Fuzzy Logic-Driven Energy-Aware Auditing Framework Using IOTA for Sustainable Supply Chains

Abstract

In modern supply chains, visibility and sustainability is becoming dependent on energy-efficient and auditable data management frameworks. The use of blockchainbased auditing methods can yield transparent visibility and mechanized auditing capabilities. However, typical auditing solutions using blockchain come with significant energy resource-consuming overheads that are not viable in Industrial IoT (IIoT). In contrast, traditional routing methods do not concurrently account for energy consumption at multiple layers of complexity. In this paper, a novel framework consisting of Fuzzy Logic-Based Energy Aware Routing (FLEA-RPL) combined with the lightweight Internet of Things Application (IOTA) Tangle is proposed, for green supply chain auditing. This is done by first collecting the sensor data (temperature, location, and, residual energy) from the IIoT nodes. The data is preprocessed to receive a similar distribution for incoming sensor data and to filter out inconsistent anomalies. Moreover, FLEA-RPL uses fuzzy inference to assess and choose optimal parent nodes to route the data to nodes on the routing tree, for minimizing energy consumption, according to residual energy and, load to send the data. The routed data is then permanently logged onto a Tangle so that the route is immutable and, therefore, low power and energy data is permanently attached to the distributed ledger. The final step is that the intelligent compliance auditing module monitors the contents of the distributed ledger for violations of a certain Service Level Agreement (SLA) from the ledger. The proposed FLEA-RPLIOTA attained better results, when compared FLEA-RPL in terms of Residual Energy (97.74 %), Packet Loss Ratio (2.2 %) respectively.