Dynamic Controller Placement in Software Defined Drone Networks

Alharthi, Mohannad; Taha, Abd‐Elhamid M.; Hassanein, Hossam S.

doi:10.1109/globecom38437.2019.9013799

Cited by 4 publications

(7 citation statements)

References 13 publications

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“…Section 2.1) and execution (either static or progressive deployment of SDN devices within a legacy network). In particular, a progressive deployment might require adaptive solutions of the problem, as done in dynamic contexts such as vehicular networks [354], or the so-called Software-Defined Drone networks [355] and Software-Defined Satellite Networking [356]. -Legacy middleboxes.…”

Section: Open Research Challenges In Hsdnmentioning

confidence: 99%

Hybrid SDN evolution: A comprehensive survey of the state-of-the-art

et al. 2021

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Software-Defined Networking (SDN) is an evolutionary networking paradigm which has been adopted by large network and cloud providers, among which are Tech Giants. However, embracing a new and futuristic paradigm as an alternative to well-established and mature legacy networking paradigm requires a lot of time along with considerable financial resources and technical expertise. Consequently, many enterprises can not afford it. A compromise solution then is a hybrid networking environment (a.k.a. Hybrid SDN (hSDN)) in which SDN functionalities are leveraged while existing traditional network infrastructures are acknowledged.Recently, hSDN has been seen as a viable networking solution for a diverse range of businesses and organizations. Accordingly, the body of literature on hSDN research has improved remarkably. On this account, we present this paper as a comprehensive state-of-the-art survey which expands upon hSDN from many different perspectives.

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Section: Open Research Challenges In Hsdnmentioning

confidence: 99%

Hybrid SDN evolution: A comprehensive survey of the state-of-the-art

et al. 2021

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“…Kobo et al [27] proposed the CPP for Software Defined Wireless Sensor Networks (SDWSN). Recently, Alharthi et al [28] proposed a dynamic scheme for software defined drone networks. The objective of their solution is to minimize the number of drones that operate as SDN controllers and adjust their locations dynamically as the controlled nodes adjust their locations to meet changing mission requirements.…”

Section: Related Workmentioning

confidence: 99%

SDN Wireless Controller Placement Problem-The 4G LTE-U Case

et al. 2021

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To cope with the shortage of available licensed spectrum, 4th Generation Long Term Evolution (4G LTE) is expected to be deployed also in the unlicensed spectrum. This raises the problem of the coexistence of multiple operators. Obviously, a Software Defined Networking (SDN) based control approach can utilize the radio bandwidth by coordinating between multiple LTE-Unlicensed (LTE-U) operators. Within SDN control plane, there is a well-known issue namely the Controller Placement Problem (CPP) which has a major impact on the efficiency of the control plane. This paper addresses the Wireless Controller Placement Problem (WCPP) when the SouthBound interface (SBi) is based on 4G LTE unlicensed. The proposed solution improves the throughput, link failure probability and the transparency on the SBi from concurrent transmissions on the control plane. Two heuristic solutions are considered, one is a simulated annealing based and the other is a ray-shooting based. The simulation results show that they are fast and efficient and the ray-shooting based heuristic out-performs the simulated annealing based heuristic. In addition, it is shown that the transparency improves in bigger networks.

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“…They report that this "dynamic" approach outperforms the standard static approach by approximately an average of 20%. In [2], the authors formulate the DCP problem for an SDN enabled drone network as a Mixed Integer Non-linear Program (MINLP), and propose solving this problem using a heuristic that relies on decoupling the placement and assignment tasks.…”

Section: Literature Reviewmentioning

confidence: 99%

“…To summarize, there are two main approaches for the DCP problem in the literature. Either authors assume they proactively know the value of network variables in the future, as in [7], [14], [16], [18], or they rely on what we earlier described as the frame-by-frame approach, as in [2], [13] amongst others. Both of these methods fall short of realworld practicality.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A wide range of such networks may be found in the literature, e.g., Software Defined Vehicular Networks (SDVNs), Low Earth Orbit (LEO) constellations, Software Defined Mobile Networks (SDMNs), Aeronautical Telecommunication Networks 1 Authors are with Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, United States of America reza2@illinois.edu, beck3@illinois.edu (ATNs) or drone/UAV networks. Similar to the work presented in [2] and [3], we may assume controllers are SDNenabled aerial devices enabling a flying network infrastructure, as illustrated in Figure 1. A practical realization of such devices could be drones, or UAV's.…”

Section: Introductionmentioning

confidence: 99%

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RCP: A Temporal Clustering Algorithm for Real-time Controller Placement in Mobile SDN Systems

Soleymanifar¹,

Beck²

2021

Preprint

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Software Defined Networking (SDN) is a recent paradigm in telecommunication networks that disentangles data and control planes and brings more flexibility and efficiency to the network as a result. The Controller Placement (CP) problem in SDN, which is typically subject to specific optimality criteria, is one of the primary problems in the design of SDN systems. Dynamic Controller Placement (DCP) enables a placement solution that is adaptable to inherent variability in network components (traffic, locations, etc.). DCP has gained much attention in recent years, yet despite this, most solutions proposed in the literature cannot be implemented in real-time, which is a critical concern especially in UAV/drone based SDN networks where mobility is high and split second updates are necessary. As current conventional methods fail to be relevant to such scenarios, in this work we propose a real-time control placement (RCP) algorithm. Namely, we propose a temporal clustering algorithm that provides real-time solutions for DCP, based on a control theoretic framework for which we show the solution exponentially converges to a near-optimal placement of controller devices. RCP has linear O(n) iteration computational complexity with respect to the underlying network size, n, i.e., the number of nodes, and also leverages the maximum entropy principle from information theory. This approach results in high quality solutions that are practically immune from getting stuck in poor local optima, a drawback that most works in the literature are susceptible to. We compare our work with a frame-by-frame approach and demonstrate its superiority, both in terms of speed and incurred cost, via simulations. According to our simulations RCP can be up to 25 times faster than the conventional frame-by-frame method.

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Dynamic Controller Placement in Software Defined Drone Networks

Cited by 4 publications

References 13 publications

Hybrid SDN evolution: A comprehensive survey of the state-of-the-art

Hybrid SDN evolution: A comprehensive survey of the state-of-the-art

SDN Wireless Controller Placement Problem-The 4G LTE-U Case

RCP: A Temporal Clustering Algorithm for Real-time Controller Placement in Mobile SDN Systems

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