Caching as a Service in 5G Networks: Intelligent Transport and Video on Demand Scenarios

With the explosive growth of mobile multimedia traffic, the problem of allocating computing and spectral resources for very low latency services become a challenge for next generation mobile networks. We exploit all the benefits of a completely virtualized environment, where mobile virtual network o...

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Bibliographic Details
Main Authors: Assila, Bouchaib, Kobbane, Abdellatif, El Koutbi, Mohammed, Ben-Othman, Jalel, Mokdad, Lynda
Format: Conference Proceeding
Language:English
Subjects:
5G mobile communication
Cloud computing
Computer architecture
Delays
Games
Internet of Things
Quality of service
Online Access:Request full text
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Summary:With the explosive growth of mobile multimedia traffic, the problem of allocating computing and spectral resources for very low latency services become a challenge for next generation mobile networks. We exploit all the benefits of a completely virtualized environment, where mobile virtual network operators (MVNOs) and virtual service providers (VSPs) are connected in the Cloud through network as a service (NaaS) using distributed infrastructure as a service (IaaS). VSPs provide services according to Internet of things (IoT) devices requests including software as a service (SaaS) and emerging caching techniques Cache as a Service (CaaS) to satisfy the quality of service (QoS) requirements. Thus, we propose a many-to-many matching game between the sets of IoT devices and the set of virtual service providers (VSPs). To solve this game, we exploit the deferred acceptance algorithm that enables the players to self-organize into a stable matching and a reasonable number of algorithm iterations. To highlight the effectiveness of our approach for the on-demand services, we applied it on two typical services requiring ultra- reliability and low-latency communications (uRLLC): The intelligent transport and the video on-demand services. Simulation results has demonstrated that our proposed matching strategy coupled to CaaS caching capabilities on distributed F-RAN significantly outperforms the traditional strategies in terms of latency and network traffic load.
ISSN:2576-6813
DOI:10.1109/GLOCOM.2018.8648110