Problem
Research questions and friction points this paper is trying to address.
FaaS
edge-cloud continuum
data replication
client latency
heterogeneous consistency
Replication-Aware Placement of Functions and Data in the Edge-Cloud Continuum
🤖 AI Summary
研究了如何在边缘云连续体中联合调度函数和放置数据以最小化客户端延迟，提出了一种二进制线性规划模型和一种拓扑感知的贪婪启发式方法。
📝 Abstract
Function-as-a-Service (FaaS) has emerged as the prominent programming model for the edge-cloud continuum. FaaS inherently decouples stateless functions from their persistent state. We study how to jointly schedule functions and place data to minimize client latency, considering data replication under heterogeneous consistency requirements. We introduce a Binary Linear Programming (BLP) model to compute optimal placements, establishing a rigorous theoretical baseline. Since the BLP scales cubically with the infrastructure nodes, we propose a topology-aware greedy heuristic that efficiently approximates the optimal solution. Our evaluation shows that the heuristic achieves near-optimal placement quality at a fraction of the computational cost, making it suitable for periodic system reconfigurations.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Binary Linear Programming
topology-aware heuristic
data replication
heterogeneous consistency requirements
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