Dependent Function Embedding for Distributed Serverless Edge Computing

Edge computing is booming as a promising paradigm to extend service provisioning from the centralized cloud to the network edge. Benefit from the development of serverless computing, an edge server can be configured as a carrier of limited serverless functions, in the way of deploying Docker runtime...

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Vydané v:IEEE transactions on parallel and distributed systems Ročník 33; číslo 10; s. 2346 - 2357
Hlavní autori: Deng, Shuiguang, Zhao, Hailiang, Xiang, Zhengzhe, Zhang, Cheng, Jiang, Rong, Li, Ying, Yin, Jianwei, Dustdar, Schahram, Zomaya, Albert Y.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Apexes
Cloud computing
Completion time
dependent function embedding
directed acyclic graph
Edge computing
Embedding
function placement
Graph theory
Internet of Things
Optimization
Power measurement
Provisioning
Routing
Segmentation
Servers
Surveillance
task scheduling
Virtual links
ISSN:1045-9219, 1558-2183
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Shrnutí:Edge computing is booming as a promising paradigm to extend service provisioning from the centralized cloud to the network edge. Benefit from the development of serverless computing, an edge server can be configured as a carrier of limited serverless functions, in the way of deploying Docker runtime and Kubernetes engine. Meanwhile, an application generally takes the form of directed acyclic graphs (DAGs), where vertices represent dependent functions and edges represent data traffic. The status quo of minimizing the completion time (a.k.a. makespan) of the application motivates the study on optimal function placement. However, current approaches lose sight of proactively splitting and mapping the traffic to the logical data paths between the heterogeneous edge servers, which could affect the makespan significantly. To remedy that, we propose an algorithm, termed as Dependent Function Embedding (DPE), to get the optimal edge server for each function to execute and the moment it starts executing. DPE finds the best segmentation of each data traffic by exquisitely solving several infinity norm minimization problems. DPE is theoretically verified to achieve the global optimality. Extensive experiments on Alibaba cluster trace show that DPE significantly outperforms two baseline algorithms in makespan by 43.19% and 40.71%, respectively.
Bibliografia:ObjectType-Article-1
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2021.3137380