机构:
Boston Univ, Ctr Polymer Studies, Boston, MA 02215 USABoston Univ, Ctr Polymer Studies, Boston, MA 02215 USA
Chen, Yiping
[1
]
Paul, Gerald
论文数: 0引用数: 0
h-index: 0
机构:
Boston Univ, Ctr Polymer Studies, Boston, MA 02215 USABoston Univ, Ctr Polymer Studies, Boston, MA 02215 USA
Paul, Gerald
[1
]
Havlin, Shlomo
论文数: 0引用数: 0
h-index: 0
机构:
Bar Ilan Univ, Minerva Ctr, IL-52900 Ramat Gan, Israel
Bar Ilan Univ, Dept Phys, IL-52900 Ramat Gan, IsraelBoston Univ, Ctr Polymer Studies, Boston, MA 02215 USA
Havlin, Shlomo
[2
,3
]
Liljeros, Fredrik
论文数: 0引用数: 0
h-index: 0
机构:
Stockholm Univ, Dept Sociol, S-10691 Stockholm, SwedenBoston Univ, Ctr Polymer Studies, Boston, MA 02215 USA
Liljeros, Fredrik
[4
]
Stanley, H. Eugene
论文数: 0引用数: 0
h-index: 0
机构:
Boston Univ, Ctr Polymer Studies, Boston, MA 02215 USABoston Univ, Ctr Polymer Studies, Boston, MA 02215 USA
Stanley, H. Eugene
[1
]
机构:
[1] Boston Univ, Ctr Polymer Studies, Boston, MA 02215 USA
[2] Bar Ilan Univ, Minerva Ctr, IL-52900 Ramat Gan, Israel
[3] Bar Ilan Univ, Dept Phys, IL-52900 Ramat Gan, Israel
[4] Stockholm Univ, Dept Sociol, S-10691 Stockholm, Sweden
The problem of finding the best strategy to immunize a population or a computer network with a minimal number of immunization doses is of current interest. It has been accepted that the targeted strategies on most central nodes are most efficient for model and real networks. We present a newly developed graph-partitioning strategy which requires 5% to 50% fewer immunization doses compared to the targeted strategy and achieves the same degree of immunization of the network. We explicitly demonstrate the effectiveness of our proposed strategy on several model networks and also on real networks.