Geohyperbolic Routing and Addressing Schemes
March 01, 2017 Β· Declared Dead Β· π Computer communication review
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ivan Voitalov, Rodrigo Aldecoa, Lan Wang, Dmitri Krioukov
arXiv ID
1703.00520
Category
cs.NI: Networking & Internet
Cross-listed
physics.soc-ph
Citations
34
Venue
Computer communication review
Last Checked
6 months ago
Abstract
The key requirement to routing in any telecommunication network, and especially in Internet-of-Things (IoT) networks, is scalability. Routing must route packets between any source and destination in the network without incurring unmanageable routing overhead that grows quickly with increasing network size and dynamics. Here we present an addressing scheme and a coupled network topology design scheme that guarantee essentially optimal routing scalability. The FIB sizes are as small as they can be, equal to the number of adjacencies a node has, while the routing control overhead is minimized as nearly zero routing control messages are exchanged even upon catastrophic failures in the network. The key new ingredient is the addressing scheme, which is purely local, based only on geographic coordinates of nodes and a centrality measure, and does not require any sophisticated non-local computations or global network topology knowledge for network embedding. The price paid for these benefits is that network topology cannot be arbitrary but should follow a specific design, resulting in Internet-like topologies. The proposed schemes can be most easily deployed in overlay networks, and also in other network deployments, where geolocation information is available, and where network topology can grow following the design specifications.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Networking & Internet
R.I.P.
π»
Ghosted
π
π
The Cartographer
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
π
π
The Cartographer
A Survey of Indoor Localization Systems and Technologies
R.I.P.
π»
Ghosted
Survey of Important Issues in UAV Communication Networks
π
π
The Cartographer
Network Function Virtualization: State-of-the-art and Research Challenges
π
π
The Cartographer
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted