Communication Intensive Task Offloading With IDMZ for Secure Industrial Edge Computing

The Industrial Internet of Things provides an opportunity for flexible and collaborative manufacturing, but introduces more risk and more communication overhead from the Internet to the industrial field. To avoid attacks from unreliable service providers and requesters, Industrial Demilitarized Zone (IDMZ) is introduced in conjunction with firewalls to provide new communication modes between edge servers and industrial devices. As the number of tasks being offloaded to the edge side increases, optimal task offloading to balance the risk and the communication overhead with limited demilitarized buffer size becomes a challenge. Therefore, this paper establishes a mathematical model for secure task offloading in the Industrial Internet-of-Things considering dense communication with different communication modes. Then, a Parallel Gbest-centric differential evolution (P-G-DE) is designed to solve this task offloading problem with a heuristic-embedded initialization strategy, a modified Gbest-centric differential evolutionary operator and a circular-rotated parallelization scheme. The experimental results verify that the proposed method is capable of providing a high-quality solution with a lower risk and a shorter execution time in seconds, compared to six state-of-the-art evolutionary algorithms.