Abstract
Community network edge-clouds have been attracting significant interests over the recent years with the emergence of ubiquitous networked devices embedded in our daily activities and increasingly widespread fully-distributed heterogeneous networks of smart edges offering various applications and services in real time. This paper proposes EdgeCNC, a novel joint multilayer adaptive opportunistic network-coding algorithm integrated with adaptive opportunistic content caching service. EdgeCNC exploits the multilayer spatial-temporal locality of users' mobility and interests in community network edge-clouds in order to select highly suitable set of contents to forward, cache and network code to highly suitable set of nodes in order to enhance QoS, reduce data transmissions and improve energy efficiency. We perform a multi-criteria evaluation of EdgeCNC performance in realistic Foursquare New York scenario of mobile community edgeclouds against the benchmark and competitive protocols in the face of dynamically changing users' publish-subscribe and mobility patterns. We show that EdgeCNC achieves higher success ratio and data transmission efficiency while keeping lower delays, packet loss and energy consumption compared to the competitive and benchmark protocols.