Serverless Edge Computing: A Taxonomy, Systematic Literature Review, Current Trends and Research Challenges
Iqra Batool, Sania Kanwal
TL;DR
This systematic literature review maps the landscape of serverless edge computing (SEC) and proposes a detailed taxonomy to organize the field around development, metrics, platforms, and applications. By following Kitchenham guidelines and analyzing 47 primary studies, the paper identifies current-state architectures, QoS considerations, and toolchains (e.g., OpenFaaS, TinyFaaS) while highlighting key challenges such as heterogeneity, latency, reliability, and energy efficiency at the edge. The taxonomy and trend analysis reveal rising interest since 2017, with emerging emphasis on edge AI and blockchain for security/privacy, guiding researchers toward standardized evaluation and architecture design. The practical impact lies in providing researchers and practitioners a structured framework to compare SEC approaches, identify gaps, and prioritize future work toward scalable, secure, and low-latency edge deployments.
Abstract
In recent years, the rapid expansion of Internet of Things (IoT) nodes and devices has seamlessly integrated technology into everyday life, amplifying the demand for optimized computing solutions. To meet the critical Quality of Service (QoS) requirements such as reduced latency, efficient bandwidth usage, swift reaction times, scalability, privacy, and security serverless edge computing has emerged as a transformative paradigm. This systematic literature review explores the current landscape of serverless edge computing, analyzing recent studies to uncover the present state of this technology. The review identifies the essential features of serverless edge computing, focusing on architectural designs, QoS metrics, implementation specifics, practical applications, and communication modalities central to this paradigm. Furthermore, we propose a comprehensive taxonomy that categorizes existing research efforts, providing a comparative analysis based on these classifications. The paper concludes with an in depth discussion of open research challenges and highlights promising future directions that hold potential for advancing serverless edge computing research.