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Ultra-dense networks are widely regarded as a promising solution toexplosively growing applications of Internet-of-Things (IoT) mobile devices(IMDs). However, complicated and severe interferences need to be tackledproperly in such networks. To this end, both orthogonal multiple access (OMA)and non-orthogonal multiple access (NOMA) are utilized at first. Then, in orderto attain a goal of green and secure computation offloading, under theproportional allocation of computational resources and the constraints oflatency and security cost, joint device association, channel selection,security service assignment, power control and computation offloading are donefor minimizing the overall energy consumed by all IMDs. It is noteworthy thatmulti-step computation offloading is concentrated to balance the network loadsand utilize computing resources fully. Since the finally formulated problem isin a nonlinear mixed-integer form, it may be very difficult to find itsclosed-form solution. To solve it, an improved whale optimization algorithm(IWOA) is designed. As for this algorithm, the convergence, computationalcomplexity and parallel implementation are analyzed in detail. Simulationresults show that the designed algorithm may achieve lower energy consumptionthan other existing algorithms under the constraints of latency and securitycost.

Secure and Multi-Step Computation Offloading and Resource Allocation in Ultra-Dense Multi-Task NOMA-Enabled IoT Networks