Implementation of Multiple Controllers to Remove the Threat of a Single Point of Failure in the Software Defined Networks

2020 ◽  
Vol 14 (7) ◽  
Keyword(s):  
Single Point ◽  
Software Defined Networks ◽  
Multiple Controllers

scholarly journals To eliminate the threat of a Single Point of Failure in the SDN by using the Multiple Controllers

2020 ◽  
Vol 9 (2) ◽  
pp. 234-241
Keyword(s):  
Single Point ◽  
High Availability ◽  
Software Defined Network ◽  
Tolerance Mechanism ◽  
Control Logic ◽  
Global View ◽  
Single Controller ◽  
Entire Network ◽  
Sdn Controller ◽  
Multiple Controllers

The Software Defined Network (SDN) provides an innovative paradigm for networking, which improve the programmability and flexibility of the network. Due to the separation between the control and data plane, all the control logic transfer to the controller. In SDN, the controller, which provides a global view of the whole network. That is why it acts as the “Network Brain” of the network. Because the controller has the capability to configure or reconfigure the forwarding devices by customizing their policies in a dynamic manner. Thus, the controller provides a centralized logical view of the entire network. Therefore, all manipulation and implementation in the network are control by the single controller in the SDN, which increases the maximum chance of a single point of failure (SPOF) in the network. As a consequence, it collapses the entire network. Therefore, a fault tolerance mechanism is required which reduce single point of failure in the network by using multiple controllers. As a significance, this mechanism also increases the scalability, reliability, and high availability of services in the network. The three different roles of multiple controllers are equal, master and slave exist in the SDN. In the simulation, the Ryu SDN controller and Mininet tool are utilized. During the simulation to analysis, what is happen when a single point of failure (SPOF) occur in the network and how to use the different roles of the multiple controllers (such as equal, master and slave) which reduces the threat of single point of failure in SDN network.

Load-balancing routing in software defined networks with multiple controllers

2018 ◽  
Vol 141 ◽  
pp. 82-91 ◽  
Author(s):  
Haibo Wang ◽  
Hongli Xu ◽  
Liusheng Huang ◽  
Jianxin Wang ◽  
Xuwei Yang
Keyword(s):  
Load Balancing ◽  
Software Defined Networks ◽  
Multiple Controllers

Augmented Affinity Propagation-Based Network Partitioning for Multiple Controllers Placement in Software Defined Networks

2020 ◽  
Vol 17 (1) ◽  
pp. 228-233
Author(s):  
C. N. Sminesh ◽  
E. Grace Mary Kanaga ◽  
A. G. Sreejish
Keyword(s):  
Large Scale ◽  
Affinity Propagation ◽  
Software Defined Networks ◽  
Network Partitioning ◽  
Control Plane ◽  
Placement Problem ◽  
Large Scale Network ◽  
Scale Network ◽  
Controller Placement Problem ◽  
Multiple Controllers

Software Defined Networks (SDN) divide network intelligence and packet forwarding functionalities between control plane and data plane devices respectively. Multiple controllers need to be deployed in the control plane in large SDN networks to improve performance and scalability. In a multi-controller scenario, finding the adequate number of controllers and their load distribution are open research challenges. In a large-scale network, the control plane load balancing is termed a controller placement problem (CPP). It is observed that of the existing solutions for the CPP, clustering-based approaches provide computationally less intensive solutions. The proposed augmented affinity propagation (augmented-AP) clustering identifies the required number of network partitions and places the controllers such that the distribution of switches to the controller is much better than with existing algorithms. The simulation results show that the computed controller imbalance factor of augmented-AP algorithm outperforms the existing k-means algorithm.

Fine-scale taxonomic and temporal variability in the energy density of invertebrate prey of juvenile Chinook salmon Oncorhynchus tshawytscha

2020 ◽  
Vol 655 ◽  
pp. 185-198
Author(s):  
J Weil ◽  
WDP Duguid ◽  
F Juanes
Keyword(s):  
Energy Density ◽  
Chinook Salmon ◽  
Temporal Variability ◽  
Energy Content ◽  
Single Point ◽  
Single Species ◽  
Fine Scale ◽  
Temporal Differences ◽  
Juvenile Chinook Salmon ◽  
Juvenile Chinook

Variation in the energy content of prey can drive the diet choice, growth and ultimate survival of consumers. In Pacific salmon species, obtaining sufficient energy for rapid growth during early marine residence is hypothesized to reduce the risk of size-selective mortality. In order to determine the energetic benefit of feeding choices for individuals, accurate estimates of energy density (ED) across prey groups are required. Frequently, a single species is assumed to be representative of a larger taxonomic group or related species. Further, single-point estimates are often assumed to be representative of a group across seasons, despite temporal variability. To test the validity of these practices, we sampled zooplankton prey of juvenile Chinook salmon to investigate fine-scale taxonomic and temporal differences in ED. Using a recently developed model to estimate the ED of organisms using percent ash-free dry weight, we compared energy content of several groups that are typically grouped together in growth studies. Decapod megalopae were more energy rich than zoeae and showed family-level variability in ED. Amphipods showed significant species-level variability in ED. Temporal differences were observed, but patterns were not consistent among groups. Bioenergetic model simulations showed that growth rate of juvenile Chinook salmon was almost identical when prey ED values were calculated on a fine scale or on a taxon-averaged coarse scale. However, single-species representative calculations of prey ED yielded highly variable output in growth depending on the representative species used. These results suggest that the latter approach may yield significantly biased results.

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