Editing Efficient Search Algorithms in Power-Law Networks

Title: Efficient Search Algorithms in Power-Law Networks

Main Research Question: How can we develop efficient search algorithms for networks with power-law degree distributions, such as peer-to-peer networks?

Methodology: We propose a number of local search strategies that utilize high-degree nodes in power-law graphs. These strategies have sub-linear costs that scale with the size of the graph. We demonstrate the utility of these strategies on the Gnutella peer-to-peer network.

Results: We introduce several local search algorithms that exploit the power-law nature of these networks. We show that these algorithms work effectively on real Gnutella networks and can reduce the network search traffic.

Implications: These search algorithms can be applied to other power-law networks, such as social networks and biological networks. They can help improve the efﬁciency of search processes in these networks and reduce the overall network traffic.

Conclusion: In conclusion, we have developed efficient search algorithms for power-law networks that utilize high-degree nodes and have sub-linear costs. These algorithms can be applied to various power-law networks, such as peer-to-peer networks, and can help improve the efﬁciency of search processes in these networks.

Link to Article: https://arxiv.org/abs/0103016v1
Authors: 
arXiv ID: 0103016v1

[[Category:Computer Science]]
[[Category:Networks]]
[[Category:Search]]
[[Category:These]]
[[Category:Algorithms]]
[[Category:Power]]