A Systematic Literature Review For Cloud Computing And Edge Computing Performance Comparison

This paper is a systematic literature review comparing the performance of cloud computing and edge computing. Metrics used to compare performance are latency, throughput, energy efficiency, cost, response time, and packet loss. With the exponential growth of internet of things (IOT) Devices and the demand for low-latency applications increasing, Edge computing emerged as a supplementary improvement to cloud computing. While cloud computing offers greater scalability and easier centralized management, edge computing allows computation to happen closer to the data sources, reducing latency and improving real-time processing capabilities. This study reviews existing research to evaluate the strengths, limitations, and trade-offs of utilizing each computational paradigm. Findings reveal that edge computing consistently outperforms traditional cloud computing in latency-sensitive and real-time applications, achieving lower RTT and energy consumption. However, cloud computing remains superior in scalability and cost-effectiveness for non-latency sensitive tasks. The paper also highlights the phenomenon of performance inversion in edge computing while under high utilization. This study aims to guide researchers and practitioners in selecting the appropriate computing infrastructure for specific applications. Future research directions include exploring hybrid cloud-edge architectures and conducting real-world implementation studies.