SDN-Controller Placement for D2D Communications

Llerena, Yarisley Peña; Gondim, Paulo Roberto de Lira

doi:10.1109/access.2019.2955434

Cited by 16 publications

(9 citation statements)

References 31 publications

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“…The authors in [31] used simulated annealing for joint controller and satellite gateway placement. An ant colony with an external memory CPP algorithm was proposed in [14] and validated against particle swarm optimization (PSO) for load balancing. In [32], the authors explored the load-balancing CPP with a predetermined number of controllers, addressing proactive and reactive controller-node assignments.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The majority of CPP research has focused on minimizing the controller deployment cost while achieving low latency [4], [6], [7], [9], [13], [14], [16], [17], [24]- [27], [29]. Other works expanded their scope to include load balancing among distributed controllers and considerations of computational and storage power [6], [7], [13], [14], [16], [17], [25], [26].…”

Section: Literature Reviewmentioning

confidence: 99%

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On Robust Optimal Joint Deployment and Assignment of RAN Intelligent Controllers in O-RANs

Abdel-Rahman,

Mazied,

Hassan

et al. 2024

IEEE Open J. Commun. Soc.

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The open radio access network (O-RAN) architecture is consolidating the concept of softwaredefined cellular networks beyond 5G networks, mainly through the introduction of the near-real-time radio access network (RAN) intelligent controller (Near-RT RIC) and the xApps. The deployment of the Near-RT RICs and the assignment of RAN nodes to the deployed RICs play a crucial role in optimizing the performance of O-RANs. In this paper, we develop a robust optimization framework for joint RIC deployment and assignment, considering the uncertainty in user locations. Specifically, our contributions are as follows. First, we develop C 3 P 2 , a robust static joint RIC placement and RAN node-RIC assignment scheme. The objective of C 3 P 2 is to minimize the number of RICs needed to control all RAN nodes while ensuring that the response time to each RAN node will not exceed δ milliseconds with a probability greater than β. Second, we develop CPPA, a robust joint RIC placement and adaptive RAN node-RIC assignment scheme. In contrast to C 3 P 2 , CPPA enjoys a recourse capability, where the RAN node-RIC assignment adapts to the variations in the user locations. We use chance-constrained stochastic optimization combined with several linearization techniques to develop a mixed-integer linear (MIL) formulation for C 3 P 2 . Two-stage stochastic optimization with recourse, combined with several linearization techniques, is used to develop an MIL formulation for CPPA. The optimal performance of C 3 P 2 and CPPA has been examined under various system parameter values. Furthermore, sample average approximation has been employed to design efficient approximate algorithms for solving C 3 P 2 and CPPA. Our results demonstrate the robustness of the proposed stochastic resource allocation schemes for O-RANs compared to existing deterministic allocation schemes. They also show the merits of adapting the allocation of resources to the network uncertainties compared to statically allocating them.INDEX TERMS Open radio access networks (O-RANs), RAN intelligent controller (RIC) placement, RIC assignment, chance-constrained stochastic optimization, two-stage stochastic optimization with recourse, sample average approximation.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

On Robust Optimal Joint Deployment and Assignment of RAN Intelligent Controllers in O-RANs

Abdel-Rahman,

Mazied,

Hassan

et al. 2024

IEEE Open J. Commun. Soc.

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“…And when the controller is overloaded then, it affects the QoS metrics. The authors in [18] have added external memory to the ant colony system to solve the controller placement problem. The results obtained were compared with those of PSO to verify the effectiveness.…”

Section: Related Reviewmentioning

confidence: 99%

Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

Belgaum¹,

Ali²,

Alansari³

et al. 2022

Computers, Materials &Amp; Continua

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Software-defined networking (SDN) plays a critical role in transforming networking from traditional to intelligent networking. The increasing demand for services from cloud users has increased the load on the network. An efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service (QoS). The multiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best algorithms. Moreover, the requests need to be transferred to reliable network elements. To address SDN's current and future challenges, there is a need to know how artificial intelligence (AI) optimization techniques can efficiently balance the load. This study aims to explore two artificial intelligence optimization techniques, namely Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO), used for load balancing in SDN. Further, we identified that a modification to the existing optimization technique could improve the performance by using a reliable link and node to form the path to reach the target node and improve load balancing. Finally, we propose a conceptual framework for SDN futurology by evaluating node and link reliability, which can balance the load efficiently and improve QoS in SDN.

