Croesus: Multi-Stage Processing and Transactions for Video-Analytics in Edge-Cloud Systems
Samaa Gazzaz, Vishal Chakraborty, Faisal Nawab

TL;DR
Croesus introduces a multi-stage edge-cloud processing framework for video analytics that balances accuracy and performance by combining real-time approximate edge computation with cloud-based correction.
Contribution
The paper presents Croesus, a novel multi-stage approach enabling efficient, accurate video analytics in edge-cloud systems through staged processing and transaction safety mechanisms.
Findings
Multi-stage processing improves accuracy-performance trade-off.
Croesus effectively balances real-time edge computation with cloud correction.
Proposed safety protocols ensure transaction consistency in multi-stage systems.
Abstract
Emerging edge applications require both a fast response latency and complex processing. This is infeasible without expensive hardware that can process complex operations -- such as object detection -- within a short time. Many approach this problem by addressing the complexity of the models -- via model compression, pruning and quantization -- or compressing the input. In this paper, we propose a different perspective when addressing the performance challenges. Croesus is a multi-stage approach to edge-cloud systems that provides the ability to find the balance between accuracy and performance. Croesus consists of two stages (that can be generalized to multiple stages): an initial and a final stage. The initial stage performs the computation in real-time using approximate/best-effort computation at the edge. The final stage performs the full computation at the cloud, and uses the…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Privacy-Preserving Technologies in Data · IoT and Edge/Fog Computing
MethodsPruning
