Optimized load balancing by dynamic BBU-RRH mapping in C-RAN architecture

Paixão, Ermínio Augusto Ramos da; Vieira, Rafael Fogarolli; Araújo, Welton Vasconcelos; Cardoso, Diego Lisboa

doi:10.1109/fmec.2018.8364051

Cited by 12 publications

(8 citation statements)

References 3 publications

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“…K-means performed well in terms of the number of clusters and tightness of the clusters, although it required a longer time to attain convergence. In [58], through simulation, the performance of the proposed algorithm was compared with a solution proposed in the literature [60], having an identical scenario and another optimal solution that divides the users between BBU sectors without considering their distributions in the RRHs. The load balancing of BBUs considering a different number of users was considered as the performance metric.…”

Section: Evaluation Techniques For Rrh Clustering Methodsmentioning

confidence: 99%

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Resource Management in Cloud Radio Access Network: Conventional and New Approaches

Rodoshi

Kim

Choi

2020

Sensors

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Cloud radio access network (C-RAN) is a promising mobile wireless sensor network architecture to address the challenges of ever-increasing mobile data traffic and network costs. C-RAN is a practical solution to the strict energy-constrained wireless sensor nodes, often found in Internet of Things (IoT) applications. Although this architecture can provide energy efficiency and reduce cost, it is a challenging task in C-RAN to utilize the resources efficiently, considering the dynamic real-time environment. Several research works have proposed different methodologies for effective resource management in C-RAN. This study performs a comprehensive survey on the state-of-the-art resource management techniques that have been proposed recently for this architecture. The resource management techniques are categorized into computational resource management (CRM) and radio resource management (RRM) techniques. Then both of the techniques are further classified and analyzed based on the strategies used in the studies. Remote radio head (RRH) clustering schemes used in CRM techniques are discussed extensively. In this research work, the investigated performance metrics and their validation techniques are critically analyzed. Moreover, other important challenges and open research issues for efficient resource management in C-RAN are highlighted to provide future research direction.

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Section: Evaluation Techniques For Rrh Clustering Methodsmentioning

confidence: 99%

“…In [58], the authors investigated the load-balancing problem in a C-RAN. The objective was to reduce the number of blocked calls and maximize the QoS.…”

Section: Qos-aware Rrh Clusteringmentioning

confidence: 99%

Resource Management in Cloud Radio Access Network: Conventional and New Approaches

Rodoshi

Kim

Choi

2020

Sensors

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“…A reinforcement algorithm was proposed in [33] for ORAN radio intelligent controller. load balancing in cloud radio access network can be found in [34], [35] and [36]. However, neither of these studies incorporated a quantum domain in their work, nor did they address the EE of ORAN.…”

Section: A Related Workmentioning

confidence: 99%

Optimizing the Energy Efficiency Using Quantum Based Load Balancing in Open Radio Access Networks

Al-Karawi,

Al-Raweshidy,

Nilavalan

2024

IEEE Access

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The open radio access network (ORAN) aims to improve network efficiency by reducing latency through the distributed unit (DU) and virtualization in the central unit (CU). However, the deployment of additional DU servers increases power usage and competition among virtual machines for user data processing. This study proposes a novel approach to address these challenges by incorporating load balancing strategies and quantum physics concepts, particularly entanglement theory in classical communication systems. The methodology enables the production of quantum information units from a single classical information unit, aiming to conserve energy. A simplified yet effective power consumption (PC) model for the ORAN architecture captures traffic fluctuations and provides a comprehensive characterization of power usage within a virtualized system. An optimization problem is formulated to select ORAN servers for quantum load balancing that are less energy-efficient, maximizing user benefits. The Lagrange multiplier method is used to deal with nonlinear objective functions. The presented problem is addressed through the use of two numerical methods, namely sequential quadratic programming (SQP) and the active-set approach. It is shown that the SQP model exhibits superior energy efficiency compared to the active-set model, with a difference of approximately 45%.

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“…Simulation results show a reduction of 100% in the number of blocked calls. A similar strategy is adopted in [18], although the authors address the problem by employing the particle swarm optimization (PSO), where the best solution is randomly determined on the basis of the speed and position of the particles with the best values for testing aptitude. The results obtained show improvements of up to 100% on blocked calls when QoS factors are taken into account.…”

Section: Related Workmentioning

confidence: 99%

An Intelligent SDN Framework Based on QoE Predictions for Load Balancing in C-RAN

Medeiros

Costa

Cardoso

et al. 2020

Wireless Communications and Mobile Computing

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The rapid growth of the Internet and technological advances are forcing mobile operators to increasingly invest in network infrastructures. C-RAN and SDN are regarded as enabling technologies that can overcome the limitations faced by operators, by reducing costs, increasing scalability, and paving the way for the next generation of 5G cellular networks. In this paper, an architectural solution based on SDN and computational intelligence is proposed for C-RAN, which can adjust BBU-RRH mapping through network load balancing rules by predicting subjective and objective QoE metrics for UHD video streaming. The simulation results achieved gains between 59% and 129%, in scenarios without activating a new BBU and scenarios that involve activating a new BBU, respectively.

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Optimized load balancing by dynamic BBU-RRH mapping in C-RAN architecture

Cited by 12 publications

References 3 publications

Resource Management in Cloud Radio Access Network: Conventional and New Approaches

Resource Management in Cloud Radio Access Network: Conventional and New Approaches

Optimizing the Energy Efficiency Using Quantum Based Load Balancing in Open Radio Access Networks

An Intelligent SDN Framework Based on QoE Predictions for Load Balancing in C-RAN

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