TTACO: Trusted Time-Aware Computing Offloading in Air-Ground Integrated Networks

As efficiency and security requirements emerge in computing offloading fields, trusted computing offloading has grabbed tremendous sights, especially in Air-Ground Integrated Networks (AGINs). Although traditional computing offloading studies have attempted to employ trust to identify malicious devices without mobility, the integration of trust management and computing offloading has not been explored in a high-hazardous environment. Then, with the increasing requirement of adaptation and security in new-generation network architectures (i.e., AGINs), trust management plays a pivotal role in expanding the implementation of trusted computing offloading. Therefore, we propose a trusted time-aware computing offloading mechanism in AGINs based on communication, computing offloading, and trust modeling. Specifically, a maximum reward optimization formulation is designed to generate an optimal offloading strategy, considering service utility trust, opinion service trust, computing efficiency trust, time constraints, rewards, and task volumes. Based on problem analysis, a solution paradigm is condensed to improve the probability of seeking an efficient solution. Moreover, a greedy search algorithm is designed to find the possible efficient solution, including the default solution setting stage, the boundary search stage, and the greedy reallocation stage. Due to the trust threshold affecting identification results, a dichotomy-based dynamic trust threshold method is employed to empower trusted computing offloading mechanism with the adaptive capability in AGINs. Extensive experiments show that our mechanism outperforms other baselines in terms of accuracy, precision, recall, F-measure, task success rate, and average response time.