Analysis of Software Aging Impacts on Plant Anomaly Detection with Edge Computing Edge computing allows dataintensive analytic processes running on a cloud server to migrate to a local computing environment near the data sources, and as a result the architecture can benefit from a significant bandwidth reduction as well as improved security. However, due to the scarcity of resources on an edge device, a problem of software aging is likely to occur after longtime execution. The consequence of software aging should be significant, whereas such a risk has not been studied in the previous literature. In this paper, we propose a deterministic and stochastic Petri Net (DSPN) to quantitatively analyze the impacts of software aging phenomenon on a cyberphysical system using edge computing. As a data analytic application using realworld sensor data, we consider anomaly detection for a water treatment plant. We introduce two applicationoriented performance measures, namely detection loss probability and the expected number of false alarms in terms of plant anomaly detection. Our numerical and simulation experiments on the proposed DSPN show that software aging clearly has negative impacts on the defined performance measures that reveal the necessity of greater attention to software aging issues in edge computing systems.

Towards Testing the Software Aging Behavior of Hypervisor Hypercall Interfaces With the continuing rise of cloud technology hypervisors play a vital role in the performance and reliability of current services. As longrunning applications, they are susceptible to software aging. Hypervisors offer socalled hypercall interfaces for communication with the hosted virtual machines. These interfaces require thorough robustness to assure performance, security, and reliability. Existing research either deals with the aging properties of hypervisors in general without considering the hypercalls or focusses on finding hypercall related vulnerabilities. In this work, we discuss open challenges regarding hypercall interfaces. To address these challenges, we propose an extensive framework architecture to perform robustness testing on hypercall interfaces. This framework supports extensive test campaigns as well as the modeling of hypercall interfaces.