CASE: A Context-Aware Storage Placement and Retrieval Ecosystem

IEEE Access

Ganesh Chandrasekaran¹  Pankaj Bhimrao Thorat¹  Rajesh Challa¹  Pranay Dhondi¹  Boopathi Ramasamy² 

[1] Samsung Electronics Research and Development Institute India, Bangalore (SRIB), Bengaluru, India;Samsung Electronics, Suwon, South Korea;

关键词: 5G networks;    cloud native;    microservices;    containers;    context-aware services;    communication networks and telecommunication network topology;   

DOI  :  10.1109/ACCESS.2021.3139339

来源: DOAJ

【 摘 要 】

Emerging cloud-native technologies, such as container-runtime and container-orchestrator offer unprecedented agility in developing and running applications, especially when combined with microservice-style architecture. Several existing 5G-Telecom network products such as element Management System (e-MS), 5G-Core and 5G-Access are being redesigned to fit the microservice paradigm. Cloud environment allows enterprises to scale their application on-demand with minimum cost; however, it is often difficult to use containers without sacrificing many benefits that cloud-native technology offers. The e-MS is characterized to orchestrate 5G network elements (5GNEs) deployed nationwide, and systematically store terabytes of stateful data per second. Containers are characterized to have an ephemeral state, hence ‘stateful-ness’ aspect of e-MS makes orchestration complex. In this paper, different challenges around stateful storage selection, content placement and content retrieval operations within e-MS microservices are described. To overcome these challenges, to this end, we propose CASE - A Context-Aware Storage placement and retrieval Ecosystem - which enables context-based operations to be intrinsically supported by the underlying e-MS application. Our approach has been designed to maintain the location-independent philosophy of cloud-native by associating context information directly to 5GNE rather than fixed storage entities, thereby ensuring scalability. Through simulation with real data-set obtained from one of the world’s largest terrestrial telecom operator, we show that based on such location-independent context information, CASE with e-MS can facilitate high performance despite dynamic 5GNE count agility, stateless e-MS replication and stateful storage scaling, while not posing a significant signaling burden on the cloud environment.

【 授权许可】

Unknown