signaling in various organisms, with potential applications in reducing cancer chemoresistance.

€ 1.498.280
ERC STG

Uncovering the mechanisms of action of an antiviral bacterium

This project aims to uncover the mechanisms behind Wolbachia's antiviral protection in insects and develop tools for studying symbiont gene function.

€ 1.500.000
ERC STG

The Ethics of Loneliness and Sociability

This project aims to develop a normative theory of loneliness by analyzing ethical responsibilities of individuals and societies to prevent and alleviate loneliness, establishing a new philosophical sub-field.

€ 1.025.860

Vergelijkbare projecten uit andere regelingen

ERC ADG

Symmetry and Similarity

This project aims to develop a comprehensive algorithmic theory of graph similarity, focusing on efficient comparison methods and addressing the graph isomorphism problem.

€ 2.495.575
ERC COG

Scalable Graph Algorithms for Bioinformatics using Structure, Parameterization and Dynamic Updates

This project aims to develop scalable exact graph algorithms for processing sequencing data, enhancing accuracy in RNA transcript discovery and genomic database indexing.

€ 1.999.868