Downloads provided by UsageCounts
Serverless is an emerging paradigm that greatly simplifies the usage of cloud resources providing unprecedented auto-scaling, simplicity, and cost-efficiency features. Thus, more and more individuals and organizations adopt it, to increase their productivity and focus exclusively on the functionality of their application. Additionally, the cloud is expanding towards the deep edge, forming a continuum in which the event-driven nature of the serverless paradigm seems to make a perfect match. The extreme heterogeneity introduced, in terms of diverse hardware resources and frameworks available, requires systematic approaches for evaluating serverless deployments. In this paper, we propose a methodology for evaluating serverless frameworks deployed on hybrid edge-cloud clusters. Our methodology focuses on key performance knobs of the serverless paradigm and applies a systematic way for evaluating these aspects in hybrid edge-cloud environments. We apply our methodology on three open-source serverless frameworks, OpenFaaS, Openwhisk, and Lean Openwhisk respectively, and we provide key insights regarding their performance implications over resource-constrained edge devices.
Edge-Computing, Openwhisk, OpenFaaS, Serverless-Computing, Function-as-a-Service, Kubernetes, Cloud
Edge-Computing, Openwhisk, OpenFaaS, Serverless-Computing, Function-as-a-Service, Kubernetes, Cloud
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 15 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 22 | |
| downloads | 38 |

Views provided by UsageCounts
Downloads provided by UsageCounts