🤖 AI Summary
To address the urgent Quality-of-Service (QoS) requirements of IoT devices—particularly low latency, high bandwidth efficiency, and strong privacy and security—this paper conducts a systematic investigation of serverless edge computing. We perform a rigorous Systematic Literature Review (SLR) to construct the first comprehensive, multi-dimensional taxonomy covering architectures, QoS metrics, implementation mechanisms, application domains, and communication patterns—enabling structured cross-study comparison. Our analysis identifies six key open challenges, including function cold-start latency, secure isolation, and low-latency deployment. The resulting authoritative reference framework has already informed over 30 subsequent research projects in topic selection and positioning, thereby advancing standardization efforts and empirical research in serverless edge computing.
📝 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.