A Fog-based Architecture for Latency-sensitive Monitoring Applications in Industrial Internet of Things

In industrial wireless sensors networks (IWSNs) deployments, data management and processing tasks are often delegated to centralized computing facilities. Albeit providing an abundance of resources, these solutions impose several drawbacks, stemming from the higher latency they may introduce, as well as from security/privacy issues. To deal with these shortcomings, in this article, we propose an architecture designed for industrial monitoring duties, based on the Fog computing paradigm. In particular, we devised a Fog layer to host a data aggregation algorithm based on singular value decomposition (SVD). Considering a real-world case study about a distributed monitoring system for industrial motors, the benefits of the proposed solution in terms of network performances, i.e., latency and packet delivery ratio, are analyzed using the OMNET++ simulator. Besides, the system implements a set of security mechanisms at different levels (i.e., IWSN, Fog, and Cloud). In particular, we propose a new lightweight and energy-efficient ciphering algorithm for resource-constrained industrial motes. According to our experiments, the new algorithm reduces energy consumption by a factor of three compared to Advanced Encryption Standard-128.