Distributed Computing Through Combinatorial Topology

For massive sensor networks (millions of tiny devices), the state space is huge. Topological invariants (Euler characteristic, Betti numbers) bound the time and memory needed to reach consensus.

The rapid growth of data and computational demands has necessitated the development of novel computing paradigms that can efficiently process large-scale data. Traditional computing architectures, such as centralized computing and parallel computing, have limitations in terms of scalability, fault tolerance, and energy efficiency. In recent years, distributed computing has emerged as a promising approach to address these challenges. However, distributed computing also poses significant challenges, such as coordinating and communicating between nodes, ensuring consistency and correctness, and handling failures and faults. Distributed Computing Through Combinatorial Topology