5G and beyond support the deployment of vertical applications, which is particularly appealing in combination with network slicing and edge computing to create a logically isolated environment for executing customer services. Even if serverless computing has gained significant interest as a cloud-native technology its adoption at the edge is lagging, especially because of the need to support stateful tasks, which are commonplace in, e.g., cognitive services, but not fully amenable to being deployed on limited and decentralized computing infrastructures. In this work, we study the emerging paradigm of stateful Function as a Service (FaaS) with lightweight task abstractions in WebAssembly. Specifically, we assess the implications of deploying inter-dependent tasks with an internal state on edge computing resources using a stateless vs. stateful approach and then derive a mathematical model to estimate the energy consumption of a workload with given characteristics, considering the power used for both processing and communication. The model is used in extensive simulations to determine the impact of key factors and assess the energy trade-offs of stateless vs. stateful.
Energy-Efficient Deployment of Stateful FaaS Vertical Applications on Edge Data Networks
Cicconetti, Claudio
;Bruno, Raffaele;Passarella, Andrea
2024
Abstract
5G and beyond support the deployment of vertical applications, which is particularly appealing in combination with network slicing and edge computing to create a logically isolated environment for executing customer services. Even if serverless computing has gained significant interest as a cloud-native technology its adoption at the edge is lagging, especially because of the need to support stateful tasks, which are commonplace in, e.g., cognitive services, but not fully amenable to being deployed on limited and decentralized computing infrastructures. In this work, we study the emerging paradigm of stateful Function as a Service (FaaS) with lightweight task abstractions in WebAssembly. Specifically, we assess the implications of deploying inter-dependent tasks with an internal state on edge computing resources using a stateless vs. stateful approach and then derive a mathematical model to estimate the energy consumption of a workload with given characteristics, considering the power used for both processing and communication. The model is used in extensive simulations to determine the impact of key factors and assess the energy trade-offs of stateless vs. stateful.| File | Dimensione | Formato | |
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