More Than The Sum of Its Things: Resource Sharing Across IoTs at The Edge

Abstract

The extreme growth and diversity of IoT applications, along with the heterogeneity of these devices, has led to numerous middleware solutions emerging to address various relevant challenges. These solutions have been shifting from cloud-based approaches to edge-technologies in order to handle issues related to privacy, latency, and bandwidth. Within this context, we identify an opportunity to introduce a novel IoT Middleware system that enables more seamless resource and context sharing at the edge. We propose the Hive, a middleware system that allows heterogeneous off-the-shelf devices in a common edge network to seamlessly and efficiently utilize each other's sensory and computational resources. The Hive architecture enables a new wave of multi-modal sensory applications, leveraging a pool of IoT devices, that would otherwise be unattainable. We accomplish this by decoupling the hardware, processing, and application layers within IoT devices from each other. The Hive abstracts each of these layers into a single resource pool that is shared and cross utilized on-demand within the edge network by any individual device. We implement the Hive, along with a dedicated communication protocol for our system. We evaluate the effectiveness of the Hive by integrating it with two sample IoT applications: an audio-based emotion recognition system, and a video-based facial detection application. We extensively evaluate the impact the Hive has on these new applications after integration, and additionally investigate its impact at scale. Our results show how the hive boosts the overall utilization of resources in an edge IoT network, reduces computational delay in complex applications, and most importantly, enables applications to perform at higher level of effectiveness.