On-Demand Dynamic Controller Placement in Software Defined Satellite-Terrestrial Networking

Author(s):  
Zhenzhen Han ◽  
Chuan Xu ◽  
Zhengying Xiong ◽  
Guofeng Zhao ◽  
Shui Yu
Author(s):  
Saumya Hegde ◽  
Roshni Ajayghosh ◽  
Shashidhar G. Koolagudi ◽  
Swapan Bhattacharya

2017 ◽  
Vol 14 (1) ◽  
pp. 63-76 ◽  
Author(s):  
Md Tanvir Ishtaique ul Huque ◽  
Weisheng Si ◽  
Guillaume Jourjon ◽  
Vincent Gramoli

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1701 ◽  
Author(s):  
Soufian Toufga ◽  
Slim Abdellatif ◽  
Hamza Tarik Assouane ◽  
Philippe Owezarski ◽  
Thierry Villemur

The emerging SDVN (Software Defined Vehicular Network) paradigm promises to bring flexibility and efficient resource utilization to vehicular networks, enabling the emergence of novel Intelligent Transportation Services. However, as it was initially designed with wired network in mind, applying the SDN paradigm to a vehicular context faces new challenges related to the peculiar characteristics of this network (high node mobility and node density, and the presence of wireless links). In this paper, we focus on one of the critical architectural elements of SDVN, namely, the SDN Controller Placement, and promote the use of dynamic placement methods that take into account the dynamicity of vehicular networks’ topology. We also describe the different approaches towards a dynamic controller placement and also propose an ILP (Integer Linear Programming) based dynamic placement method that adaptively readjusts the number and placement of controllers according to road traffic fluctuations. The proposed method is evaluated using a realistic traffic trace from Luxembourg City. Simulation results show that our approach outperforms the static approach as proposed in the literature.


2020 ◽  
Author(s):  
Marcus Vinícius Souza Costa ◽  
Vitor Barbosa Souza

The deployment of a dynamic and cooperative fog control plane, where controllers are selected on-demand among the most suitable underlying resources, has been recently proposed as a Control-as-a-Service (CaaS) model. Albeit it is expected that real-time applications shall benefit from this concept, mechanisms for QoS-aware controllers election is yet an open issue. In this work, we propose an adaptive rank-based controller selection strategy that is capable of tuning the weights employed for each characteristic of interest in order to cope with the environment dynamism. Results have shown an average controller exchange reduction of 37% when compared with a preliminary approach employing fixed weights in a dynamic scenario, as well as its efficiency in battery and memory usage by controllers.


2021 ◽  
Vol 68 (3) ◽  
pp. 3391-3410
Author(s):  
Ali Abdi Seyedkolaei ◽  
Seyed Amin Hosseini Seno ◽  
Rahmat Budiarto

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