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1
Intro
2
What is Edge Stream Processing?
3
Why Edge Stream Processing?
4
Outline
5
Our Goal and Challenges
6
Challenge #1: How to scale to #applications?
7
Challenge #2: How to adapt to edge dynamics?
8
DART Design and implementation
9
Dynamic Dataflow Abstraction
10
Elastic Scaling Mechanism
11
Failure Recovery Mechanism
12
Performance Evaluation
13
Conclusion
Description:
Explore DART, a scalable and adaptive edge stream processing engine, in this conference talk from USENIX ATC '21. Learn about the challenges faced by traditional data processing systems in handling time-critical and dynamically changing IoT applications. Discover how DART introduces a dynamic dataflow abstraction using distributed hash table (DHT) based peer-to-peer (P2P) overlay networks to automatically place, chain, and scale stream operators. Understand the engine's ability to reduce query latency, adapt to edge dynamics, and recover from failures. Examine DART's performance compared to Storm and EdgeWise, and its significant improvements in scalability, adaptability, and application deployment setup times for IoT applications on edge platforms.

DART - A Scalable and Adaptive Edge Stream Processing Engine

USENIX
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