Resource Management in Edge Clouds: Latency-Aware Approaches for Big Data Analysis

The growing demand for time-sensitive services has led to the necessity for effective resource management strategies in edge clouds. These strategies are tailored to handle complex big data needs. This study examines latency-aware resource management strategies crucial for upcoming 5G and future services, emphasizing their key role in streamlining data processing and management. This chapter book presents different techniques that effectively manage resources and reduce latency including application placement, load balancing, offloading and caching, Virtual machine placement and migration, software-defined network, and AI-powered approaches. A conclusion has been presented regarding challenges in resource management posed by the massive connectivity and heterogeneous traffic demands. Finally, future direction has been proposed in terms of cross-layer optimization, context-aware resource management, security and privacy, and energy efficiency via the lens of cutting-edge AI and machine learning methods.