Sarcouncil Journal of Engineering and Computer Sciences

Abstract: Edge computing radically revolutionizes conventional computational models by positioning processing facilities nearer to sources of data generation, addressing fundamental latency requirements and bandwidth issues associated with centralized cloud infrastructures. The digital revolution in data has increased the need for real-time processing capacities, where edge computing comes forward with solutions in terms of multi-tenant platforms and software-defined networking platforms that facilitate real-time decision-making in various application domains. Distributed processing architectures form layered computing structures in which knowledge-based task distribution maximizes utilization of resources while preserving extremely low latency features of critical importance for latency-sensitive applications. Network integration blocks natively integrate computational resources into installed base infrastructure through application-specific gateways and smart routing systems that facilitate independent data processing decisions. Performance benefits include substantial network traffic reduction, increased system robustness, and increased operational effectiveness over centralization-based approaches. Critical use cases such as autonomous vehicle systems, industrial automation use cases, and networked device ecosystems showcase disruptive advantages through localized processing that obviates reliance on network availability. Implementation approaches necessitate a holistic evaluation of infrastructure needs, security measures, and resource management issues unique to distributed edge environments. Multi-get admission to part computing frameworks deliver ultra-low latency programs with answers for complex safety threats, the use of sturdy authentication strategies, and privacy protective mechanisms tailor-made for heterogeneous computing platforms.