Exposing radio network information in a MEC-in-NFV environment: the RNISaaS concept

Abstract

The Radio Network Information Service (RNIS) is one of the key services provided by a Multi-access Edge Computing Platform (MEP), as specified in the relevant ETSI MEC standards. It is responsible for interacting with the Radio Access Network (RAN), collecting RAN-level information about User Equipment (UE) and exposing it to mobile edge applications, which can in turn utilize it to dynamically adjust their behavior to optimally match the RAN conditions. Putting the provision of RNIS in the context of the emerging MEC-in-NFV environment, where the components and services of the MEC architecture, including the MEP itself, are integrated in an NFV environment and are delivered on top of a virtualized infrastructure, we present our standards-compliant RNIS implementation based on OpenAirInterface and study critical performance aspects for its provision as a virtual function. Since the RNIS design and operation follows the publish-subscribe model, we provide alternative implementations using different message brokering technologies (RabbitMQ and Apache Kafka), and compare their use and performance in an effort to evaluate their suitability for providing RNIS in an as-a-service manner.

CDN Slicing over a Multi-Domain Edge Cloud

“…For mobile users and in regions where CDN components are deployed as ME applications, the RUM has access to information on the radio network conditions via the RNIS [44]. Our implementation includes a standardscompliant RNIS (see [55] for details on its internals), which allows ME applications to subscribe to radio information at different granularity (i.e., per user or per cell), and receive them as asynchronous notifications. The RUM can thus, at any time, be informed of the load of a cell in terms of connected users, but also of the Channel Quality Indication (CQI) of each user consuming the CDN service.…”

“…Our implementation includes a standardsthreshold (q Step 2: min ). compliant RNIS (see [55] for details on its internals), which allows ME applications to subscribe to radio information at Find the maximum number of streams a vCPU can handle with a QoE value greater than or equal to qmin. To derive this value, we use the inverse function of Eq.…”

An Edge-Based Social Distancing Detection Service to Mitigate COVID-19 Propagation

“…As input for the algorithm, we used a real existing dataset of mobile people. Second, we have implemented a prototype of the application and tested it using EURECOM's MEC platform [10], developed on top of OpenAirInterface (OAI) [11]. While the first method allows us to check the efficiency of the social distancing detection algorithm, introduced in Algorithm 1, the second method permits us to show how MEC can help to ensure near-real-time communication, and hence guarantee short latency to receive warnings when not respecting the distances.…”

On the integration of NFV and MEC technologies: architecture analysis and benefits for edge robotics

“…The work proposes some ideas how to overcome the orchestration gaps between the NFV and MEC environment without focusing on the main challenges, suggesting that the new module is adaptable to a MEC in NFV environment. The implementation of a MEC Radio Network Information Service (RNIS) aimed for a MEC-in-NFV environment is explored in [2]. That work presents how a standard-compliant RNIS can be realized on top of virtualized infrastructure and compares different message brokers that enable the RNIS MEC Service to provide information towards MEC Applications.…”