RNN‐EdgeQL: An auto‐scaling and placement approach for SFC
This paper proposes a prediction‐based scaling and placement of service function chains (SFCs) to improve service level agreement (SLA) and reduce operation cost. We used a variant of recurrent neural network (RNN) called gated recurrent unit (GRU) ...
Proposed proactive scaling and placement of SFC using ML can achieve a group‐level application‐agnostic elasticity of SFC with reduced CAPEX and OPEX. It considers the edge computing environment and is validated with two realistic traffic loads on the ...
SRv6‐based Time‐Sensitive Networks (TSN) with low‐overhead rerouting
Time‐Sensitive Networks (TSN) aims at providing a solid underpinning for the support of application connectivity demands across a wide spectrum of use cases and operational environments, such as industrial automation and automotive networks. ...
We propose a Software‐Defined Network (SDN)‐based approach for low‐overhead TSN network updates, exploiting Segment Routing over IPv6 (SRv6) for path control. Analysis of both control plane and data plane aspects is provided, and implementation experience ...
Analysis of network function sharing in Content Delivery Network‐as‐a‐service slicing scenarios
Video content consumption is currently dominating the mix of traffic observed in Internet service provider (ISP) networks. The distribution of that content is usually performed by means of content delivery network (CDN) caches storing and ...
This paper investigates through simulations the potential efficiencies that can be achieved when sharing a virtual cache function if compared with the classical approach of independent virtual caches operated per ISP, as well as the implications on ...
