Preemptive Resource Provisioning for Container-Based Audio/Video Encrypted Collaboration Applications
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Preemptive Resource Provisioning for Container‑Based Audio/Video Encrypted Collaboration Applications Rafael Xavier1 · Lisandro Zambenedetti Granville2 · Filip De Turck1 · Bruno Volckaert1 Received: 14 August 2019 / Revised: 19 May 2020 / Accepted: 26 May 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The massive industrial adoption of cloud technology has led to research into cloudenabling traditional applications. The EMD research project proposes an elastic, reliable, and secure cloud-enabled Audio and Video (A/V) collaboration platform in replacement of a reliable hardware appliance based which had fixed constraints in terms of scalability. In this context, this article introduces heuristics and architectures that efficiently and preemptively allocate EMD’s A/V encrypted and containerbased software components in the cloud. A software solution based on Kubernetes, a production-grade container orchestration platform, is compared with another solution focused on dedicated VMs. Both implement resource allocation heuristics that take into account the project’s requirements and location-aware encryption enforcement necessities: encryption is enforced for more sensitive data. A company training scenario with dynamically distributed instructors is modelled using existing A/V stream concepts, and component prototypes are extended to support encryption and containerisation, whose prototype performance evaluation drives the investigation of heuristics and architectures and feeds their larger-scale simulation-based assessment. Results show that container orchestration costs are at least 52% lower than dedicated VMs for this scenario, but rely on relaxing a project requirement: the time taken to establish a new streaming session was to be kept below 2 s. The switch to orchestrated containers raised this up to a maximum of 2.5 s. Keywords Cloud · Audio/Video · Streaming · Container orchestration
* Rafael Xavier [email protected] Extended author information available on the last page of the article
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Journal of Network and Systems Management
Fig. 1 Example of collaboration scenario studied in this article: one instructor sends his A/V streaming data to multiple attendees, which may return their camera’s images to the instructor. Users are positioned inside or outside pre-defined safe zones, and platform components process the data in order to encrypt it or adapt it to user endpoint’s capabilities
1 Introduction Cloud hosting models offer advantages such as flexibility and global distribution, with the ability to rapidly scale to massive amounts of users. The maturity of this model brings research efforts focused on the conversion of traditional solutions to this new paradigm. One example of collaboration handled by the platform is depicted in Fig. 1. Multiple bi-directional streaming flows carry course presentation A/V data in a one-to-many fashion, from an instructor endpoint to a select group of attendees’ endpoints (flows are represented by black arr
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