As one of the enabling technologies for cyber-physical systems and Internet of Things systems, cloud computing provides cost-effective resources in an on-demand manner. This merit lends the cloud to running critical services that need redundancy to achieve high reliability.
The parallel model is a cloud service using the N-version programming (NVP) redundancy technique that creates and runs multiple task solver versions (TSVs) in parallel to perform a requested service and decides the output using the threshold voting. A malicious attacker may get unauthorized access to a user’s data when the user’s and attacker’s virtual machines co-reside in the same cloud server. To reduce the chance of the co-residence attack success and users’ expense, an individual TSV cancellation policy is implemented, which removes a TSV’s virtual machine from its host server immediately once this TSV completes the task execution. A probabilistic method is proposed in a research lab to evaluate the task reliability and data security under the considered cloud service model. Constrained optimization problems are further formulated and solved, which find the optimal number of TSVs maximizing the task reliability subject to providing the desired level of data security. Examples are presented to demonstrate interactions and impacts of different parameters on the task reliability and data security, as well as on the optimization solutions.
A k-out-of-n system with weighted components is a system that consists of components that contribute differently to the overall performance of the system, and functions if the total weight/contribution of all working components exceeds or is equal to the level k. Such a system is useful and suitable for modeling capacity-based systems such as power systems, transportation systems, and manufacturing systems. This is concerned with the lost capacity by the weighted-k-out-of-n system at the time when the system fails. This random quantity is useful for making an optimal decision about the spare capacity that should be available to renew the system upon its failure. In particular, the distribution of this random quantity is derived and the theoretical results are illustrated for a power system consisting of a specified number of generating units.
Making public concerns tangible
Digitization processes in the public sector have led to an increase in innovative approaches for better service delivery using information and communication technology. Citizens, however, often have reservations towards e-government efforts due to concerns regarding data protection (DP) and data security (DS). We argue that citizens’ understanding of DP and DS is a prerequisite for governments to adequately address citizens’ concerns regarding e-government initiatives.