Abstract
The need for real-time analysis of smart data gave birth to the idea of fog computing. On one hand, the introduction of the fog layer to the cloud-IoT ecosystem provides faster response, mobility, and location awareness; On the other hand, it increases the attack surface area for the adversaries. The user data becomes highly probable to fall prey to the attackers as now it is processed near the end devices. Under these circumstances, the development of a trustworthy network is very important. Trust management in fog computing network involves different factors; ‘dependability’ being one of them. In this paper, the authors have presented a transitive interpretation to manage dependability in the said scenario. As per the proposed interpretation, load balancing may be deployed for a dependable fog system. Therefore, in the given research work, the authors have presented HBI-LB, a dependable fault-tolerant load balancing technique using a nature-inspired approach. The proposed approach is simulated using CloudSim 3.0.3-based Cloud Analyst tool. The obtained results are compared to the traditional and state-of-the-art approaches. The comparison is done based on average response time versus the number of tasks and executable instruction length per task.
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Verma, R., Chandra, S. HBI-LB: A Dependable Fault-Tolerant Load Balancing Approach for Fog based Internet-of-Things Environment. J Supercomput 79, 3731–3749 (2023). https://doi.org/10.1007/s11227-022-04797-6
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DOI: https://doi.org/10.1007/s11227-022-04797-6