Resiliency-based edge computing is a growing research domain that focuses on ensuring reliability, fault tolerance, and service continuity in highly dynamic and distributed edge environments. Research papers in this field study strategies to mitigate failures caused by hardware faults, cyber-attacks, overload conditions, and network disruptions, which are especially critical in latency-sensitive applications like smart healthcare, autonomous vehicles, industrial IoT, and mission-critical services. Studies emphasize resilient architectures that integrate redundancy, fault detection, load redistribution, and self-healing mechanisms to maintain service availability. Recent works explore AI-driven and machine learning-based predictive models for proactive fault management, as well as blockchain-enabled frameworks for secure and tamper-resistant service recovery. Resiliency research also investigates hybrid edge–cloud–fog collaboration to enhance adaptability under varying workloads and mobility scenarios. Furthermore, energy-aware and cost-efficient resiliency mechanisms are being designed to minimize overhead while maintaining high Quality of Service (QoS) and Quality of Experience (QoE). Overall, resiliency-based edge computing research highlights the importance of building robust, adaptive, and self-sustaining systems that can withstand disruptions and ensure continuous, reliable service delivery in next-generation networks.