Impact of Priority-Based Caching on Cache Performance for Smart Building IoT Sensors in Named Data Networking

Abstract

Smart building Internet of Things (IoT) deployments generate diverse sensor data with varying operational criticality and temporal characteristics, creating significant challenges for efficient content delivery in Named Data Networking (NDN) environments. Security camera feeds require prioritized cache treatment for real-time monitoring, while environmental sensor readings can tolerate lower service levels. Traditional NDN caching strategies employ uniform policies that fail to differentiate between these heterogeneous traffic patterns, treating all content equally regardless of operational importance. This paper presents a Priority-Freshness Aware Caching Strategy integrating three-tier priority differentiation with sensor-specific freshness evaluation for smart building environments, assigning high priority to security cameras (5-second freshness), medium to air quality monitors (10-second), and low to temperature sensors (30-second freshness). A multiplicative scoring mechanism combines priority levels with freshness status to guide cache admission and eviction decisions, evaluated using ndnSIM 2.7 across varying cache sizes (CS50-CS300) and user loads (30-200 users). Results demonstrate that at baseline configuration (CS100, 100 users), high-priority sensors achieve 64.98% cache hit ratio compared to 44.65% for low-priority sensors (45.5% relative improvement), with performance gaps widening from 10.39 to 21.72 percentage points as user load increases from 30 to 200 users.