Optimal Use of Harvested Solar, Hybrid Storage and Base Station Resources for Green Cellular Networks

Chiang, Po-Han; Guruprasad, Ranjini; Dey, Sujit

doi:10.1109/tgcn.2018.2834519

Cited by 19 publications

(10 citation statements)

References 31 publications

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“…Despite of significant grid energy saving using MEC, the processing and content caching at the mobile edges still causes noticeable energy consumption especially in areas with dense deployment [19]. The integration of ambient renewable energy into the MEC has attracted the attentions from both academia and industry [9], [10], [20], [21]. In renewable energy-powered systems, the design objective should be improving the system performance subject to the available harvested energy since the renewable energy comes with very low cost.…”

Section: Related Workmentioning

confidence: 99%

“…However, these two works consider only either one edge server or one mobile device which can not be extended to large scale system in which the spatial diversity in the energy harvesting at different regions should be taken into account. Discussions on optimal battery storage size and efficient use of harvested energy in green cellular networks are detailed in respectively [20] and [21]. The existing works mainly focus on the computing performance of renewable energy-powered MEC system.…”

Section: Related Workmentioning

confidence: 99%

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Energy-Aware QoE and Backhaul Traffic Optimization in Green Edge Adaptive Mobile Video Streaming

Mehrabi

Siekkinen

Ylä-Jääski

2019

IEEE Trans. on Green Commun. Netw.

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Collaborative caching and processing at the network edges through mobile edge computing (MEC) helps to improve the quality of experience (QoE) of mobile clients and alleviate significant traffic on backhaul network. Due to the challenges posed by current grid powered MEC systems, the integration of time-varying renewable energy into the MEC known as green MEC (GMEC) is a viable emerging solution. In this paper, we investigate the enabling of GMEC on joint optimization of QoE of the mobile clients and backhaul traffic in particularly dynamic adaptive video streaming over HTTP (DASH) scenarios. Due to intractability, we design a greedy-based algorithm with self-tuning parameterization mechanism to solve the formulated problem. Simulation results reveal that GMEC-enabled DASH system indeed helps not only to decrease grid power consumption but also significantly reduce backhaul traffic and improve average video bitrate of the clients. We also find out a threshold on the capacity of energy storage of edge servers after which the average video bitrate and backhaul traffic reaches a stable point. Our results can be used as some guidelines for mobile network operators (MNOs) to judge the effectiveness of GMEC for adaptive video streaming in next generation of mobile networks. Index Terms-Green mobile edge computing (GMEC), DASH, Quality of experience (QoE), Fairness, Greedy-based algorithm. Antti Ylä-Jääski received the Ph.D. degree from ETH Zurich in 1993. From 1994 to 2009, he was with Nokia in several research and research management positions, with a focus on future Internet, mobile networks, applications, services, and service architectures. Since 2004, he has been a tenured Professor with the Department of Computer Science, Aalto University. His current research interests include mobile cloud computing, mobile multimedia systems, pervasive computing and communications, indoor positioning and navigation, energy efficient communications and computing, and Internet of Things.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Energy-Aware QoE and Backhaul Traffic Optimization in Green Edge Adaptive Mobile Video Streaming

Mehrabi

Siekkinen

Ylä-Jääski

2019

IEEE Trans. on Green Commun. Netw.

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“…Some applications to real-time dispatch issues with storage and renewables are reported: in [27], Lyapunov optimization is utilized to promote the integration of distributed renewable energy resources in smart grid system; a Lyapunov optimizationbased energy management strategy for the energy hub with an energy router is proposed in [28]. Besides, this method is also applied to edge computing [29] and mobile communication [30]. The above works employ the conventional Lyapunov optimization with infinite hozizon; the finite-horizon Lyapunov optimization method is first reported in in [31] by M. Dong et al, which introduces an offset term that represents the desired change of SoC level accross the finite time horizon; in recent years, it is used in [32] for joint storage-load scheduling and in [33] for bidirectional storage management in the residential side.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Self-Dispatch of a Remote Wind-Storage Integrated Power Plant Without Predictions: Explicit Policy and Performance Guarantee

Guo

Wei

Chen

et al. 2021

IEEE Open J. Power Energy

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“…Being motivated from the aforementioned concerns, envisioning the future access networks to be powered by the standalone renewable energy sources and the conjunction of RES with the conventional energy sources are the excellent alternates in order to achieve a green cellular communication with a minimum amount of toxic carbon contents under lowcost electricity. Several studies [18]- [20] have carried out for curving down the energy costs by adopting standalone renewable energy sources to power cellular networks. Nonetheless, this could lead to a severe mismatch between load demand and interruptible RE supply, especially for large-scale wireless networks.…”

Section: Introductionmentioning

confidence: 99%

Techno-Economic and Energy Efficiency Analysis of Optimal Power Supply Solutions for Green Cellular Base Stations

Jahid

Hossain²,

Monju

et al. 2020

IEEE Access

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The widespread proliferation of internet access, affordable wireless gadgets, the user data demand and the corresponding extended cellular networks entailing significant energy consumption and carbon footprints. With the added benefits of renewable energy harvesting (REH) technology, telecom base stations (BSs) are predominantly supplied by green power sources to reduce operational expenditure (OPEX) and atmospheric pollution with guaranteed quality of service (QoS). Accordingly, this paper examines the plausibility of optimal power supply solutions such as standalone solar photovoltaic (PV), hybrid PV/wind turbine (PV/WT), hybrid PV/diesel generator (DG) and hybrid PV/electric grid (PV/EG) to feed the Long Term Evolution (LTE) BSs pertaining to technical, economic and environmental aspects in Bangladesh. An extensive Monte-Carlo based simulations are performed to evaluate wireless network performance in terms of throughput, energy efficiency (EE), energy efficiency gain (EE gain), average energy savings, radio efficiency varying system bandwidth (B) and BS transmission power (P TX) considering the dynamic behavior of traffic intensity and renewable energy (RE) generation profile. By leveraging the cell zooming technique and a green traffic steering framework endeavors to minimize the net present cost and maximize the average energy savings as well. The simulation results reveal that the cell zooming technique attained energy savings yielding up to 36% and improvement of EE gain achieved about 23% with effective modeling of REH. Subsequently, a comprehensive comparison of the aforementioned schemes is pledged for further validation. INDEX TERMS Green cellular networks, renewable energy harvesting, hybrid energy, energy efficiency, cell zooming, eco-sustainability, LTE.

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Optimal Use of Harvested Solar, Hybrid Storage and Base Station Resources for Green Cellular Networks

Cited by 19 publications

References 31 publications

Energy-Aware QoE and Backhaul Traffic Optimization in Green Edge Adaptive Mobile Video Streaming

Energy-Aware QoE and Backhaul Traffic Optimization in Green Edge Adaptive Mobile Video Streaming

Real-Time Self-Dispatch of a Remote Wind-Storage Integrated Power Plant Without Predictions: Explicit Policy and Performance Guarantee

Techno-Economic and Energy Efficiency Analysis of Optimal Power Supply Solutions for Green Cellular Base Stations

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