SooGREEN: Service-oriented optimization of green mobile networks

The fifth generation (5G) of cellular networks promises to be a major step in the evolution of wireless technology. 5G is planned to be used in a very broad set of application scenarios. These scenarios have strict heterogeneous requirements that will be accomplished by enhancements on the radio access network and a collection of innovative wireless technologies. Softwarization technologies, such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV), will play a key role in integrating these different technologies. Network slicing emerges as a cost-efficient solution for the implementation of the diverse 5G requirements and verticals. The 5G radio access and core networks will be based on a SDN/NFV infrastructure, which will be able to orchestrate the resources and control the network in order to efficiently and flexibly and with scalability provide network services. In this paper, we present the up-to-date status of the software-defined 5G radio access and core networks and a broad range of future research challenges on the orchestration and control aspects.

show abstract

“…In the current works the target has mainly been energy efficiency [88,89]. However, multiple targets need to be taken into account.…”

Section: Channel Selectionmentioning

confidence: 99%

Orchestration and Control in Software‐Defined 5G Networks: Research Challenges

Nencioni

Garroppo

Gonzalez

et al. 2018

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…Equally, such data is crucial in planning and configuration of edge computing and storage infrastructure to optimize latency for certain services and benefit others by computation offloading to the edge cloud [5], [6]. Furthermore, service-level traffic data is key to other service oriented studies within networking, including the design of traffic classification techniques [7] and energy efficiency optimization [8], and beyond, such as for data plan analysis [9], [10] or to reveal links between apps consumption and urbanization levels or socioeconomic status [11], [12].…”

Section: Introductionmentioning

confidence: 99%

AppShot: A Conditional Deep Generative Model for Synthesizing Service-Level Mobile Traffic Snapshots at City Scale

Sun

Fiore

et al. 2022

IEEE Trans. Netw. Serv. Manage.

View full text Add to dashboard Cite

Service-level mobile traffic data enables research studies and innovative applications with a potential to shape future service-oriented communication systems and beyond. However, real-world datasets reporting measurements at the individual service level are hard to access as such data is deemed commercially sensitive by operators. APPSHOT is a model for generating synthetic high-fidelity city-scale snapshots of service level mobile traffic. It can operate in any geographical region and relies solely on easily available spatial context information such as population density, thus allowing the generation of new and open traffic datasets for the research community. The design of APPSHOT is informed by an original characterization of servicelevel mobile traffic data. APPSHOT is a novel conditional GAN design instantiated by a convolutional neural network generator and two discriminators. The model features several other innovative mechanisms including multi-channel and overlapping patch based generation to address the unique challenges involved in generating mobile service traffic snapshots. Experiments with ground-truth data collected by a major European operator in multiple metropolitan areas show that APPSHOT can produce realistic network loads at the service level for areas where it has no prior traffic knowledge, and that such data can reliably support service-oriented networking studies.

show abstract

“…This can be explained by the complex nature brought by interconnected network equipment, and the difficulty to represent digital services. In addition, there has not been enough published works on LCA of digital services, only on energy efficiency (Yoro et al, 2018a(Yoro et al, , 2018b(Yoro et al, , 2017 and network optimization (Masoudi et al, 2019;Rocha et al, 2017). Thus, a primary challenge to concurrently design for cost and environment is to adopt relevant representation tools and techniques for digital services.…”

Section: Introductionmentioning

confidence: 99%

Design-for-Cost-and-Environment: Ontological Analysis and Comparison of Service Representation Approaches

Villanueva

Yannou

Leroy

et al. 2020

Proc. Des. Soc.: Des. Conf.

View full text Add to dashboard Cite

Brought by the need for competent approaches to assess the financial cost and environmental impact towards service design-for-cost-and-environment, this paper investigates on the following service representation approaches: Service Blueprinting, Process Chain Network, Business Process Model & Notation, and Customer Journey Mapping. An ontological analysis further compares their similarities and differences. Lastly, a table summarizes the findings, were further insights could be drawn to help service companies be more aware of both their spending and ecological responsibility.

show abstract

SooGREEN: Service-oriented optimization of green mobile networks

Cited by 5 publications

References 8 publications

Orchestration and Control in Software‐Defined 5G Networks: Research Challenges

Orchestration and Control in Software‐Defined 5G Networks: Research Challenges

AppShot: A Conditional Deep Generative Model for Synthesizing Service-Level Mobile Traffic Snapshots at City Scale

Design-for-Cost-and-Environment: Ontological Analysis and Comparison of Service Representation Approaches

Contact Info

Product

Resources

About