IoT Serverless Computing at the Edge: A Systematic Mapping Review
Journal
Computers
Date Issued
2021-10
Author(s)
DOI
10.3390/computers10100130
Abstract
Serverless computing is a new concept allowing developers to focus on the core functionality of their code, while abstracting away the underlying infrastructure. Even though there are existing
commercial serverless cloud providers and open-source solutions, dealing with the explosive growth
of new Internet of Things (IoT) devices requires more efficient bandwidth utilization, reduced latency,
and data preprocessing closer to the source, thus reducing the overall data volume and meeting
privacy regulations. Moving serverless computing to the edge of the network is a topic that is actively
being researched with the aim of solving these issues. This study presents a systematic mapping
review of current progress made to this effect, analyzing work published between 1 January 2015 and
1 September 2021. Using a document selection methodology which emphasizes the quality of the
papers obtained through querying several popular databases with relevant search terms, we have
included 64 entries, which we then further categorized into eight main categories. Results show that
there is an increasing interest in this area with rapid progress being made to solve the remaining
open issues, which have also been summarized in this paper. Special attention is paid to open-source
efforts, as well as open-access contributions.
commercial serverless cloud providers and open-source solutions, dealing with the explosive growth
of new Internet of Things (IoT) devices requires more efficient bandwidth utilization, reduced latency,
and data preprocessing closer to the source, thus reducing the overall data volume and meeting
privacy regulations. Moving serverless computing to the edge of the network is a topic that is actively
being researched with the aim of solving these issues. This study presents a systematic mapping
review of current progress made to this effect, analyzing work published between 1 January 2015 and
1 September 2021. Using a document selection methodology which emphasizes the quality of the
papers obtained through querying several popular databases with relevant search terms, we have
included 64 entries, which we then further categorized into eight main categories. Results show that
there is an increasing interest in this area with rapid progress being made to solve the remaining
open issues, which have also been summarized in this paper. Special attention is paid to open-source
efforts, as well as open-access contributions.
Subjects
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