Trends and challenges for autonomic RRM and MAC functionality for QoS provision and capacity expansions in the context of 5G beyond 6GHz

Belikaidis, Ioannis-Prodromos; Γεωργακόπουλος, Ανδρέας; Demestichas, Panagiotis; Herzog, Uwe; Moessner, Klaus; Vahid, Seiamak; Fitch, Michael; Briggs, Keith; Miscopein, Benoît; Okyere, Bismark; Frascolla, Valerio

doi:10.1109/eucnc.2017.7980748

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…One of the first projects is SPEED-5G [109], which is among the projects under the 5G PPP-Phase 1 [108] that focused on the autonomous RRM and self-optimization of spectrum utilization in heterogeneous small cells based networks. The H2020 SELFNET [110] and COGNET [111], as well as FP7 SEMAFOUR [112], are projects that were devoted to self-organized network management.…”

Section: B Research Activitiesmentioning

confidence: 99%

On Energy Efficient Resource Allocation in Shared RANs: Survey and Qualitative Analysis

Marzouk

Barraca

Radwan

2020

IEEE Commun. Surv. Tutorials

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An expansion of services and unprecedented traffic growth is anticipated in future networks, aligned with the adoption of the long-awaited Fifth Generation (5G) of mobile communications. To support this demand, without exposing mobile operators to the pressure of CAPEX and OPEX, 5G uses new frequency bands, and adopts promising trends, including: densification, softwarization, and autonomous management. While the first technology is proposed to handle the traffic growth requirements, the softwarization and autonomous management are expected to play, in synergy, to ensure the desired trade-off between reducing the CAPEX and OPEX, while guaranteeing the quality of service (QoS). Softwarization is expected to transform the network design, from one size fits all, to more demand oriented adaptive resource allocation. In this work, we focus on this point, by discussing how these technologies act in synergy towards enabling RAN sharing. Particularly, we focus on how they fit into the issue of energy efficient Multi-Operator Resource Allocation (MO-RA). After a survey and classification of schemes leveraging this synergy for distinct resource allocation (RA) objectives, we present a detailed survey and qualitative classification of RA schemes with respect to energy efficiency. This work presents an innovative survey, since it concentrates on multiple operators, and the enabling of Mobile Virtual Network Operators (MVNOs), which will come into play with the complete virtualization of mobile networks. Based on the deep literature analysis of the different operations that can bring energy savings to MO-RA, we conclude the work with listing open challenges and future research directions.

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Section: B Research Activitiesmentioning

confidence: 99%

On Energy Efficient Resource Allocation in Shared RANs: Survey and Qualitative Analysis

Marzouk

Barraca

Radwan

2020

IEEE Commun. Surv. Tutorials

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“…The edge computing paradigm has been widely accepted as an important concept for sustainability of future Cloud Service Providers (CSPs) and Mobile Network Operators (MNOs) [1], [2]. It is well acknowledged by both enterprise and academia as a valid approach and is actively under research [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Achlys: Towards a Framework for Distributed Storage and Generic Computing Applications for Wireless IoT Edge Networks with Lasp on GRiSP

Igor

Roy

2019

2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)

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Internet of Things (IoT) continues to grow exponentially, in number of devices and the amount of data they generate. Processing this data requires an exponential increase in computing power. For example, aggregation can be done directly at the edge. However, aggregation is very limited; ideally we would like to do more general computations at the edge. In this paper we propose a framework for doing generalpurpose edge computing directly on sensor networks themselves, without requiring external connections to gateways or cloud. This is challenging because sensor networks have unreliable communication, unreliable nodes, and limited (if any) computing power and storage. How can we implement production-quality components directly on these networks? We need to bridge the gap between the unreliable, limited infrastructure and the stringent requirements of the components. To solve this problem we present Achlys, an edge computing framework that provides reliable storage, computation, and communication capabilities directly on wireless networks of IoT sensor nodes. Using Achlys, the sensor network is able to configure and manage itself directly, without external connectivity. Achlys combines the Lasp key/value store and the Partisan communication library. Lasp provides efficient decentralized storage based on the properties of CRDTs (Conflict-Free Replicated Data Types). Partisan provides efficient connectivity and broadcast based on hybrid gossip. Both Lasp and Partisan are specifically designed to be extremely resilient. They are able to continue working despite high node churn, frequent network partitions, and unreliable communication. Our first implementation of Achlys is on a network of GRiSP embedded system boards. We choose GRiSP as our first implementation platform because it implements highlevel functionality, namely Erlang, directly on the bare hardware and because it directly supports Pmod sensors and wireless connectivity. We give some first results on using Achlys for building edge systems and we explain how we plan to evolve Achlys in the future. Achlys is a work in progress that is being done in the context of the LightKone European H2020 research project, and we are in the process of implementing and evaluating a proof-of-concept application in the area of precision agriculture. A. The Achlys frameworkThis paper presents Achlys, a framework that directly addresses the problem of general-purpose edge computing.

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Estimating data traffic through software-defined multiple access for IoT applications over 5G networks

Alshaflut

Thayananthan

2018

2018 15th Learning and Technology Conference (L&T)

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Trends and challenges for autonomic RRM and MAC functionality for QoS provision and capacity expansions in the context of 5G beyond 6GHz

Cited by 3 publications

References 16 publications

On Energy Efficient Resource Allocation in Shared RANs: Survey and Qualitative Analysis

On Energy Efficient Resource Allocation in Shared RANs: Survey and Qualitative Analysis

Achlys: Towards a Framework for Distributed Storage and Generic Computing Applications for Wireless IoT Edge Networks with Lasp on GRiSP

Estimating data traffic through software-defined multiple access for IoT applications over 5G networks

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