Freyr ^++: Harvesting Idle Resources in Serverless Computing via Deep Reinforcement Learning

Serverless computing has revolutionized online service development and deployment with ease-to-use operations, auto-scaling, fine-grained resource allocation, and pay-as-you-go pricing. However, a gap remains in configuring serverless functions-the actual resource consumption may vary due to functio...

Full description

Bibliographic Details

Published in:	IEEE transactions on parallel and distributed systems Vol. 35; no. 11; pp. 2254 - 2269
Main Authors:	Yu, Hanfei, Wang, Hao, Li, Jian, Yuan, Xu, Park, Seung-Jong
Format:	Journal Article
Language:	English
Published:	IEEE 01.11.2024
Subjects:	Attention Deep reinforcement learning Dynamic scheduling Heuristic algorithms incremental learning Memory management Nearest neighbor methods reinforcement learning resource harvesting Serverless computing Training
ISSN:	1045-9219, 1558-2183
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!