A distributed multi-layer MEC-cloud architecture for processing large scale IoT-based multimedia applications

Abstract

The enormous growth of the Internet of Things (IoT) devices gave governments, businesses, and individual users new means to accomplish their missions. Several IoT applications require deployment at a large scale such as smart cities. Large-scale IoT applications help achieve better monitoring services and more efficient cities. IoT multimedia (IoTMM) applications provide a unique level of intelligence that cannot be obtained with traditional IoT applications. IoTMM applications intensely consume bandwidth, processing, and storage resources compared to traditional IoT applications. IoT nodes vary in their capabilities, where some nodes have high processing capabilities while others do not. Cloud services models (IaaS, PaaS, and SaaS) provide a perfect solution for applications of high demand for resources. However, such models are inefficient when dealing with multimedia applications due to the high bandwidth requirements before reaching the cloud. Mobile edge computing (MEC) model creates a new level of providers according to the proximity of the end users to the network resources. Edge providers can offload some processing that is usually done at the cloud, which improves the overall performance of cloud-based applications. In this paper, we propose a new distributed structure for processing multimedia applications in the cloud, where different layers of processing and providers are involved. Every layer is responsible for a specific role depending on the type of the multimedia application and multimedia device. The major contribution of the proposed architecture includes two main elements: the support of scalable IoTMM applications in large deployment scenarios and the support of effective multimedia information sharing. The proposed architecture supports a scalable architecture for IoTMM applications with minimum additional resources compared to the traditional models. The proposed model allows for effective and practical sharing of multimedia information (raw multimedia data or features extracted from multimedia data). In addition, the proposed architecture provides applications with the ability of accessing intelligent multimedia information and services with minimum software development efforts. We support our claims with detailed simulation results and analysis.