A Game Model and Fault Recovery Algorithm for SDN Multi-Domain.

Sensors (Basel)

The College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Published: December 2024

Software-defined networking (SDN) offers an effective solution for flexible management of Wireless Sensor Networks (WSNs) by separating control logic from sensor nodes. This paper tackles the challenge of timely recovery from SDN controller failures and proposes a game theoretic model for multi-domain controllers. A game-enhanced autonomous fault recovery algorithm for SDN controllers is proposed, which boasts fast fault recovery and low migration costs. Taking into account the remaining capacity of controllers and the transition relationships between devices, the target controller is first selected to establish a controller game domain. The issue of mapping the out-of-control switches within the controller game domain to the target controller is transformed into a linear programming problem for solution. A multi-population particle swarm optimization algorithm with repulsive interaction is employed to iteratively evolve the optimal mapping between controllers and switches. Finally, migration tasks are executed based on the optimal mapping results, and the role transition of the target controller is completed. Comparative experimental results demonstrate that, compared to existing SDN controller fault recovery algorithms, the proposed algorithm can balance the migration cost of switches and the load pressure on controllers while reducing propagation delay in SDN controllers, significantly decreasing the fault recovery time.

Download full-text PDF

Source
http://dx.doi.org/10.3390/s25010164DOI Listing

Publication Analysis

Top Keywords

fault recovery
20
target controller
12
recovery algorithm
8
algorithm sdn
8
sdn controller
8
sdn controllers
8
controller game
8
game domain
8
optimal mapping
8
controller
7

Similar Publications

A Game Model and Fault Recovery Algorithm for SDN Multi-Domain.

Sensors (Basel)

December 2024

The College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Software-defined networking (SDN) offers an effective solution for flexible management of Wireless Sensor Networks (WSNs) by separating control logic from sensor nodes. This paper tackles the challenge of timely recovery from SDN controller failures and proposes a game theoretic model for multi-domain controllers. A game-enhanced autonomous fault recovery algorithm for SDN controllers is proposed, which boasts fast fault recovery and low migration costs.

View Article and Find Full Text PDF

One of the leading challenges in Water Resource Recovery Facility monitoring and control is the poor data quality and sensor consistency due to the tough and complex circumstances of the process operation. This paper presents a new principal component analysis fault detection approach for the nitrate and nitrite concentration sensor based on Water Resource Recovery Facility measurements, together with the Fisher Discriminant Analysis identification of fault types. Five malfunction cases were considered: constant additive error, ramp changing error in time, incorrect amplification error, random additive error, and unchanging sensor value error.

View Article and Find Full Text PDF

Fuzzy modelling and cost optimization of fault-tolerant system with service interruption.

ISA Trans

December 2024

Department of Mathematics, Deshbandhu College, University of Delhi, New Delhi 110019, India. Electronic address:

Redundancy and maintainability-supported fault-tolerant machining systems are used in many industries to achieve pre-specified reliability and system capability. In this investigation, a non-Markov model for the machining system has been developed by involving the concepts of server vacation, server breakdown, and reboot process. The server may fail and undergo primary repair which may be unsuccessful in recovering the server.

View Article and Find Full Text PDF

We use seismic waves that pass through the hypocentral region of the 2016 M6.5 Norcia earthquake together with Deep Learning (DL) to distinguish between foreshocks, aftershocks and time-to-failure (TTF). Binary and N-class models defined by TTF correctly identify seismograms in test with > 90% accuracy.

View Article and Find Full Text PDF
Article Synopsis
  • Bangladesh is focusing on enhancing power generation with ambitious plans, including a 2∗660 MW coal-power station in Patuakhali set to begin operations in December 2024.
  • The technology proposed aims to tackle CO emissions, which are a concern for health and biodiversity, while exploring solvents like monoethanolamine (MEA) for carbon capture, though challenges like corrosiveness and high energy demand persist.
  • Current CO removal technologies face drawbacks, necessitating modifications for higher efficiency, and the study indicates a significant daily carbon emission of approximately 4.806 million kilograms from the power plant.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!