Energy Efficiency and Network Performance: A Reality Check in SDN-Based 5G Systems

Fernández-Fernández, Adriana; Cervelló-Pastor, Cristina; Aday, Leonardo Ochoa

doi:10.3390/en10122132

Cited by 17 publications

(11 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several energy harvesting techniques that can be utilized for wireless sensor networks are given in [79]. Here, the major techniques which can be utilized for energy harvesting are classified as cooperative communication [41,80,81], energy harvesting and wireless charging [76,82,83], radio optimization [84], modulation optimization [46,85,86], sleep/wake up mechanisms [87][88][89], multi path routing and data reduction techniques such as adaptive sampling, compression and network coding.…”

Section: Radio Frequency (Rf) Energy Harvestingmentioning

confidence: 99%

A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

et al. 2020

View full text Add to dashboard Cite

Energy efficiency is a major concern in the emerging mobile cellular wireless networks since massive connectivity is to be expected with high energy requirements from the network operators. Non-orthogonal multiple access (NOMA) being the frontier multiple access scheme for 5G, there exists numerous research attempts on enhancing the energy efficiency of NOMA enabled wireless networks while maintaining its outstanding performance metrics such as high throughput, data rates and capacity maximized optimally.The concept of green NOMA is introduced in a generalized manner to identify the energy efficient NOMA schemes. These schemes will result in an optimal scenario in which the energy generated for communication is managed sustainably. Hence, the effect on the environment, economy, living beings, etc is minimized. The recent research developments are classified for a better understanding of areas which are lacking attention and needs further improvement. Also, the performance comparison of energy efficient, NOMA schemes against conventional NOMA is presented. Finally, challenges and emerging research trends, for energy efficient NOMA are discussed.

show abstract

Section: Radio Frequency (Rf) Energy Harvestingmentioning

confidence: 99%

A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

et al. 2020

View full text Add to dashboard Cite

show abstract

“…If the extreme isolation of control and data plane could be relieved then the macro cell would be able to serve the users with not just the control signaling but also with data transfer at low frequencies, resulting in a higher percentage of energy savings in the network. In addition to this concept, Reference [64] discusses the possibility of achieving 50–80% energy savings by incorporation of the energy aware heuristic algorithms.…”

Section: Review Of Sdn Technology For Enhancing Eementioning

confidence: 99%

A Survey on Recent Trends and Open Issues in Energy Efficiency of 5G

Usama

Erol‐Kantarci

2019

Sensors

View full text Add to dashboard Cite

The rapidly increasing interest from various verticals for the upcoming 5th generation (5G) networks expect the network to support higher data rates and have an improved quality of service. This demand has been met so far by employing sophisticated transmission techniques including massive Multiple Input Multiple Output (MIMO), millimeter wave (mmWave) bands as well as bringing the computational power closer to the users via advanced baseband processing units at the base stations. Future evolution of the networks has also been assumed to open many new business horizons for the operators and the need of not only a resource efficient but also an energy efficient ecosystem has greatly been felt. The deployment of small cells has been envisioned as a promising answer for handling the massive heterogeneous traffic, but the adverse economic and environmental impacts cannot be neglected. Given that 10% of the world’s energy consumption is due to the Information and Communications Technology (ICT) industry, energy-efficiency has thus become one of the key performance indicators (KPI). Various avenues of optimization, game theory and machine learning have been investigated for enhancing power allocation for downlink and uplink channels, as well as other energy consumption/saving approaches. This paper surveys the recent works that address energy efficiency of the radio access as well as the core of wireless networks, and outlines related challenges and open issues.

show abstract

“…Software-defined networks (SDNs) is a relatively new concept that is used in several fields like in wireless sensor architectures [8,9], fifth-generation cellular systems (5G) [10,11], future smart systems [12] and cognitive routing [13]. SDN is becoming popular because of its flexibility to separate the hardware packet forwarding mechanism from the control logic [14,15].…”

Section: Introductionmentioning

confidence: 99%

Towards a Scalable Software Defined Network-on-Chip for Next Generation Cloud

Scionti

Mazumdar

Portero

2018

Sensors

View full text Add to dashboard Cite

The rapid evolution of Cloud-based services and the growing interest in deep learning (DL)-based applications is putting increasing pressure on hyperscalers and general purpose hardware designers to provide more efficient and scalable systems. Cloud-based infrastructures must consist of more energy efficient components. The evolution must take place from the core of the infrastructure (i.e., data centers (DCs)) to the edges (Edge computing) to adequately support new/future applications. Adaptability/elasticity is one of the features required to increase the performance-to-power ratios. Hardware-based mechanisms have been proposed to support system reconfiguration mostly at the processing elements level, while fewer studies have been carried out regarding scalable, modular interconnected sub-systems. In this paper, we propose a scalable Software Defined Network-on-Chip (SDNoC)-based architecture. Our solution can easily be adapted to support devices ranging from low-power computing nodes placed at the edge of the Cloud to high-performance many-core processors in the Cloud DCs, by leveraging on a modular design approach. The proposed design merges the benefits of hierarchical network-on-chip (NoC) topologies (via fusing the ring and the 2D-mesh topology), with those brought by dynamic reconfiguration (i.e., adaptation). Our proposed interconnect allows for creating different types of virtualised topologies aiming at serving different communication requirements and thus providing better resource partitioning (virtual tiles) for concurrent tasks. To further allow the software layer controlling and monitoring of the NoC subsystem, a few customised instructions supporting a data-driven program execution model (PXM) are added to the processing element’s instruction set architecture (ISA). In general, the data-driven programming and execution models are suitable for supporting the DL applications. We also introduce a mechanism to map a high-level programming language embedding concurrent execution models into the basic functionalities offered by our SDNoC for easing the programming of the proposed system. In the reported experiments, we compared our lightweight reconfigurable architecture to a conventional flattened 2D-mesh interconnection subsystem. Results show that our design provides an increment of the data traffic throughput of 9.5% and a reduction of 2.2× of the average packet latency, compared to the flattened 2D-mesh topology connecting the same number of processing elements (PEs) (up to 1024 cores). Similarly, power and resource (on FPGA devices) consumption is also low, confirming good scalability of the proposed architecture.

show abstract

Energy Efficiency and Network Performance: A Reality Check in SDN-Based 5G Systems

Cited by 17 publications

References 41 publications

A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

A Survey on Recent Trends and Open Issues in Energy Efficiency of 5G

Towards a Scalable Software Defined Network-on-Chip for Next Generation Cloud

Contact Info

Product

Resources

About