Towards Energy-Efficient and Secure Data Transmission in AI-Enabled Software Defined Industrial Networks

Currently, increasing attention is devoted to artificial intelligence (AI) enabled software defined industrial networks (AI-SDINs). Toward energy-efficient and secure data transmission in AI-SDINs, a metric called energy-cost-per-useful-bit (ECPUB), which means energy cost of transmitting per useful bit is presented to evaluate energy efficiency and a novel energy-efficiency based secure multipath routing scheme is then put forward. Specifically, the ECPUB incorporates the utility and the law of diminishing marginal utility, for revealing the relationship among energy consumption, residual energy, and useful bits required. Moreover, in this article, an energy-efficiency based secure multipath routing scheme ((ESMR)-S-2) is proposed by adopting the ECPUB and (t, n) threshold secret sharing scheme, for enhancing the security under the premise of guaranteeing energy efficiency. Extensive simulation results show that ECPUB can evaluate the energy efficiency and facilitate the balance of network load, while (ESMR)-S-2 can prolong the lifetime of the network and simultaneously ensure the network functionality securely.