Energy-Efficient UAV Deployment with Flexible Functional Split Selection

Wang, Liumeng; Zhou, Sheng

doi:10.1109/spawc.2018.8445959

Cited by 13 publications

(8 citation statements)

References 11 publications

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“…The energy consumption, together with functional split, is also studied in [48], using a real implementation based on Open Air Interface (OAI). Energy is also considered in [49], although in this case the flexible functional split is applied to optimize the energy consumption, including baseband processing, in scenarios with Unmanned Aerial Vehicles (UAVs) Finally, it is also worth mentioning some works that consider the interplay of functional split with techniques used for service deployment and provisioning in cellular networks. In this regard, functional split is considered in [50] as part of network slicing to ensure certain QoS.…”

Section: Related Workmentioning

confidence: 99%

Flexible Functional Split and Fronthaul Delay: A Queuing-Based Model

et al. 2021

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We study the delay over virtual RAN (vRAN) topologies, entailing base stations that are divided into centralized and distributed units, as well as the packet-switched fronthaul network that connects them. We consider the use of flexible functional split, where the functions that are executed at each of these two entities can be dynamically shifted. We propose a queuing-based model, which is able to precisely mimic the behavior of such nodes, and we validate it by means of extensive simulations. We also exploit Jackson Networks theory to establish the end-to-end delay over the fronthaul network, allowing us to assess the impact of having different networking policies and conditions (for instance, background traffic or heterogeneous technologies). Thanks to the simulator we can also broaden the analysis, by studying the delay variability. In addition, we conduct an in-depth analysis of the performance exhibited by a realistic network setup, whose particular characteristics might hinder the services performance, due to the longer dwell times at each split configuration. The results evince the validity of the proposed model, even under realistic conditions. We show that it might not be enough to guarantee an average stable operation of the centralized/distributed units, but the traffic load should remain below the slowest service rate, to avoid reaching unacceptable delays. An increase of > 100× is observed in the delay, using the realistic network setup, when these conditions do not hold.• We first extend the DU/CU model, by considering not only different service rates per split configuration, but also dwell times. In addition, this enhanced model also permits having different stand-by times after each split, and avoids the possibility of going to the same split after leaving it. • We exploit Jackson Theory and the CU/DU model to yield the overall end-to-end delay, considering the

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Section: Related Workmentioning

confidence: 99%

Flexible Functional Split and Fronthaul Delay: A Queuing-Based Model

et al. 2021

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“…Some works have also put emphasis on the impact that this type of architectures might have over energy consumption. In this sense, split selection is optimized considering energy constraints in [23], [24], while the authors of [25] propose an energy-aware split selection algorithm for scenarios with Unmanned Aerial Vehicles (UAVs). In the same line, the selection of functional splits in [26], as well as their duration, considers energy constraints over a network with energy harvesting-enabled radio elements.…”

Section: Related Workmentioning

confidence: 99%

Understanding the Performance of Flexible Functional Split in 5G vRAN Controllers: A Markov Chain-Based Model

Díez

Hervella

Agüero

2021

IEEE Trans. Netw. Serv. Manage.

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We study Flexible Functional Split functionality of 5G vRAN controllers in 5G networks. We propose an innovative model, based on a Markov Chain, which can be used to characterize their performance. We consider both infinite and finite-buffer controllers. In the former, frames would not be lost (provided the system works in a stable regime), and we thus focus on the time frames stay at the controller. For the finite-buffer controller, there might be losses, and we analyze the trade-off between time at the controller (which might hinder the stringent delay requirements of 5G services), and loss probability. Matrix-geometric techniques are used to resolve the corresponding Quasi-Birth-Death process. The validity of the proposed model is assessed by means of an extensive experiment campaign carried out over an ad-hoc eventdriven simulator, which is also used to broaden the analysis, considering different service rate distributions, as well as the variability of the studied performance indicators. The results show that the proposed model can be effectively exploited to tackle the dimensioning of these systems, as it sheds light on how their configuration impacts the expected delay and loss rate.

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“…Other works have proposed split selection algorithms in a variety of scenarios. For instance, jointly optimization of split selection and content caching is addressed in [12], while energy efficiency along with split selection, in a scenario with Unmanned Aerial Vehicles (UAVs), is considered in [13]. Other works vary in the constraints that are assumed, like energy [14], [15] or delay [16].…”

Section: Related Workmentioning

confidence: 99%

A Quasi-Birth-Death model for Functional Split in 5G Controllers

Díez

Hervella

Agüero

2021

ICC 2021 - IEEE International Conference on Communications

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It is broadly accepted that network function virtualization will play a key role to meet the stringent and heterogeneous requirements of 5G networks. Although fully centralized approaches were initially proposed, they may impose unfeasible requirements over fronthaul links. Consequently, flexible functional split solutions are being fostered, where a central controller adapts the centralization level to current circumstances. In spite of the growing interest in this type of solutions, most of existing works focus on real implementation, while little attention has been paid so far to performance modeling. In this paper we propose a Markov Chain based controller model, which boils down to a Quasi-Birth-Death process. Under reasonable assumptions, this model provides expected values of buffer occupancy and the time frames would spend in the controller. In this sense, it aims to be a tool to support the allocation of computational resources of the virtualized entities. We validate the proposed model by comparing its results with those obtained by simulation, evincing an almost perfect match between both approaches.

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Energy-Efficient UAV Deployment with Flexible Functional Split Selection

Cited by 13 publications

References 11 publications

Flexible Functional Split and Fronthaul Delay: A Queuing-Based Model

Flexible Functional Split and Fronthaul Delay: A Queuing-Based Model

Understanding the Performance of Flexible Functional Split in 5G vRAN Controllers: A Markov Chain-Based Model

A Quasi-Birth-Death model for Functional Split in 5G Controllers

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