Abstract
Vulnerability due to inter-connectivity of multiple networks has been observed in many complex networks. Previous works mainly focused on robust network design and on recovery strategies after sporadic or massive failures in the case of complete knowledge of failure location. We focus on cascading failures involving the power grid and its communication network with consequent imprecision in damage assessment. We tackle the problem of mitigating the ongoing cascading failure and providing a recovery strategy. We propose a failure mitigation strategy in two steps: 1) Once a cascading failure is detected, we limit further propagation by re-distributing the generator and load's power. 2) We formulate a recovery plan to maximize the total amount of power delivered to the demand loads during the recovery intervention. Our approach to cope with insufficient knowledge of damage locations is based on the use of a new algorithm to determine consistent failure sets (CFS). We show that, given knowledge of the system state before the disruption, the CFS algorithm can find all consistent sets of unknown failures in polynomial time provided that, each connected component of the disrupted graph has at least one line whose failure status is known to the controller.
Original language | English (US) |
---|---|
Title of host publication | Proceedings - 2017 IEEE 36th International Symposium on Reliable Distributed Systems, SRDS 2017 |
Publisher | IEEE Computer Society |
Pages | 54-63 |
Number of pages | 10 |
ISBN (Electronic) | 9781538616796 |
DOIs | |
State | Published - Oct 13 2017 |
Event | 36th IEEE International Symposium on Reliable Distributed Systems, SRDS 2017 - Hong Kong, Hong Kong Duration: Sep 26 2017 → Sep 29 2017 |
Publication series
Name | Proceedings of the IEEE Symposium on Reliable Distributed Systems |
---|---|
Volume | 2017-September |
ISSN (Print) | 1060-9857 |
Other
Other | 36th IEEE International Symposium on Reliable Distributed Systems, SRDS 2017 |
---|---|
Country | Hong Kong |
City | Hong Kong |
Period | 9/26/17 → 9/29/17 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Hardware and Architecture
- Computer Networks and Communications
Cite this
}
Controlling cascading failures in interdependent networks under incomplete knowledge. / Tootaghaj, Diman Zad; Bartolini, Novella; Khamfroush, Hana; La Porta, Thomas F.
Proceedings - 2017 IEEE 36th International Symposium on Reliable Distributed Systems, SRDS 2017. IEEE Computer Society, 2017. p. 54-63 8069068 (Proceedings of the IEEE Symposium on Reliable Distributed Systems; Vol. 2017-September).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Controlling cascading failures in interdependent networks under incomplete knowledge
AU - Tootaghaj, Diman Zad
AU - Bartolini, Novella
AU - Khamfroush, Hana
AU - La Porta, Thomas F.
PY - 2017/10/13
Y1 - 2017/10/13
N2 - Vulnerability due to inter-connectivity of multiple networks has been observed in many complex networks. Previous works mainly focused on robust network design and on recovery strategies after sporadic or massive failures in the case of complete knowledge of failure location. We focus on cascading failures involving the power grid and its communication network with consequent imprecision in damage assessment. We tackle the problem of mitigating the ongoing cascading failure and providing a recovery strategy. We propose a failure mitigation strategy in two steps: 1) Once a cascading failure is detected, we limit further propagation by re-distributing the generator and load's power. 2) We formulate a recovery plan to maximize the total amount of power delivered to the demand loads during the recovery intervention. Our approach to cope with insufficient knowledge of damage locations is based on the use of a new algorithm to determine consistent failure sets (CFS). We show that, given knowledge of the system state before the disruption, the CFS algorithm can find all consistent sets of unknown failures in polynomial time provided that, each connected component of the disrupted graph has at least one line whose failure status is known to the controller.
AB - Vulnerability due to inter-connectivity of multiple networks has been observed in many complex networks. Previous works mainly focused on robust network design and on recovery strategies after sporadic or massive failures in the case of complete knowledge of failure location. We focus on cascading failures involving the power grid and its communication network with consequent imprecision in damage assessment. We tackle the problem of mitigating the ongoing cascading failure and providing a recovery strategy. We propose a failure mitigation strategy in two steps: 1) Once a cascading failure is detected, we limit further propagation by re-distributing the generator and load's power. 2) We formulate a recovery plan to maximize the total amount of power delivered to the demand loads during the recovery intervention. Our approach to cope with insufficient knowledge of damage locations is based on the use of a new algorithm to determine consistent failure sets (CFS). We show that, given knowledge of the system state before the disruption, the CFS algorithm can find all consistent sets of unknown failures in polynomial time provided that, each connected component of the disrupted graph has at least one line whose failure status is known to the controller.
UR - http://www.scopus.com/inward/record.url?scp=85038126055&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85038126055&partnerID=8YFLogxK
U2 - 10.1109/SRDS.2017.14
DO - 10.1109/SRDS.2017.14
M3 - Conference contribution
AN - SCOPUS:85038126055
T3 - Proceedings of the IEEE Symposium on Reliable Distributed Systems
SP - 54
EP - 63
BT - Proceedings - 2017 IEEE 36th International Symposium on Reliable Distributed Systems, SRDS 2017
PB - IEEE Computer Society
ER -