Abstract:
The inefficient sharing of industrial cloud resour- ces among multiple users and vulnerabilities of virtual machines (VM)s and servers prompt unauthorized access to users...Show MoreMetadata
Abstract:
The inefficient sharing of industrial cloud resour- ces among multiple users and vulnerabilities of virtual machines (VM)s and servers prompt unauthorized access to users’ sensitive data along with excess consumption of power and resource wastage. To address these entangled issues, this paper proposes a novel Emerging VM Threat Prediction and Dynamic Workload Estimation based Resource Allocation (ETP-WE) framework that predicts VM threats and resource usage proactively in real-time. The proposed framework contributes by introducing a Risk-Score Matrix that analyses multiple risks for each VM; utilizing knowledge of proposed security and workload analyzers for efficient VM Placement (VMP), and estimating resource utilization by developing an ensemble predictor for prior mitigation of over-/under-load on servers. ETP-WE framework collaborates machine-learning-based security and workload analysis for secure and resource-efficient VMP, thereby reducing the number of security threats, optimizing resource utilization, power-consumption, and adapting to the changes in application demands. The performance of the proposed framework is evaluated using two benchmark datasets OpenNebula and Google Cluster. The simulation-based comparison with state-of-the-arts validates the efficacy of ETP-WE in terms of reduction of security threats, power consumption, and number of active servers up to 86.9%, 66.67% and 30%-80%, respectively with an improved resource utilization up to 60%-75% over existing approaches Note to Practitioners—Industry clouds serve the precise needs and provide the service features and tools as per the industry’s needs to help organizations meet their workloads processing and storage demands. For instance, healthcare and financial organizations have to comply with extended security to meet specific service requirements. To this context, we have proposed a novel ETP-WE framework for prediction and mitigation of cyberthreats on virtual resources in real-time for sec...
Published in: IEEE Transactions on Automation Science and Engineering ( Volume: 21, Issue: 4, October 2024)