Deduplicator: When Computation Reuse Meets Load Balancing at the Network Edge
arxiv(2024)
摘要
Load balancing has been a fundamental building block of cloud and, more
recently, edge computing environments. At the same time, in edge computing
environments, prior research has highlighted that applications operate on
similar (correlated) data. Based on this observation, prior research has
advocated for the direction of "computation reuse", where the results of
previously executed computational tasks are stored at the edge and are reused
(if possible) to satisfy incoming tasks with similar input data, instead of
executing incoming tasks from scratch. Both load balancing and computation
reuse are critical to the deployment of scalable edge computing environments,
yet they are contradictory in nature. In this paper, we propose the
Deduplicator, a middlebox that aims to facilitate both load balancing and
computation reuse at the edge. The Deduplicator features mechanisms to identify
and deduplicate similar tasks offloaded by user devices, collect information
about the usage of edge servers' resources, manage the addition of new edge
servers and the failures of existing edge servers, and ultimately balance the
load imposed on edge servers. Our evaluation results demonstrate that the
Deduplicator achieves up to 20
compared to several other load balancing approaches, while also effectively
balancing the distribution of tasks among edge servers at line rate.
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