TY - JOUR
T1 - Disaster-survivable cloud-network mapping
AU - Colman-Meixner, Carlos
AU - Dikbiyik, Ferhat
AU - Habib, M. Farhan
AU - Tornatore, Massimo
AU - Chuah, Chen Nee
AU - Mukherjee, Biswanath
PY - 2014/6
Y1 - 2014/6
N2 - Cloud-computing services are provided to consumers through a network of servers and network equipment. Cloud-network (CN) providers virtualize resources [e.g., virtual machine (VM) and virtual network (VN)] for efficient and secure resource allocation. Disasters are one of the worst threats for CNs as they can causemassive disruptions andCN disconnection. A disaster may also induce post-disaster correlated, cascading failures which can disconnect more CNs. Survivable virtual-network embedding (SVNE) approaches have been studied to protect VNs against single physicallink/- node and dual physical-link failures in communication infrastructure, but massive disruptions due to a disaster and their consequences can make SVNE approaches insufficient to guarantee cloud-computing survivability. In this work, we study the problem of survivable CN mapping from disaster. We consider risk assessment, VM backup location, and post-disaster survivability to reduce the risk of failure and probability of CN disconnection and the penalty paid by operators due to loss of capacity.We formulate the proposed approach as an integer linear program and study two scenarios: a natural disaster, e.g., earthquake and a human-made disaster, e.g., weapons-of-mass-destruction attack. Our illustrative examples show that our approach reduces the risk of CN disconnection and penalty up to 90% compared with a baseline CNmapping approach and increases the CN survivability up to 100% in both scenarios.
AB - Cloud-computing services are provided to consumers through a network of servers and network equipment. Cloud-network (CN) providers virtualize resources [e.g., virtual machine (VM) and virtual network (VN)] for efficient and secure resource allocation. Disasters are one of the worst threats for CNs as they can causemassive disruptions andCN disconnection. A disaster may also induce post-disaster correlated, cascading failures which can disconnect more CNs. Survivable virtual-network embedding (SVNE) approaches have been studied to protect VNs against single physicallink/- node and dual physical-link failures in communication infrastructure, but massive disruptions due to a disaster and their consequences can make SVNE approaches insufficient to guarantee cloud-computing survivability. In this work, we study the problem of survivable CN mapping from disaster. We consider risk assessment, VM backup location, and post-disaster survivability to reduce the risk of failure and probability of CN disconnection and the penalty paid by operators due to loss of capacity.We formulate the proposed approach as an integer linear program and study two scenarios: a natural disaster, e.g., earthquake and a human-made disaster, e.g., weapons-of-mass-destruction attack. Our illustrative examples show that our approach reduces the risk of CN disconnection and penalty up to 90% compared with a baseline CNmapping approach and increases the CN survivability up to 100% in both scenarios.
KW - Cloud computing
KW - Cloud-network mapping
KW - Disaster survivability
KW - Virtual machine
KW - Virtual-network mapping
UR - http://www.scopus.com/inward/record.url?scp=84903603482&partnerID=8YFLogxK
U2 - 10.1007/s11107-014-0434-6
DO - 10.1007/s11107-014-0434-6
M3 - Article (Academic Journal)
AN - SCOPUS:84903603482
SN - 1387-974X
VL - 27
SP - 141
EP - 153
JO - Photonic Network Communications
JF - Photonic Network Communications
IS - 3
ER -