The wireless control plane: An overview and directions for future research

Mazied, EmadelDin A.; ElNainay, Mustafa; Abdel-Rahman, Mohammad J.; Midkiff, Scott F.; Rizk, Mohamed R. M.; Rakha, Hesham A.; MacKenzie, Allen B.

doi:10.1016/j.jnca.2018.09.017

Cited by 14 publications

(9 citation statements)

References 50 publications

(131 reference statements)

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“…The integration of NFV and SDN technologies in the area of UAV networks is still at its infancy [264]. Indeed, this integration can provide novel support for both the deployment of UAV network services and the increasing business of UAV products [265]. Furthermore, this technology aims to provide high-performance processing of data traffic through the next generation of mobile networks, and especially when they are supported by UAVs [266].…”

Section: B Other Nfv-enabled Applicationsmentioning

confidence: 99%

Softwarization of UAV Networks: A Survey of Applications and Future Trends

et al. 2020

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Unmanned Aerial Vehicles (UAVs) have become increasingly important in assisting 5G and beyond 5G (B5G) mobile networks. Indeed, UAVs have all the potentials to both satisfy the ever-increasing mobile data demands of such mobile networks and provide ubiquitous connectivity to different kinds of wireless devices. However, the UAV assistance paradigm faces a set of crucial issues and challenges. For example, the network management of current UAV-assisted systems is time consuming, complicated, and carried out manually, thus causing a multitude of interoperability issues. To efficiently address all these issues, Software-Defined Network (SDN) and Network Function Virtualization (NFV) are two promising technologies to efficiently manage and improve the UAV assistance for the next generation of mobile networks. In the literature, no clear guidelines are describing the different use cases of SDN and NFV in the context of UAV assistance to terrestrial networks, including mobile networks. Motivated by this fact, in this survey, we guide the reader through a comprehensive discussion of the main characteristics of SDN and NFV technologies. Moreover, we provide a thorough analysis of the different classifications, use cases, and challenges related to UAV-assisted systems. We then discuss SDN/NFV-enabled UAV-assisted systems, along with several case studies and issues, such as the involvement of UAVs in cellular communications, monitoring, and routing, to name a few. We furthermore present a set of open research challenges, high-level insights, and future research directions related to UAV-assisted systems.

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Section: B Other Nfv-enabled Applicationsmentioning

confidence: 99%

Softwarization of UAV Networks: A Survey of Applications and Future Trends

et al. 2020

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“…Recently, there has been increasing interest in a wireless SBi in which the controllers communicate with the data plane switches over a wireless channel. Mazied et al [17] claimed that the integration of SDN to 5G networks requires a wireless SBi in which the controllers communicate with the data plane over a wireless channel. However, a wireless SBi is more complicated and suffers from other shortcomings such as radio interference.…”

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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“…An outline and directions of the wireless control plane (WCP) were introduced by Mohammad et al for future investigation. A summary of the WCP scheme of D‐WCP and I‐WCP was described in this paper.…”

Section: Literature Surveymentioning

confidence: 99%

Assimilation of fuzzy clustering approach and EHO‐Greedy algorithm for efficient routing in WSN

Pattnaik

Sahu

2020

Int J Communication

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Summary The problems related to energy consumption and improvement of the network lifetime of WSN (wireless sensor network) have been considered. The base station (BS) location is the main concern in WSN. BSs are fixed, yet, they have the ability to move in some situations to collect the information from sensor nodes (SNs). Recently, introducing mobile sinks to WSNs has been proved to be an efficient way to extend the lifespan of the network. This paper proposes the assimilation of the fuzzy clustering approach and the Elephant Herding Optimization (EHO)‐Greedy algorithm for efficient routing in WSN. This work considers the separate sink nodes of a fixed sink and movable sink to decrease the utilization of energy. A fixed node is deployed randomly across the network, and the movable sink node moves to different locations across the network for collecting the data. Initially, the number of nodes is formed into the multiple clusters using the enhanced expectation maximization algorithm. After that, the cluster head (CH) selection done through a fuzzy approach by taking the account of three factors of residual energy, node centrality, and neighborhood overlap. A suitable collection of CH can extremely reduce the utilization of energy and also enhancing the lifespan. Finally, the routing protocol of the hybrid EHO‐Greedy algorithm is used for efficient data transmission. Simulation results display that the proposed technique is better to other existing approaches in regard to energy utilization and the system lifetime.

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The wireless control plane: An overview and directions for future research

Cited by 14 publications

References 50 publications

Softwarization of UAV Networks: A Survey of Applications and Future Trends

Softwarization of UAV Networks: A Survey of Applications and Future Trends

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

Assimilation of fuzzy clustering approach and EHO‐Greedy algorithm for efficient routing in WSN

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