Paper Info
Title
Data-Driven Edge Resource Provisioning for Inter-Dependent Microservices with Dynamic Load
Abstract
This paper studies how to provision edge computing and network resources for complex microservice-based applications (MSAs) in face of uncertain and dynamic geo-distributed demands. The complex inter-dependencies between distributed microservice components make load balancing for MSAs extremely challenging, and the dynamic geo-distributed demands exacerbate load imbalance and consequently congestion and performance loss. In this paper, we develop an edge resource provisioning model that accurately captures the inter-dependencies between microservices and their impact on load balancing across both computation and communication resources. We also propose a robust formulation that employs explicit risk estimation and optimization to hedge against potential worstcase load fluctuations, with controlled robustness-resource tradeoff. Utilizing a data-driven approach, we provide a solution that provides risk estimation with measurement data of past load geo-distributions. Simulations with real-world datasets have validated that our solution provides the important robustness crucially needed in MSAs, and performs superiorly compared to baselines that neglect either network or inter-dependency constraints.
Year
DOI
Venue
2021
10.1109/GLOBECOM46510.2021.9685155
2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)
Keywords
DocType
ISSN
Edge computing, microservice, load balancing, resource provisioning, robustness, data-driven
Conference
2334-0983
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Ruozhou Yu100.34
Szu-Yu Lo200.34
Fangtong Zhou300.34
Guoliang Xue4489.12