TY - JOUR
T1 - Percolation thresholds for robust network connectivity
AU - Mohseni-Kabir, Arman
AU - Pant, Mihir
AU - Towsley, Don
AU - Guha, Saikat
AU - Swami, Ananthram
N1 - Funding Information:
This research was sponsored in part by the US Army Research Laboratory and the UK Ministry of Defense under Agreement Number W911NF-16-3-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the US Army Research Laboratory, the US Government, the UK Ministry of Defense or the UK Government. The US and UK Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.
Publisher Copyright:
© 2021 IOP Publishing Ltd and SISSA Medialab srl
PY - 2021/1
Y1 - 2021/1
N2 - Communication networks, power grids, and transportation networks are all examples of networks whose performance depends on reliable connectivity of their underlying network components even in the presence of usual network dynamics due to mobility, node or edge failures, and varying traffic loads. Percolation theory quantifies the threshold value of a local control parameter such as a node occupation (resp., deletion) probability or an edge activation (resp., removal) probability above (resp., below) which there exists a giant connected component (GCC), a connected component comprising of a number of occupied nodes and active edges whose size is proportional to the size of the network itself. Any pair of occupied nodes in the GCC is connected via at least one path comprised of active edges and occupied nodes. The mere existence of the GCC itself does not guarantee that the long-range connectivity would be robust, e.g. to random link or node failures due to network dynamics. In this paper, we explore new percolation thresholds that guarantee not only spanning network connectivity, but also robustness. We define and analyze four measures of robust network connectivity, explore their interrelationships, and numerically evaluate the respective robust percolation thresholds for the 2D square lattice.
AB - Communication networks, power grids, and transportation networks are all examples of networks whose performance depends on reliable connectivity of their underlying network components even in the presence of usual network dynamics due to mobility, node or edge failures, and varying traffic loads. Percolation theory quantifies the threshold value of a local control parameter such as a node occupation (resp., deletion) probability or an edge activation (resp., removal) probability above (resp., below) which there exists a giant connected component (GCC), a connected component comprising of a number of occupied nodes and active edges whose size is proportional to the size of the network itself. Any pair of occupied nodes in the GCC is connected via at least one path comprised of active edges and occupied nodes. The mere existence of the GCC itself does not guarantee that the long-range connectivity would be robust, e.g. to random link or node failures due to network dynamics. In this paper, we explore new percolation thresholds that guarantee not only spanning network connectivity, but also robustness. We define and analyze four measures of robust network connectivity, explore their interrelationships, and numerically evaluate the respective robust percolation thresholds for the 2D square lattice.
KW - Classical phase transitions
KW - Communication
KW - Critical exponents and amplitudes
KW - Information networks
KW - Percolation problems
KW - Supply
UR - http://www.scopus.com/inward/record.url?scp=85100975414&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85100975414&partnerID=8YFLogxK
U2 - 10.1088/1742-5468/abd312
DO - 10.1088/1742-5468/abd312
M3 - Article
AN - SCOPUS:85100975414
VL - 2021
JO - Journal of Statistical Mechanics: Theory and Experiment
JF - Journal of Statistical Mechanics: Theory and Experiment
SN - 1742-5468
IS - 1
M1 - 013212
ER -