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Tactic: Apply edge computing
Tactic sort:
Awesome Tactic
Type: Architectural Tactic
Category: resource-adaptation
Title
Apply edge computing
Description
Moving computing resources closer to users decreases the latency. Furthermore, the system can be designed in a way that only processed/aggregated data need to be transported which reduces the amount of data traffic. Transporting less data over the network is expected to reduce the energy consumption.
Participant
Cloud consumer
Related software artifact
Classification software
Context
Edge versus cloud-only
Software feature
Data processing
Tactic intent
Decreasing data traffic, to increase performance and energy-efficiency
Target quality attribute
Performance
Other related quality attributes
Energy-efficiency
Measured impact
According to estimations, the energy consumption of the data processing and ML classification is relatively similar in the edge and cloud-only scenarios. The energy consumption of the data transport, on the other hand, differs several orders of magnitude when comparing the on edge versus cloud-only scenarios. The reduction in data transport is also a main motivation for applying the edge architecture. Therefore, we argue that, in a scenario where large volumes of data need to be processed, applying an edge architecture has a positive effect on the energy consumption of the workload. In this specific case study a difference of 21.242 kWh was identified between the cloud-only and edge scenario, indicating a decrease of the energy consumption of 96% when using the edge scenario.
Source
Master Thesis “Architectural Tactics to Optimize Software for Energy Efficiency in the Public Cloud” by Sophie VosGraphical representation
