# The effect of the toplolgy adaptation on search performance in overlay network

arXiv: https://arxiv.org/abs/2012.13146 · HTML: https://mlsanity.com/paper/2012.13146/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Dec 2020.

## Built on by (most cited first, 1 of 1)

- [A Comprehensive Survey on Federated Learning: Concept and Applications](https://mlsanity.com/paper/2201.09384/) (2022)

## Abstract (arXiv)

The work presented in this research paper has focused on the effect of network to-pology adaptation on search performance in peer to peer overlay network. Guided search vs. blind search have been studied with the aim of improving the search re-sults and decreasing the time a search message would take to reach the destination. The network has been formulated as a bi-direction graph with vertices represent network nodes and edges represent connections. The level of network subject of this study is on application layer, that means two nodes are connected if they know each other contact addresses. A good example of this kind of network is the social network where all the lower layers are hidden from the end user. Two different search algorithms have been studied under these circumstances, namely: depth first algorithm and breadth first algorithm. Furthermore, the algorithms performance is examined under random topology (scale free network topology) and under topology adaptation. A simulation scenario has been designed to investigate the fidelity of the system and study the suggested solutions. Simulation results have shown that the search algorithms are performing better under topology adaptation in terms of re-sults quality and search time.