A novel recovery strategy based on link prediction and hyperbolic geometry of complex networks. (10th September 2021)
- Record Type:
- Journal Article
- Title:
- A novel recovery strategy based on link prediction and hyperbolic geometry of complex networks. (10th September 2021)
- Main Title:
- A novel recovery strategy based on link prediction and hyperbolic geometry of complex networks
- Authors:
- Moshiri, Mahdi
Safaei, Farshad
Samei, Zeynab - Editors:
- De Domenico, Manlio
- Abstract:
- Abstract: Recovery of complex networks is an important issue that has been extensively used in various fields. Much work has been done to measure and improve the stability of complex networks during attacks. Recently, many studies have focused on the network recovery strategies after attack. In many real cases, link retrieval and recovery of critical infrastructures such as transmission network and telecommunications infrastructures are of particular importance and should be prioritized. For example, when a flood disrupts optical fibre communications in transmission networks and paralyzes the network, link retrieval corresponds to the recovery of fibre communications, so that the transmission network communication capacity can be restored at the earliest possible time. So, predicting the appropriate reserved links in a way that the network can be recovered at the lowest cost and fastest time after attacks or interruptions will be critical in a disaster. In this article, different kinds of attack strategies are provided and some retrieval strategies based on link prediction methods are proposed to recover the network after failure and attack. Beside that, a new link prediction method based on the hyperbolic geometry of the complex network is proposed to discover redundant links. The numerical simulations reveal its superiority than other common and recent link prediction-based methods used for network recovery, especially in the case of attacks based on edge betweennessAbstract: Recovery of complex networks is an important issue that has been extensively used in various fields. Much work has been done to measure and improve the stability of complex networks during attacks. Recently, many studies have focused on the network recovery strategies after attack. In many real cases, link retrieval and recovery of critical infrastructures such as transmission network and telecommunications infrastructures are of particular importance and should be prioritized. For example, when a flood disrupts optical fibre communications in transmission networks and paralyzes the network, link retrieval corresponds to the recovery of fibre communications, so that the transmission network communication capacity can be restored at the earliest possible time. So, predicting the appropriate reserved links in a way that the network can be recovered at the lowest cost and fastest time after attacks or interruptions will be critical in a disaster. In this article, different kinds of attack strategies are provided and some retrieval strategies based on link prediction methods are proposed to recover the network after failure and attack. Beside that, a new link prediction method based on the hyperbolic geometry of the complex network is proposed to discover redundant links. The numerical simulations reveal its superiority than other common and recent link prediction-based methods used for network recovery, especially in the case of attacks based on edge betweenness strategy. … (more)
- Is Part Of:
- Journal of complex networks. Volume 9:Number 4(2021)
- Journal:
- Journal of complex networks
- Issue:
- Volume 9:Number 4(2021)
- Issue Display:
- Volume 9, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 9
- Issue:
- 4
- Issue Sort Value:
- 2021-0009-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-09-10
- Subjects:
- complex networks -- link prediction -- hyperbolic geometry -- redundant link recovery -- network infrastructure failures recovery -- intentional attacks
Numerical analysis -- Periodicals
Computer networks -- Periodicals
Social networks -- Periodicals
518.05 - Journal URLs:
- http://comnet.oxfordjournals.org/ ↗
http://www.oxfordjournals.org/en/ ↗ - DOI:
- 10.1093/comnet/cnab007 ↗
- Languages:
- English
- ISSNs:
- 2051-1310
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20113.xml