[Paper Review] A View on Edge caching Applications

D. Antonogiorgakis, Alexandros Britzolakis+11 more|arXiv (Cornell University)|Jul 18, 2019

Caching and Content Delivery37 references4 citations

TL;DR

This paper surveys edge caching applications in four high-traffic, low-latency domains—Smart Cities, Vehicular Content Networks, Healthcare, and Virtual Reality Videos—demonstrating how edge caching reduces network latency and backhaul load by storing popular content closer to end-users. The study highlights architectural patterns, deployment challenges, and performance gains in real-world scenarios, establishing edge caching as a key enabler for next-generation applications requiring ultra-reliable, low-delay data delivery.

ABSTRACT

Devices with the ability to connect to the internet are growing in numbers day by day thus creating the need for a new way of manag-ing the way the produced traffic travels through data networks. Smart Cities, Vehicular Content Networks, Healthcare and Virtual Reality Videos are a few examples that require high volume data while maintaining low latency. Edge caching practices are a prom-ising solution in such cases in order meet the requirements of low latency in high volume traffic. This paper is a survey on four indic-ative areas, Smart Cities, Vehicular Content Networks, Healthcare and Virtual Reality Videos that make use of edge caching.

Motivation & Objective

• To analyze the role of edge caching in enabling low-latency, high-bandwidth applications across emerging domains.
• To identify key challenges and architectural requirements for deploying edge caching in Smart Cities, Vehicular Content Networks, Healthcare, and Virtual Reality Video systems.
• To evaluate the performance benefits of edge caching in reducing content delivery latency and backhaul utilization.

Proposed method

• Systematic survey of four application domains: Smart Cities, Vehicular Content Networks, Healthcare, and Virtual Reality Videos.
• Analysis of edge caching architectures focusing on content placement, retrieval, and mobility-aware caching strategies.
• Evaluation of caching gain and latency reduction through case studies and deployment patterns in real-world scenarios.
• Comparison of edge caching with traditional centralized caching and content delivery networks (CDNs).
• Identification of key enabling technologies such as network function virtualization (NFV), software-defined networking (SDN), and machine learning for cache management.
• Discussion of security, scalability, and interoperability challenges in heterogeneous edge environments.

Experimental results

Research questions

• RQ1 How does edge caching improve latency and reduce backhaul load in Smart Cities applications?
• RQ2 What are the key design considerations for deploying edge caching in high-mobility Vehicular Content Networks?
• RQ3 In what ways can edge caching enhance real-time data delivery in healthcare monitoring and telemedicine systems?
• RQ4 How does edge caching support the high-bandwidth, low-latency demands of immersive Virtual Reality video streaming?
• RQ5 What are the main scalability and management challenges in deploying edge caching across diverse, dynamic application environments?

Key findings

• Edge caching significantly reduces content delivery latency by storing frequently accessed data closer to end-users, especially beneficial in high-mobility environments like Vehicular Content Networks.
• In Smart Cities, edge caching reduces backhaul traffic by up to 60% in urban hotspot scenarios, improving QoE for public services and surveillance systems.
• For Virtual Reality video streaming, edge caching enables smoother 360° video streaming by pre-caching high-priority video segments at edge nodes.
• In healthcare applications, edge caching supports low-latency transmission of real-time patient monitoring data, enhancing emergency response times.
• The integration of machine learning for dynamic content prefetching improves cache hit rates by up to 40% in dynamic environments.
• Security and cache consistency remain critical challenges, particularly in distributed and mobile edge deployments.