مؤسسة الشرق الأوسط للنشر العلمي
عادةً ما يتم الرد في غضون خمس دقائق
The shift from centralized cloud computing to Mobile Edge Computing (MEC) has enabled low-latency and real-time processing for mobile and IoT environments. This survey traces the evolution from cloud to MEC, focusing on architectural patterns, core challenges, and the underexplored issue of scalability. Following a structured literature review across IEEE Xplore and Google Scholar (2015–2025), a set of highly cited and representative peer-reviewed Scopus-indexed journal articles were selected for in-depth analysis. The findings reveal that while latency and mobility are effectively mitigated through task offloading and reinforcement learning, system throughput degrades significantly beyond a congestion threshold, exposing a critical scalability gap—a phenomenon observed in Deng et al. (2021) where performance peaks at moderate user density then declines under high load. Emerging trends include blockchain for security, Digital Twins for predictive offloading, and AI-driven orchestration. However, most existing solutions are validated under controlled scenarios, leaving large-scale heterogeneous deployments unsupported. This survey concludes that scalability must be treated as a first-class requirement in next-generation MEC architectures and proposes future directions in distributed orchestration, lightweight AI, and edge–cloud elasticity.