Name
Abstract | ||
|---|---|---|
Communication networks need to be both adaptive and scalable. The last few years have seen an explosive growth of software-defined networking (SDN) and network function virtualization (NFV) to address this need. Both technologies help enable networking software to be decoupled from the hardware so that software functionality is no longer constrained by the underlying hardware and can evolve independently. Both SDN and NFV aim to advance a software-based approach to networking, where networking functionality is implemented in software modules and executed on a suitable cloud computing platform. Achieving this goal requires the virtualization paradigm used in these services that play an important role in the transition to software-based networks. Consequently, the corresponding computing platforms accompanying the virtualization technologies need to provide the required agility, robustness, and scalability for the services executed. Serverless computing has recently emerged as a new paradigm in virtualization and has already significantly changed the economics of offloading computations to the cloud. It is considered as a low-latency, resource-efficient, and rapidly deployable alternative to traditional virtualization approaches, such as those based on virtual machines and containers. Serverless computing provides scalability and cost reduction, without requiring any additional configuration overhead on the part of the developer. In this paper, we explore and survey how serverless computing technology can help building adaptive and scalable networks and show the potential pitfalls of doing so. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JPROC.2019.2898101 | Proceedings of the IEEE |
Keywords | DocType | Volume |
Containers,Cloud computing,Virtualization,Hardware,Servers,FAA,Network function virtualization | Journal | 107 |
Issue | ISSN | Citations |
4 | 0018-9219 | 4 |
PageRank | References | Authors |
0.50 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paarijaat Aditya | 1 | 4 | 0.84 |
| Istemi Ekin Akkus | 2 | 68 | 6.96 |
| Andre Beck | 3 | 71 | 7.44 |
| Ruichuan Chen | 4 | 205 | 18.95 |
| Volker Hilt | 5 | 480 | 41.90 |
| Ivica Rimac | 6 | 297 | 23.46 |
| Klaus Satzke | 7 | 4 | 0.84 |
| Manuel Stein | 8 | 114 | 13.16 |