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“…According to Mohit et al [6], it fails to preserve system anonymity and security if the patient's device is lost or stolen. On the other hand, the protocol of Mohit et al [5] fails to avoid a denial of service (DoS) attack.…”

Section: Related Workmentioning

confidence: 99%

“…One of the requirements for proper functioning of e-health/m-health/TMIS and other systems for the IoT is reductions in both the consumption of computational and communication resources for energy saving and the congestion In this study, we have considered D2D communication with establishing/managing connection through the cellular infrastructure. Among its advantages are possible offloading between the mobile network and the D2D network, and efficient allocation of the spectrum if inband D2D is used [5]. Therefore, if some information collected by a sensor used by a patient is to be transmitted through a cellular network and indicates an emergency which demands rapid decision and actuation by a physician and/or a health center, D2D communications are an excellent alternative for its rapid transmission.…”

Section: Introductionmentioning

confidence: 99%

Mutual Authentication Protocol for D2D Communications in a Cloud-Based E-Health System

Lopes

Gondim

2020

Sensors

Self Cite

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The development of the Internet of Things (IoT) predicts several new applications, some of which are designed to be incorporated into e-health systems, and some technologies, like cloud computing and device-to-device communication (D2D), are promising for use in the support of resource-constrained devices employed in Mobile-health (m-health) and Telecare Medicine Information Systems (TMIS). In a scenario with billions of devices predicted for the IoT, it is essential to avoid performance and security problems, among others. Security is fundamental for the achievement of optimal performance regarding the sensibility of e-health shared data and, especially, the anonymity of patients and other entities, while it is also essential to consider the scarcity of bandwidth in wireless networks. This paper proposes a new mutual authentication protocol for m-health systems, which supports D2D communication, ensuring security and surpassing the performance and security of other authentication procedures reported in the literature. on communication channels, given a large number of new emerging devices. Therefore, computational costs must be reduced for the optimization of power resources.On the other hand, device-to-device (D2D) communication, commonly implemented by ad hoc wireless networks, enables patients' devices to connect directly to a medical entity to send health data collected by sensors and receive diagnoses faster than in the traditional way. The constant monitoring of patients and analyses of health reports are crucial for the avoidance of medical conditions, such as strokes and heart attacks, because the chances of a person being sick can be detected much faster.D2D communication provides a direct connection of devices with or without the intervention of traditional network infrastructure (e.g., 3rd Generation Partnership Project (3GPP) standards). Therefore, the ability to connect devices can provide data offload through nearby devices directly, thus reducing problems, such as congestion and scarcity of spectrum, and expanding network coverage by enabling devices to relay their data. D2D communication is promising for 5G technology and IoT due to its adaptation to support small and resource-constrained devices predicted by those two technologies. However, security schemes for D2D communication are still in the initial development stages, which require more research and studies for their improvement and consolidation, in addition to authentication and key agreement protocols adapted to them.D2D is suitable for e-health/m-health/TMIS since it can accelerate the transmission of data and provide a connection to devices located outside the coverage of 3GPP networks. This might be the key for the success of e-health/m-health/TMIS applications, because most data exchanged provide information on patients' health, e.g., heartbeat, blood sugar, and pressure, which is sensitive to delays for saving lives. Moreover, since e-health/m-health/TMIS devices are mostly resource-constrained, they require adapted traditional aut...

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SDN-Controller Placement for D2D Communications

Cited by 16 publications

References 31 publications

On Robust Optimal Joint Deployment and Assignment of RAN Intelligent Controllers in O-RANs

On Robust Optimal Joint Deployment and Assignment of RAN Intelligent Controllers in O-RANs

Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

Mutual Authentication Protocol for D2D Communications in a Cloud-Based E-Health System

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